Electricity Consumption and Efficiency Measures in Public Buildings: A Comprehensive Review

Abstract

Industrialization and the expansion of service sectors have led to a significant increase in electricity consumption. This rising demand has also been observed in public buildings, which account for a considerable share of total electrical energy use. Coupled with the upward trend in energy prices, this increase has likewise escalated electricity costs in these sectors. The objective of this review is to compile studies that analyze electricity consumption in large public buildings, with a primary focus on universities, as well as works that propose or implement energy-saving measures aimed at reducing consumption. Throughout this review, it is observed that effective monitoring of consumption as well as the use of demand management systems can reduce electricity consumption by up to 15%. Additionally, the studies collected consistently highlight the need for improvements in real-time data monitoring to enhance energy management. Buildings that implement energy-saving measures achieve reductions in demand exceeding 10%, while those incorporating renewable energy systems are capable of covering between 40% and 50% of their energy needs. Of these systems, solar photovoltaic technology is that most widely adopted by public buildings, primarily due to its adaptability to the architectural characteristics and operational requirements of such facilities. This review underscores the substantial impact that optimized monitoring and renewable energy integration can have on reducing the energy footprint of large public facilities.

1. Introduction

Electricity consumption in industrialized countries is notably increasing due to the use of services, innovation, and industrialization [1,2,3,4]. Additionally, energy consumption in public buildings is further increased by the electrification of certain services that play a significant role in overall electricity consumption, such as heating, ventilation, and air conditioning [5]. Moreover, not only has the demand for electricity increased, but the price of energy has also risen in recent years [6,7], becoming strained since COVID-19. Additionally, in February 2022 due to the Russia–Ukraine crisis, it reached an average of 545 €/MWh in Spain in March of that same year, with a price of 700 €/MWh on the eighth day of that month [8]. This caused energy costs for households and industry to increase between 62.6% and 112.9% [9]. According to the OMIE, which is the nominated electricity market operator (NEMO) for managing the day-ahead and intraday electricity markets in the Iberian Peninsula, 2022 saw the highest average energy price in recent years, with a value of 167.72 €/MWh, as shown in Figure 1. Electricity consumption in countries like Spain had been increasing by an average of 4.2% annually, with electricity consumption in industrialized countries continuing to rise [10]. It is worth noting that this is not true across the board, as since 2018, annual electricity consumption in Spain has been decreasing [11].

Climate policies that increase the cost of fossil fuels incentivize the expansion of renewable energy capacity and accelerate the transition towards such energies due to price effects [12]. These policies, both at national and international level, aim for greater renewable energy generation. One such policy is the Europe 2050 Strategy [13], the objectives of which partly focus on a transition to renewable energy by increasing its generation share and improving energy efficiency across all sectors, including buildings. Electricity consumption in buildings accounts for between 20% and 40% of total electrical energy consumption [14,15]. Furthermore, buildings are responsible for 35% of CO₂ emissions in the EU [16], a figure of concern to organizations such as the European Union. In countries like China, consumption has increased considerably, with an average rise in electricity consumption of 10% recorded over a decade ago [17]. Regarding other types of consumption, such as residential, between 2000 and 2018, consumption in China increased from 99.5 billion kWh to 552.1 billion kWh, marking a 4.55-fold increase [18]. In 2023, electricity consumption in Spain decreased by 2.3% compared to 2022, falling to a total of 244,665 GWh. This reduction is attributed to energy efficiency measures adopted by consumers and high levels of inflation [19]. Figure 1 shows that the average arithmetic price of the daily electricity market in 2023 was 87.69 €/MWh, 91.3% lower than in 2022 [8], leading to a reduction in electricity bills in 2023. However, it is still necessary to study the behavior of electricity consumption in all types of buildings to seek to reduce the consumption of electrical energy [20].

1.1. Need for Data Monitoring

The economic sustainability of a country is closely linked to its degree of energy dependence, making it essential to utilize all available mechanisms to detect inefficiencies and identify opportunities for energy savings [21]. Therefore, it is crucial to implement an initiative that involves establishing a monitoring system to evaluate energy consumption in public buildings, with the aim of promoting improvements in energy efficiency [22]. This requires the use of consumption statistics, conducting dynamic inspections, and performing detailed audits of electrical usage in buildings [17,23,24]. When systematically analyzed, the vast amount of data on electricity consumption, derived from smart meters and billing systems, offers countless opportunities, such as studying consumption patterns and predictions. It has been demonstrated that this type of analysis can result in a reduction of up to 20% in electricity consumption [25], with it thus being necessary to disseminate knowledge about the benefits of energy audit practices [26]. Other strategies are also used, such as demand-side management (DSM), the aim of which is to adjust electricity consumption to the supply available, particularly at times of high demand, thereby reducing costs, increasing energy efficiency, and reducing environmental impact [27]. New intelligent approaches have recently been promoted for data monitoring in building supervision and energy efficiency, including a system based on the Internet of Things, which is also low-cost [28]. This system utilizes the recording of time series data based on Internet of Things protocols, and, when combined with contactless sensors, eliminates the limitations of monitoring a restricted number of points and the challenges of ensuring data integrity in its optimal form. Therefore, the monitoring of electrical energy consumption data provides us with many possibilities, as can be clearly seen in Figure 2.

1.2. Motivation

Energy consumption monitoring systems are currently focused on software development to achieve energy-saving and emission reduction goals through the analysis and tracking of building energy consumption. However, the analysis of the management system and the organizational structure related to energy consumption monitoring has been overlooked [22]. There is extensive research dedicated to the study of electricity consumption, with the goal of predicting energy usage based on factors such as occupancy levels, building age, or outdoor temperature [29,30,31]. It is now common to find studies of this nature conducted in public buildings, such as universities, with the purpose of determining the cost of the energy demanded by public entities based on forecasts [32,33]. However, fewer studies focus on electricity consumption in public buildings and institutions based on real data, as many rely on surveys or estimates [34]. The analysis of actual energy consumption in these buildings is crucial for developing specific energy plans and strategies to optimize demand, whether over a defined period or on a continuous basis [35]. Once energy-saving measures have been implemented, studying consumption allows changes in demand patterns to be evaluated, from both an energy and an economic perspective [36]. Additionally, many buildings choose to install renewable energy technologies to offset their energy demand, making the analysis of their generation and the resulting consumption essential for assessing their contribution to the building’s sustainability [37].

This review focuses on works that examine electricity consumption in public buildings with high energy demands, such as universities and government administration buildings, where consumption analysis is particularly important due to their size and public nature. It is of vital importance to study the consumption and energy efficiency measures in these types of buildings, as the high energy prices in recent years have led to significant changes in their billing. While residential or private buildings have been extensively studied, there is a growing need to investigate how to optimize energy consumption in these public entities.

The remainder of the paper is structured as follows: Section 2 presents the different studies collected in this paper, where different results are obtained and their methodologies are discussed. Section 3 is a discussion of the collected studies, interpreting the results and indicating the limitations of each of the studies. Finally, Section 4 develops the conclusions, indicating the key findings, implications for the field, and final reflections.

2. Research Methodologies

This section provides a thorough review of various articles that, as noted in Section 1.2, focus on research related to the use of electrical energy in public buildings. These studies not only concentrate on the detailed examination of energy consumption, but also investigate the implementation of energy-saving strategies intended to enhance efficiency in these facilities. Additionally, renewable energy system projects are examined as comprehensive solutions to reduce reliance on traditional energy sources and minimize carbon emissions [38]. The primary focus of the review is on large-scale public structures with high energy consumption, such as universities, hospitals, and other public institutions, which account for a considerable percentage of the sector’s total energy use. These organizations are significant not only because of the size and variety of their infrastructures, but also due to the opportunities they provide for the deployment of emerging technologies and energy management strategies that could be replicated in similar contexts [39,40]. Figure 3 shows the methodology employed in this work, which is structured around several key steps to ensure a comprehensive and systematic approach. It begins by identifying the objectives pursued by the study, which serve as the foundation to guide the research process. This is followed by an extensive search for previous works, intended to compile the relevant literature and contextualize the study within the existing body of knowledge. Finally, the methodology involves a detailed review and analysis of each of the works identified, ensuring that the insights gained contribute meaningfully to the research objectives and provide a robust basis for the conclusions drawn. Figure 4 shows the publication years of the three types of articles reviewed in this work.

2.1. Study of Consumption in Public and/or Educational Institutions

Buildings account for one-third of primary energy consumption in industrialized countries [18]. Additionally, improving energy efficiency is a current priority of the European Union, which seeks to promote more efficient consumption practices [41]. Therefore, it is essential to collect detailed information on building characteristics, consumption patterns, and energy performance, by means of leveraging programs, studies, and surveys [42].

Energy consumption in public buildings comprises multiple uses, including air conditioning, ventilation, lighting, envelops, hot water, elevators, and office equipment, among others [43]. Improvements in building thermal performance and energy efficiency have helped reduce energy consumption, especially in heating. However, the increase in electronic device usage and the growing demand for comfort have partially counteracted these advances, maintaining electricity consumption at high levels [44]. Various tools are available to better evaluate and understand electricity consumption, including models based on historical consumption data [45]. Moreover, management tools such as DSM [27] and energy management systems (EMS) [46] aim to reduce electricity bills and peak loads. For instance, a study in an office building in India revealed an annual savings potential of 231,656 kWh, with an initial investment leading to a payback period of 1.7 years, which was considered an early return [47].

Regarding data monitoring, Table 1 presents various methodologies used, such as surveys of building occupants [43,48,49], electronic sources [34], electricity bills [50], and smart meters [51,52,53]. A number of studies have measured and reported average consumption per area, such as one at Griffith University (Australia), which recorded an average consumption of 170 kWh/m² [54]. In contrast, Yale University reported an average of 739 kWh/m², and another university in the U.S. averaged 265 kWh/m². A study in Jiangbei District, Chongqing [55], determined that the average consumption in schools was 33 kWh/m², a lower value than in universities due to lower equipment needs and energy demands. In Certaldo, Tuscany [56], public buildings recorded an average consumption of 345 kWh/m². In northern China, an analysis of different types of public buildings found that schools averaged 103.27 kWh/m², while hospitals averaged 194.64 kWh/m² [43], although other studies report different values. For example, a study of hospitals in China found a consumption of 50.5 kWh/m², while another in the cold climate region of China reported an average consumption of 187.85 kWh/m² [55]. For office buildings, the average consumption is 188.36 kWh/m², while a study in large buildings in Beijing, Dalian, Ji’nan, and Harbin reported an average of 76.56 kWh/m² [44]. Another analysis in Jiangbei District, Chongqing [55], revealed that government offices had an average consumption of 53.9 kWh/m². These results show that consumption in buildings of the same nature can vary significantly based on a wide variety of factors, such as building size, number and type of loads, use, and geographic location.

As mentioned, energy management systems aim to identify and understand energy consumption patterns in order to optimize them, thus engaging stakeholders [57]. Studies have investigated electricity demand to analyze consumption behavior, such as one conducted at the University of Bordeaux [51], France, where smart meters were implemented to study electricity demand, while at the Polytechnic University of Madrid, Spain, comparable systems were installed for the same purpose [52].

Improved knowledge of energy consumption patterns facilitates the identification of causes of higher consumption, enabling future energy efficiency measures to be established. This is exemplified by various buildings that monitor their electricity consumption data, such as the University of Malaysia [34]. Another study at the same university [58] obtained electricity consumption patterns, identifying peak and minimum demand times. Additionally, a breakdown of electricity consumption by building and equipment type was conducted, finding that 50% of the consumption was attributed to air conditioning, 31% to electrical equipment, 19% to lighting, and 1% to other uses. This was not the only study to categorize the percentage of consumption by load type; an energy analysis of an institutional building in Malaysia [26] showed that air conditioning accounted for 34% of consumption, lighting 18%, computers 10%, and elevators 7%. In Greece, an analysis of public bank offices [56] determined that air conditioning accounted for 48% of total consumption, while lighting accounted for 35% and office equipment 7%. A study in an office building in India [47] found that 45% of consumption was due to air conditioning, 14% to lighting, 12% to uninterrupted power systems, and 13% to other systems. This pattern is typical in public buildings such as offices, while it tends to vary in universities due to different loads and activities. The studies reviewed clearly indicate that air-conditioning equipment represents the most energy-intensive component in public buildings, accounting for a significant portion of overall energy consumption. Specifically, it is observed that air-conditioning systems typically consume between 35% and 50% of the total energy used in such facilities. This trend is consistent across various types of public buildings, including offices, educational institutions, and healthcare facilities, highlighting the critical role of climate control systems in shaping energy usage patterns. These findings are further corroborated by a study focused on energy efficiency in public buildings [40], which reported similar consumption values, reinforcing the conclusion that air-conditioning systems are a primary target for energy-saving interventions.

Another study at the University of Bordeaux (France) [48] analyzed electricity demand and observed that consumption rises at 07:00, remains constant until 11:00, and then decreases between 14:00 and 23:00, coinciding with academic hours. Another study at the University of Castilla-La Mancha, Spain [59], also examined consumption patterns, observing that 41% of electricity is consumed by research buildings. Additionally, they identified five distinct consumption patterns: winter, spring, working summer, August vacation, and fall, with the lowest consumption recorded during August, corresponding to the university’s closure. All the studies agree that consumption during working hours is higher than at weekends and public holidays. Another notable aspect in the studies reviewed is the energy consumption of a building depending on its year of construction. Research indicates that older buildings, due to construction methods such as envelope and insulation types, tend to have higher electricity consumption compared to new buildings [60]. This trend was confirmed in a study on schools in Manitoba, Canada [61], which found that older schools showed significantly higher energy consumption. This is not a one-off case, as another study on public schools in Luxembourg [16] demonstrated a positive correlation between the year of construction and energy usage, meaning that older buildings have higher consumption rates. Therefore, although newer buildings benefit from improved construction methods, their energy consumption will ultimately depend on the type of activity and connected loads [58].

As shown in Table 1, data acquisition for energy consumption typically relies on monitoring via smart readers or acquiring data directly from the utility company. However, several studies lacked complete datasets due to measurement errors. Additionally, various studies have collected consumption data through surveys and electronic sources, which tends to reduce accuracy. Regarding sampling periods, monthly consumption data is the most common, with a data collection period predominantly spanning one year. Most studies fall within the years 2011 to 2021, with fewer publications outside this timeframe. In terms of the number of buildings analyzed, no clear trends were identified, although the majority of studies focused on more than one building. Finally, the last column of Table 1 summarizes the main findings from each referenced study.

Table 1. List of references focused on the analysis of electricity consumption in public buildings.

Ref.	Year	Building Type	No. Buildings Analyzed	Database Acquisition	Dataset		Analysis Performed
					Sampling Period	Period
[62]	2000	University of Melbourne	5 building categories depending on their use	Estimation based on annual lighting demand hours	Annual consumption by category	-	Study of lighting alternatives to achieve a reduction in electricity consumption
[51]	2002	University of Bordeaux (France)	-	Utility readings	Annual consumption	1 year	Implements a tool to analyze electrical demand
[55]	2009	Public buildings in Jiangbei District of Chongqing	72 buildings (only 14 analyzed)	Energy audits and building measurements	Annual consumption	-	Obtains average consumption by type of building. Markets consume 253.1 kWh/m2, offices 116.2 kWh/m2, hotels 132.2 kWh/m2, schools 33 kWh/m2, government offices 53.9 kWh/m2 and hospitals 50.5 kWh/m2.
[56]	2011	Public bank branches	39 bank branches (only 11 analyzed)	Bills	Monthly consumption	6 years	The average annual energy consumption is 345 kWh/m2. HVAC consumes 48%, lighting 35%, and other office and electronic equipment 17%.
[63]	2012	Public buildings managed by municipalities in Certaldo, Tuscany	Schools, public offices, cemetery, etc.	-	Annual consumption by type of building	2 years	Public lighting accounts for 64% of total consumption, followed by schools with 13%.
[58]	2012	University of Malaysia	-	Utility readings	1 h	1 year	Consumption patterns, breakdown of electricity consumption by building and electrical appliances. Consumption on weekdays is higher than at weekends
[16]	2014	Public schools	68 buildings (4 sports, 22 pre-school, 30 primary and 12 secondary buildings)	Data acquisition system per building (not all of them)	Annual consumption	1 year	There is a positive linear correlation between year of construction and electricity consumption, with most buildings showing higher than expected consumption.
[22]	2015	Public buildings (government, markets, exhibition and sport buildings)	20 buildings	Data acquisition system from utility readings	-	3 years	Obtains the average consumption per area for each type of building.
[47]	2015	Public office in India	1 building	Data acquisition system (16 supply points)	1 min	5 years	Energy audit to determine consumption. 45% comes from air conditioning, 14% from lighting, 12% from UPS systems and 13% from other systems. Identifies key areas of potential savings.
[43]	2017	Public buildings (type not specified)	119 typical buildings	Questionnaire	Yearly consumption	1 year	The average energy consumption per area is 188.36 kWh/m2 in offices, 194.64 kWh/m2 in hospitals and 103.27 kWh/m2 in schools.
[64]	2017	University of Mangosuthu (South Africa)	-	Energy meter at substation	30 min	2 months	Consumption peaks of 220 kWh, average consumption of 150 kWh and highest expenditure due to air conditioning
[50]	2017	University of Tun Hussein Onn (Malaysia)	1 building (library)	Bills	Monthly consumption	1 year	Total energy wastage of 63.5 MWh due to misuse of lighting, air flows, air conditioning and misuse of electrical equipment.
[61]	2017	Manitoba schools, Canada	129 schools (only 30 analyzed)	Data provided by local company	Monthly consumption	10 years	Older buildings consume more energy than new buildings. Schools that renovate HVAC or the envelope decrease energy consumption.
[44]	2017	Office buildings	56 typical office building (19 non-government offices and 37 government office)	Data acquisition system	Monthly consumption	-	Non-government offices have less variability in consumption, while government offices have a more concentrated range. The average annual consumption is 76.56 kWh/m2 in government offices and 68.14 kWhm2 in non-government offices.
[57]	2017	University of Applied Sciences of Western Switzerland	1 building	Data acquisition by smart meters	15 min	-	Implement an energy management system (BEMS) in order to integrate stakeholders to monitor consumption and increase energy efficiency.
[54]	2018	University of Griffitch (Germany)	50 academic offices, 11 administration offices, 8 teaching buildings, 6 research buildings and 5 libraries	Data acquisition system per building	1 h	2 years	Libraries and research buildings are those that consume the most energy. The average consumption in this campus is 170 kWh/m2
[48]	2018	University of Bordeaux (France). Technology and Science Campus	30 in three categories: Teaching, research, and administration	Storage server	Hourly, but only managed to represent 45% of the data	3 years	Analysis of electricity use by building type and consumption patterns
[65]	2018	Malang State University, Indonesia	1 building (Electrical Engineering)	Measurement of voltage and current data on each phase and in the neutral current	1 s	14 s	Performs data monitoring using an IoT system (Internet of Things), allowing users to see values such as active, reactive, apparent power or power factor.
[48]	2019	University	50 Universities	Online questionnaire	Annual percentage	-	Makes recommendations to improve energy efficiency
[66]	2019	University of Johannesburg	Three categories: residences, student centers, and other buildings	Utility readings	Monthly consumption	1 year	Calculates the percentage of consumption of the campus total for each building type.
[49]	2019	Public schools	17 schools	Questionnaire	Annual consumption of every school	1 year	Electricity accounts for 30.55% of total consumption and 31.71% of the cost. Laboratories and research centers are the largest consumers.
[52]	2020	Polytechnic University of Madrid (Spain)	-	Utility readings	Monthly average values	3 years	Analyzes campus consumption by applying simplifications excluding buildings
[34]	2021	University of Malaysia	11 buildings	Expert surveys, electronic sources, and documentation	Annual consumption by building	1 year	Analysis of the main elements contributing to increased consumption.
[26]	2021	Institutional building in Malaysia	1 building	Estimation by equations	Monthly consumption	3 years	Air conditioning accounts for 34%, lighting for 18%, computers for 10% and lifts for 7%.
[22]	2021	Hospital buildings	30 hospitals (only 12 analyzed)	Data acquisition system by building	-	3 years	Consumption is compared according to the architectural layout. Average consumption of 187.85 kWh/m2. The highest consumption is obtained in summer by the cooling systems.
[67]	2021	Educational building	1 building	Data acquisition system by 64 submeters (measures the consumption of different systems)	5 min	1 year	There is an electricity consumption gap of 2.41 times, and 48% of annual consumption occurs during non-working hours.
[68]	2021	Different types	1 office, 1 laboratory, 1 library and 1 hospital	Data acquisition system by building	1 h	1 year	Consumption increases with the level of occupancy. The highest consumption is found in laboratories and offices.
[59]	2023	University of Castilla La Mancha (Spain). Albacete Campus	16 buildings, focused on 4	Data acquisition system from utility readings	Hourly and quarter-hourly	1 year	Analysis of electricity use, electrical, seasonal, and daily patterns

Table 1. List of references focused on the analysis of electricity consumption in public buildings.

Ref.	Year	Building Type	No. Buildings Analyzed	Database Acquisition	Dataset		Analysis Performed
					Sampling Period	Period
[62]	2000	University of Melbourne	5 building categories depending on their use	Estimation based on annual lighting demand hours	Annual consumption by category	-	Study of lighting alternatives to achieve a reduction in electricity consumption
[51]	2002	University of Bordeaux (France)	-	Utility readings	Annual consumption	1 year	Implements a tool to analyze electrical demand
[55]	2009	Public buildings in Jiangbei District of Chongqing	72 buildings (only 14 analyzed)	Energy audits and building measurements	Annual consumption	-	Obtains average consumption by type of building. Markets consume 253.1 kWh/m2, offices 116.2 kWh/m2, hotels 132.2 kWh/m2, schools 33 kWh/m2, government offices 53.9 kWh/m2 and hospitals 50.5 kWh/m2.
[56]	2011	Public bank branches	39 bank branches (only 11 analyzed)	Bills	Monthly consumption	6 years	The average annual energy consumption is 345 kWh/m2. HVAC consumes 48%, lighting 35%, and other office and electronic equipment 17%.
[63]	2012	Public buildings managed by municipalities in Certaldo, Tuscany	Schools, public offices, cemetery, etc.	-	Annual consumption by type of building	2 years	Public lighting accounts for 64% of total consumption, followed by schools with 13%.
[58]	2012	University of Malaysia	-	Utility readings	1 h	1 year	Consumption patterns, breakdown of electricity consumption by building and electrical appliances. Consumption on weekdays is higher than at weekends
[16]	2014	Public schools	68 buildings (4 sports, 22 pre-school, 30 primary and 12 secondary buildings)	Data acquisition system per building (not all of them)	Annual consumption	1 year	There is a positive linear correlation between year of construction and electricity consumption, with most buildings showing higher than expected consumption.
[22]	2015	Public buildings (government, markets, exhibition and sport buildings)	20 buildings	Data acquisition system from utility readings	-	3 years	Obtains the average consumption per area for each type of building.
[47]	2015	Public office in India	1 building	Data acquisition system (16 supply points)	1 min	5 years	Energy audit to determine consumption. 45% comes from air conditioning, 14% from lighting, 12% from UPS systems and 13% from other systems. Identifies key areas of potential savings.
[43]	2017	Public buildings (type not specified)	119 typical buildings	Questionnaire	Yearly consumption	1 year	The average energy consumption per area is 188.36 kWh/m2 in offices, 194.64 kWh/m2 in hospitals and 103.27 kWh/m2 in schools.
[64]	2017	University of Mangosuthu (South Africa)	-	Energy meter at substation	30 min	2 months	Consumption peaks of 220 kWh, average consumption of 150 kWh and highest expenditure due to air conditioning
[50]	2017	University of Tun Hussein Onn (Malaysia)	1 building (library)	Bills	Monthly consumption	1 year	Total energy wastage of 63.5 MWh due to misuse of lighting, air flows, air conditioning and misuse of electrical equipment.
[61]	2017	Manitoba schools, Canada	129 schools (only 30 analyzed)	Data provided by local company	Monthly consumption	10 years	Older buildings consume more energy than new buildings. Schools that renovate HVAC or the envelope decrease energy consumption.
[44]	2017	Office buildings	56 typical office building (19 non-government offices and 37 government office)	Data acquisition system	Monthly consumption	-	Non-government offices have less variability in consumption, while government offices have a more concentrated range. The average annual consumption is 76.56 kWh/m2 in government offices and 68.14 kWhm2 in non-government offices.
[57]	2017	University of Applied Sciences of Western Switzerland	1 building	Data acquisition by smart meters	15 min	-	Implement an energy management system (BEMS) in order to integrate stakeholders to monitor consumption and increase energy efficiency.
[54]	2018	University of Griffitch (Germany)	50 academic offices, 11 administration offices, 8 teaching buildings, 6 research buildings and 5 libraries	Data acquisition system per building	1 h	2 years	Libraries and research buildings are those that consume the most energy. The average consumption in this campus is 170 kWh/m2
[48]	2018	University of Bordeaux (France). Technology and Science Campus	30 in three categories: Teaching, research, and administration	Storage server	Hourly, but only managed to represent 45% of the data	3 years	Analysis of electricity use by building type and consumption patterns
[65]	2018	Malang State University, Indonesia	1 building (Electrical Engineering)	Measurement of voltage and current data on each phase and in the neutral current	1 s	14 s	Performs data monitoring using an IoT system (Internet of Things), allowing users to see values such as active, reactive, apparent power or power factor.
[48]	2019	University	50 Universities	Online questionnaire	Annual percentage	-	Makes recommendations to improve energy efficiency
[66]	2019	University of Johannesburg	Three categories: residences, student centers, and other buildings	Utility readings	Monthly consumption	1 year	Calculates the percentage of consumption of the campus total for each building type.
[49]	2019	Public schools	17 schools	Questionnaire	Annual consumption of every school	1 year	Electricity accounts for 30.55% of total consumption and 31.71% of the cost. Laboratories and research centers are the largest consumers.
[52]	2020	Polytechnic University of Madrid (Spain)	-	Utility readings	Monthly average values	3 years	Analyzes campus consumption by applying simplifications excluding buildings
[34]	2021	University of Malaysia	11 buildings	Expert surveys, electronic sources, and documentation	Annual consumption by building	1 year	Analysis of the main elements contributing to increased consumption.
[26]	2021	Institutional building in Malaysia	1 building	Estimation by equations	Monthly consumption	3 years	Air conditioning accounts for 34%, lighting for 18%, computers for 10% and lifts for 7%.
[22]	2021	Hospital buildings	30 hospitals (only 12 analyzed)	Data acquisition system by building	-	3 years	Consumption is compared according to the architectural layout. Average consumption of 187.85 kWh/m2. The highest consumption is obtained in summer by the cooling systems.
[67]	2021	Educational building	1 building	Data acquisition system by 64 submeters (measures the consumption of different systems)	5 min	1 year	There is an electricity consumption gap of 2.41 times, and 48% of annual consumption occurs during non-working hours.
[68]	2021	Different types	1 office, 1 laboratory, 1 library and 1 hospital	Data acquisition system by building	1 h	1 year	Consumption increases with the level of occupancy. The highest consumption is found in laboratories and offices.
[59]	2023	University of Castilla La Mancha (Spain). Albacete Campus	16 buildings, focused on 4	Data acquisition system from utility readings	Hourly and quarter-hourly	1 year	Analysis of electricity use, electrical, seasonal, and daily patterns

2.2. Energy-Saving Measures to Reduce Consumption in Public Buildings

In recent years, interest in energy-saving measures and environmental awareness has grown, driven by current policies [69]. In Europe, countries like Spain have experienced increased electricity costs due to natural gas prices and global economic recovery post-COVID-19 [70], negatively impacting energy bills for households and businesses [71]. As noted in Section 1.2, a better understanding of energy consumption patterns enables the proposal of more effective savings measures [58], ideally visualizing usage behavior throughout the day. However, there is still a lack of mandatory measures to promote energy savings and raise employee awareness in this area [22].

To implement energy-saving measures, many studies utilize pre-existing data on electricity consumption, whether through electronic sources [34], consumer surveys [43,46], software simulations [72,73], or real-time measurement [50,58,74], among others. Table 2 compiles the studies analyzed on energy efficiency measures implemented in public buildings, detailing the data types used, measures applied, and main results achieved.

A study at a university campus in India employs DSM strategies [27], a method widely used in various countries to reduce emissions [75]. DSM focuses on managing load distribution to lower peak demand and reduce electricity costs. In this study, DSM implementation reduced peak demand from 100.92 kW to 90.92 kW, and average load from 44.46 kW to 43.42 kW. Other studies also monitor consumption to identify peak usage times, as seen in schools and universities in Guangdong, China [46], which achieved savings of up to 15%, or in public buildings in China [22], where analyzing energy use by building type and monitoring consumption led to targeted energy-saving measures, such as replacing doors and windows, upgrading building envelopes, and adjusting air conditioning settings.

In another study, a detailed energy audit in a public office in India [47] involved monitoring consumption data from 16 supply points, creating electrical diagrams, and measuring performance. This audit identified waste areas and proposed energy-saving measures, with key areas being air conditioning, lighting, uninterruptible power supply systems (UPSs), and the installation of an energy monitoring and management system (EMTS). Analysis revealed that improvements to air conditioning would reduce consumption by 40%, while implementing an EMTS system would reduce it by 5%. Furthermore, another study reports that the installation of elements with monitoring provides a 54% reduction over elements without this capability [74].

Many studies highlight air conditioning, as it constitutes one of the largest loads in public buildings [22,57,76]. Measures in this area vary: for instance, at a university in Malaysia [34], maintaining a 24 ºC temperature, optimizing schedules, and selecting efficient equipment are recommended. Similarly, at Osaka University in Japan [74], inverter technology enhances air conditioning efficiency, reducing consumption, maintaining stable temperatures, and extending equipment life, with up to 20% efficiency gains [77]. This is not the only example of modernization; in several public buildings in China, frequency conversion technology in air-conditioning systems has also been applied [22]. Another measure is the incorporation of heat recovery systems into air conditioning units to boost energy efficiency, as proposed in an administrative building in Chengdu, China [72]. In addition to modernization, some proposals involve replacing current air-conditioning systems with more suitable alternatives, as seen in studies of other public buildings in China [43]. A study on a public building in India [47] recommends installing a variable flow cooling system (IVRF), which adjusts cooling in real-time based on area-specific needs, thus avoiding unnecessary energy consumption. Another measure in this area is adjusting operation times, as implemented at India’s College of Engineering [27] and a university in Malaysia [34].

Other energy-saving measures focus on preserving a building’s thermal energy while maintaining ventilation system efficiency by properly insulating areas to retain cooling or heating, constructing envelopes with appropriate transfer coefficients [34,43,73], or replacing them altogether [72]. Windows play a crucial role in thermal insulation, as their materials and insulation quality directly impact the thermal conditions of a given zone. Therefore, several studies advocate replacing windows with better-insulated alternatives [63,73], while others focus on improving window insulation using enhanced coatings or alternative materials [50]. Doors, like windows, are also crucial, with studies suggesting insulation improvements [22]. Another area of energy-saving measures is that of lighting, both indoors and outdoors. An effective solution to reduce energy consumption and enhance energy efficiency, both in domestic and public environments, is the replacement of traditional lighting with LED technology [78,79,80]. These systems can achieve efficiencies of up to 330 lm/W, surpassing traditional technologies [81], being approximately 70% more efficient and having a longer lifespan [82]. Even before the advent of LED, several studies suggested replacing traditional lighting with sodium vapor lamps [56,69] or compact fluorescent lamps [83]. However, numerous studies now recommend replacing existing traditional lighting in buildings with LED technology [26,34,50,74]. Additional measures include reducing the number of luminaires, installing motion sensors, and decreasing lighting usage time [50]. Regarding measures for office equipment, the waiting times for screen suspension have been reduced in order to decrease electricity consumption. The information presented in Table 2 reveals that the sampling period is typically reported as monthly consumption data, although shorter intervals, such as hourly data, are also occasionally included. Regarding the data collection period, most studies encompass a one-year span. A few, however, extend up to five or six years of monitoring. A noteworthy aspect highlighted in the table is that only one study documented actual post-implementation energy consumption following the application of efficiency measures, whereas the remaining studies rely solely on estimated reduction data.

Table 2. List of references focused on the implementation of energy-saving measures in public buildings.

Ref.	Year	Building Type	No. Buildings Analyzed	Database Acquisition	Dataset		Analisys Performed	Study Consumption After Measures
					Sampling Period	Period
[69]	2004	University of Valencia (Spain)	Faculty of Physics of Burjassot	-	Monthly consumption	1 year	Proposes replacing luminaires with sodium vapor, saving 37.4%. It also proposes implementing renewable energy sources.	No
[56]	2011	Public bank branches	39 bank branches (only 11 analyzed)	Bills	Monthly consumption	6 years	Replacing to electronic ballasts reduces power by 15–22%, saves 6.5–12% energy, and 22–29 kWh/m2.	No
[58]	2012	University of Malaysia	-	Utility readings	1 h	1 year	Changes to luminaires, monitor off-time, and operation hours save 285,285 kWh/year.	No
[63]	2012	Public buildings managed by municipalities in Cerataldo, Tuscany	Schools, public offices, cemetery, etc.	-	Annual consumption by type of building	2 years	55% of interventions targeted schools/stadiums; 29% added PV, 21% replaced windows, and 14% improved lighting, with a 10–15 year payback.	No
[46]	2013	Universities and colleges in Guangdong Province	98 buildings	Buildings questionnaire (74.8% completed)	Yearly consumption	5 years	Proposes monitoring, energy supervision (15% savings), low-consumption devices, and solar water heating.	No
[22]	2015	Public buildings from China (government, markets, exhibition, and sport building)	20 buildings	Data acquisition system from utility readings	-	3 years	Analyzes consumption and suggests improving envelopes, windows, HVAC, and equipment, without reporting savings.	No
[47]	2015	Public office in India	1 building	Data acquisition system (16 supply points)	1 min	5 years	Energy improvements save: IVRF (67,530 kWh/year), EMTS (35,145 kWh/year), AC maintenance (50,342 kWh/year), UPS adjustment (30,660 kWh/year), power factor (37,755 kWh/year), and  lighting (10,224 kWh/year).	No
[73]	2016	Public buildings in Italy	Villa Sciarra Building, Italian Ministry of Economic Development (MiSE), Italian Space Agency (ASI) and Ex Bank Napoli.	Simulated consumption by STIMA 10	Monthly	4 years	Proposes envelope upgrades, window replacement, thermostatic valves, and renewables to improve energy class and reduce consumption.	No
[43]	2017	Public buildings from China (type not specified)	119 typical buildings	Questionnaire	Yearly consumption	1 year	Improvements in 119 buildings include air conditioning, energy-saving lamps, and exterior walls with better thermal insulation, resulting in potential savings of 56,649.61 × 104 kWh.	No
[50]	2017	University of Tun, Hussein On (Malaysia)	1 building (library)	Bills	Monthly consumption consumption	1 year	Measures include LED lighting, sensors, fewer luminaires, and window film, saving 681,504 kWh annually.	No
[74]	2017	University of Osaka (Japan)	Only 3 of its campuses	Intranet-based measurement system	30 min	5 years	Measures include LED lighting, more efficient heat sources, and inverter air conditioning, reducing 50,624 MWh/year.	Energy-saving measures and the implementation of PV reduced consumption by 22%.
[83]	2021	University of Bangladesh	Jashore University of Science and Technology	Estimation by power units and hours of operation	Monthly consumption	1 year	Replacing fluorescent lamps with compact fluorescents, saving 21.15%, and installing renewable energy.	No
[27]	2021	University of India	1 (College of Engineering)	Meter reading	1 h	1 year	It implements a DSM system with time shifting for air conditioning and water pumps, reducing energy use and peak demand by 10%.	No
[26]	2021	Institutional building in Malaysia	1 building	Estimation by equations	Monthly consumption	3 years	It plans a three-stage LED lighting change with 7593 lights, saving 72,750 kWh, 110,381 kWh, and 144,386 kWh annually.	No
[34]	2021	University of Malaysia	11 buildings	Expert surveys, electronic resources and documentation	Annual consumption by building	1 year	Use of natural light, LED lighting, and light-colored walls, optimizing air conditioning, choosing efficient appliances, and turning off devices when not in use.	No
[72]	2024	Administration building in Chengdu, China	1 building	Simulated consumption by Design Builder	Monthly consumption	1 year	It promotes heat recovery, photovoltaic glass, and green roofs, achieving total reductions of 235,303 kWh/m2.	No

Table 2. List of references focused on the implementation of energy-saving measures in public buildings.

Ref.	Year	Building Type	No. Buildings Analyzed	Database Acquisition	Dataset		Analisys Performed	Study Consumption After Measures
					Sampling Period	Period
[69]	2004	University of Valencia (Spain)	Faculty of Physics of Burjassot	-	Monthly consumption	1 year	Proposes replacing luminaires with sodium vapor, saving 37.4%. It also proposes implementing renewable energy sources.	No
[56]	2011	Public bank branches	39 bank branches (only 11 analyzed)	Bills	Monthly consumption	6 years	Replacing to electronic ballasts reduces power by 15–22%, saves 6.5–12% energy, and 22–29 kWh/m2.	No
[58]	2012	University of Malaysia	-	Utility readings	1 h	1 year	Changes to luminaires, monitor off-time, and operation hours save 285,285 kWh/year.	No
[63]	2012	Public buildings managed by municipalities in Cerataldo, Tuscany	Schools, public offices, cemetery, etc.	-	Annual consumption by type of building	2 years	55% of interventions targeted schools/stadiums; 29% added PV, 21% replaced windows, and 14% improved lighting, with a 10–15 year payback.	No
[46]	2013	Universities and colleges in Guangdong Province	98 buildings	Buildings questionnaire (74.8% completed)	Yearly consumption	5 years	Proposes monitoring, energy supervision (15% savings), low-consumption devices, and solar water heating.	No
[22]	2015	Public buildings from China (government, markets, exhibition, and sport building)	20 buildings	Data acquisition system from utility readings	-	3 years	Analyzes consumption and suggests improving envelopes, windows, HVAC, and equipment, without reporting savings.	No
[47]	2015	Public office in India	1 building	Data acquisition system (16 supply points)	1 min	5 years	Energy improvements save: IVRF (67,530 kWh/year), EMTS (35,145 kWh/year), AC maintenance (50,342 kWh/year), UPS adjustment (30,660 kWh/year), power factor (37,755 kWh/year), and  lighting (10,224 kWh/year).	No
[73]	2016	Public buildings in Italy	Villa Sciarra Building, Italian Ministry of Economic Development (MiSE), Italian Space Agency (ASI) and Ex Bank Napoli.	Simulated consumption by STIMA 10	Monthly	4 years	Proposes envelope upgrades, window replacement, thermostatic valves, and renewables to improve energy class and reduce consumption.	No
[43]	2017	Public buildings from China (type not specified)	119 typical buildings	Questionnaire	Yearly consumption	1 year	Improvements in 119 buildings include air conditioning, energy-saving lamps, and exterior walls with better thermal insulation, resulting in potential savings of 56,649.61 × 104 kWh.	No
[50]	2017	University of Tun, Hussein On (Malaysia)	1 building (library)	Bills	Monthly consumption consumption	1 year	Measures include LED lighting, sensors, fewer luminaires, and window film, saving 681,504 kWh annually.	No
[74]	2017	University of Osaka (Japan)	Only 3 of its campuses	Intranet-based measurement system	30 min	5 years	Measures include LED lighting, more efficient heat sources, and inverter air conditioning, reducing 50,624 MWh/year.	Energy-saving measures and the implementation of PV reduced consumption by 22%.
[83]	2021	University of Bangladesh	Jashore University of Science and Technology	Estimation by power units and hours of operation	Monthly consumption	1 year	Replacing fluorescent lamps with compact fluorescents, saving 21.15%, and installing renewable energy.	No
[27]	2021	University of India	1 (College of Engineering)	Meter reading	1 h	1 year	It implements a DSM system with time shifting for air conditioning and water pumps, reducing energy use and peak demand by 10%.	No
[26]	2021	Institutional building in Malaysia	1 building	Estimation by equations	Monthly consumption	3 years	It plans a three-stage LED lighting change with 7593 lights, saving 72,750 kWh, 110,381 kWh, and 144,386 kWh annually.	No
[34]	2021	University of Malaysia	11 buildings	Expert surveys, electronic resources and documentation	Annual consumption by building	1 year	Use of natural light, LED lighting, and light-colored walls, optimizing air conditioning, choosing efficient appliances, and turning off devices when not in use.	No
[72]	2024	Administration building in Chengdu, China	1 building	Simulated consumption by Design Builder	Monthly consumption	1 year	It promotes heat recovery, photovoltaic glass, and green roofs, achieving total reductions of 235,303 kWh/m2.	No

Figure 5 presents a box plot illustrating the energy reduction values achieved by various families of energy-saving measures across the studies reviewed. This type of plot adheres to a standardized method, where the central line within each box represents the median, that is, the central value of the variable after the dataset has been ordered. The upper and lower edges of the box correspond to the 75th and 25th percentiles of the distribution, respectively. Outliers are depicted as small black crosses, while the whiskers extend to the most extreme values within the dataset, which are not, however, classified as outliers.

Figure 5 shows the reduction in electricity consumption achieved by different types of energy efficiency measures. For lighting measures, it can be seen that the reduction values are concentrated between 10% and 20% in the blue box, with an average reduction value of 18%, as shown by the red line. The red cross is an outlier as it is a reduction value of 33%. In contrast, the HVAC measures have a wider range of achievable reductions, in which no outliers are found. It is also observed that constructive measures and data monitoring have more concentrated reduction values, with the average reduction in studies applying these measures being around 13–14%. Table 3 categorizes the types of measures implemented across various studies, highlighting that the most commonly applied are those related to lighting.

Table 3. Main energy-saving measures implemented in public buildings.

Energy-Saving Measure Implemented		Work Applying This Measure
Lighting	Change operating hours or reduce luminaires	[34,47,50,58,69,83]
	Change to more efficient luminaires	[26,34,43,50,56,58,63,74,78]
	Installing presence sensors	[50,74]
Air conditioning	Change operating time	[27,34]
	Installing IRVF	[47]
	Preventive maintenance	[34,47]
	Change to more efficient ventilation	[22,43,58,72,74]
Constructive elements	Replacement of windows or doors	[22,50,63,73]
	Replacement envelopes	[22,43,56,72,73]
Consumption monitoring	Implement energy monitoring system	[22,34,46]
	Implement energy management system	[27,46,47]
Office equipment	Change sleep time	[22,34,58]

Table 3. Main energy-saving measures implemented in public buildings.

Energy-Saving Measure Implemented		Work Applying This Measure
Lighting	Change operating hours or reduce luminaires	[34,47,50,58,69,83]
	Change to more efficient luminaires	[26,34,43,50,56,58,63,74,78]
	Installing presence sensors	[50,74]
Air conditioning	Change operating time	[27,34]
	Installing IRVF	[47]
	Preventive maintenance	[34,47]
	Change to more efficient ventilation	[22,43,58,72,74]
Constructive elements	Replacement of windows or doors	[22,50,63,73]
	Replacement envelopes	[22,43,56,72,73]
Consumption monitoring	Implement energy monitoring system	[22,34,46]
	Implement energy management system	[27,46,47]
Office equipment	Change sleep time	[22,34,58]

2.3. Renewable Energy Power Plant Installation to Reduce Consumption in Public Buildings

The previous sections discussed studies monitoring electric energy consumption, allowing for an analysis of consumption patterns and insights into the sources of energy usage. Through such analysis, energy-saving measures can be proposed more effectively as system deficiencies are identified. Furthermore, another measure implemented in buildings is the installation of renewable generation systems to meet electrical demand. This option aims to reduce part of the energy demand in public buildings, which, as noted in Section 1, are typically high consumers. However, these installations require careful evaluation due to their significant capital costs [27]. Additionally, self-consumption is reshaping traditional power grid structures, enabling distributed generation and increasing citizen involvement [48].

The deployment of a renewable energy system, in this case, within a public building such as a university, should not interfere with the institution’s activities. Therefore, the most suitable options are solar photovoltaic energy, piezoelectric energy harvesting (PZT) systems harnessing entrances and exits, revolving doors, and biological waste [84]. The integration of photovoltaic systems in buildings or public spaces is a common practice encouraged by European governments [85], with applications extending to electric vehicle charging as well [86,87].

Due to the characteristics of university campuses, solar PV systems are typically installed on building rooftops, parking structures, and facades [84,85], capitalizing on roof space and the relative heights of buildings [88]. This type of installation is highly recommended for such settings [89,90], although, unlike other solar PV installations, those on university campuses are often not grid-connected [91]. Adopting these measures is viewed not only as a business opportunity but as a means of taking responsibility for the campus’s own energy consumption [92], aligning with European regulatory objectives for responsible consumption and energy efficiency [13].

Although most cases prioritize PV energy, a study by the GreenBuilding Programme investigated energy-saving measures implemented in non-residential buildings [42], showing that, of the renewable energy installations, 35% of the buildings studied implemented PV, 22% implemented solar thermal systems, 18% implemented heat pumps (HP), 12% implemented geothermal, and 11% installed biomass boilers. In many cases, these buildings employed a combination of solar PV, solar thermal, and HP systems.

Regarding solar PV installations, it is essential to understand the current electrical consumption profiles of the public buildings to compare with the solar energy generation of the potential photovoltaic areas in the region, in order to assess viability with costs and the electrical energy produced [92]. Therefore, defining the photovoltaic potential is a prerequisite for performing an economic analysis [85].

A study at the University of Valencia (Spain), specifically on the Burjassot campus [69], simulated two installations, one of 14.4 kWp and another of 4.7 kWp, to reduce energy demand for the external grid. After performing simulations with various inclinations using the FV–Expert software from Censolar (Mairena del Aljarafe, Spain), it was found that the 14.4 kWp installation at 30º provided the highest energy generation. However, due to the long payback period, the decision was ultimately made in favor of the 4.7 kWp installation. A similar approach was taken in the photovoltaic evaluation and economic analysis at the University of Jaén, Spain [85]. In this case, four potential areas for PV system implementation were identified. However, due to the proximity of two of these areas to the secondary substation, only the two remaining areas were selected, resulting in 761 kWp simulated across the selected areas. This study showed an internal rate of return of 6.21%, a positive cumulative net present value (NPV), and a 16-year payback period, covering 25% of the demand. Another solar PV installation was simulated at the Polytechnic University of Madrid (Spain) [52], with a peak power of 3300 kW. The simulation indicated an investment payback period of 11 years, with it being able to cover 40% of the electrical energy demand.

Other studies fail to provide the exact value of demand coverage, as in the case of that on Ciputra University (Indonesia) [93], where a solar PV installation was simulated based on area and module type, yielding a coverage range between 6% and 22%. Higher demand coverage values have been found, such as at Sichuan University in China [94], where a 156 kWp installation simulation showed coverage between 33% and 46% of demand. A similar result was observed at the Technical University of Crete in Greece [91], where a 2000 kWp solar PV installation simulation was expected to cover 47% of the demand.

Energy costs undoubtedly decrease with such installations, as demonstrated at Bangladesh University [83], where the price of energy would decrease from 3.8 BBT/kWh to 2.52 DBT/kWh with a 10.65 kWp PV system. A similar case occurred with the PV installation at the University of New Haven (New England) [95], where energy costs were reduced to 4.29 $/kWh, a value below the state average, and the installation produced 3250 kWh more than initially simulated. Other studies report multiple renewable energy installations at universities, where solar PV energy is always included. At Southampton University (UK) [96], two renewable energy installations were proposed: a 1203 kWp solar PV system and a 12 kW HP system. The solar PV system covered only 4% of the demand due to regional irradiance levels, while the HP system could cover 80% of the campus’s thermal needs. This is not the only example of a university deploying two systems, as West Texas University [97] simulated a 42 kWp solar PV installation alongside a 50 kWp wind turbine. The PV system simulation generated 71,000 kWh/year, with annual savings of $6390 and a reduction of 49.7 tons of CO₂. In contrast, the wind system yielded an estimated 184,500 kWh/year and an annual saving of 11,945$.

Although this review focuses primarily on large public buildings, such as universities, similar installations can be found in facilities like hospitals. In the case of a Primary Hospital in Nigeria [53], the installation (with accumulators) would reduce the energy price from 2.31 €/kWh to 0.58 €/kWh, displacing a diesel generator. This particular study is noteworthy because its investment payback period is less than 3 years. This is primarily due to the cost of the initial generation, as a diesel generator is available. Another study focused on four iconic public buildings in Italy [73], where a 210 kWp PV system was simulated. Additionally, a combinated heat and power (CHP) system was proposed, but not simulated. The solar PV improvements increased the buildings’ energy efficiency, while the CHP system could potentially produce 30% of the necessary electricity and 55% of the required thermal energy, although it remains the most expensive measure. This is not the only example of multiple renewable energy installations in public buildings. Another study on various public buildings in Japan [98] examined a 42 kWp PV system and a potential hydrogen generation plant to utilize excess PV generation. Following the solar PV system’s implementation in 2010, consumption was reduced by 87%, achieving zero energy building status by 2013. The proposed hydrogen generation plant could produce an estimated 10,378 kWh annually, potentially reducing consumption by 51%.

Table 4 summarizes the various studies mentioned, along with other simulated or implemented installations in public entities. It can be seen that the predominant installation type is solar PV, with a wide variation in total installed capacities. It is also noteworthy that most studies employ simulations, with few studies being conducted after the installation phase or involving real-time monitoring to assess actual demand coverage.

Table 4. List of references focused on the implementation of renewable energy installations in public buildings.

Ref.	Year	Institution Name	Renewable Installation	Total Capacity (kWp)	Status	Improvements Obtained
[69]	2004	University of Valencia (Spain)	PV	14.4/4.7	Simulated	Prepares two simulations with the indicated powers and with inclinations of 30º. 35º and 40º, deciding on the 4.7 kWp installation as it has the shortest recovery period.
[99]	2007	University of Jaén (Spain)	PV	200	Installed	The average annual production for the years 2000 to 2003 is 6.40% of campus consumption.
[96]	2011	University of Southampton (UK)	PV	1204	Simulated	The system can only cope with 4% of the consumption due to irradiance levels. Payback period is 5.6 years excluding land costs.
			HP	12	Simulated	Provides at least 80% of the heat demanded by the campus. It is a viable alternative.
[85]	2011	University of Jaén (Spain)	PV	761	Simulated	Simulation of a power of 761 spread over two areas. It will generate 25% of demand, will have a payback period of 16 years and the LCOE price is estimated at 0.13 €/kWh.
[100]	2011	Queensland University (Australia)	PV	1200	Installed	-
[97]	2013	West Texas University	PV	42	Simulated	Estimated at 71,000 kWh/year, saving $6390 per year and reducing carbon dioxide emissions by 49.7 tons.
			Wind turbine	50	Simulated	Estimated at 184,500 kWh/year, with annual savings of $11,945 with the wind characteristics of the area.
[101]	2015	University of Murcia (Spain)	PV	2750	Installed	-
[73]	2016	4 Public buildings in Italy	PV	210	Simulated	The energy efficiency level of each building is improved, reducing the energy consumed per square meter.
			CHP	-	Proposal	This system can produce 30% of the electricity and 55% of the thermal energy needed, with losses of 15%. It is the most expensive measure.
[95]	2016	University of New Haven (New England)	PV	67.27	Installed	Generation in 2015 was estimated at 82,800 kWh, although it was actually 85,244 kWh. The price of the installation was 4.29 $/W, which is lower than the state average.
[91]	2017	Technical University of Crete (Greece)	PV	2000	Simulated	The PV installation will supply 47% of the campus’s annual electricity consumption, with an estimated payback of 4.2 years and an LCOE of €0.11/kWh.
[94]	2018	University campus of Sichuan (China)	PV	156	Installed	Between 33% and 46% of the electricity demand is covered thanks to the photovoltaic systems in place.
[52]	2020	Polytechnic University of Madrid (Spain)	PV	3300	Simulated	Coverage of 40% of total consumption, with a payback period of 11 years and a 13% to 30% reduction in campus emissions in 2026.
[93]	2020	University of Ciputra (Indonesia)	PV	Only the area and type of module is provided.	Simulated	PV could replace between 6% and 22% of the maximum energy demand required.
[83]	2021	University Campus of Bangladesh	PV	10.65	Calculated	There is a decrease in the energy price from 3.8 DBT/kWh to 2.52 BDT/kWh, which is 33.7% lower. This system has 140 storage batteries, and its total cost makes the proposal viable.
[98]	2022	Public buildings in Japan	PV	42	Installed	After its implementation in 2010, an 80% reduction was observed in 2013. Considering the solar energy generated, which was 55,540 kWh, this reached a value of −32 MJ/m2, achieving ZEB status.
			Hydrogen production	Surplus PV generation	Planned	Annual hydrogen production is expected to be 10,378.9 kWh, which could reduce standby power consumption by 51%.
[53]	2024	PHC Facility (Nigeria)	PV	10	Simulated	The price of energy is reduced from 2.31 €/kWh to 0.58 €/kWh, thanks to the photovoltaic system and its accumulators.

Table 4. List of references focused on the implementation of renewable energy installations in public buildings.

Ref.	Year	Institution Name	Renewable Installation	Total Capacity (kWp)	Status	Improvements Obtained
[69]	2004	University of Valencia (Spain)	PV	14.4/4.7	Simulated	Prepares two simulations with the indicated powers and with inclinations of 30º. 35º and 40º, deciding on the 4.7 kWp installation as it has the shortest recovery period.
[99]	2007	University of Jaén (Spain)	PV	200	Installed	The average annual production for the years 2000 to 2003 is 6.40% of campus consumption.
[96]	2011	University of Southampton (UK)	PV	1204	Simulated	The system can only cope with 4% of the consumption due to irradiance levels. Payback period is 5.6 years excluding land costs.
			HP	12	Simulated	Provides at least 80% of the heat demanded by the campus. It is a viable alternative.
[85]	2011	University of Jaén (Spain)	PV	761	Simulated	Simulation of a power of 761 spread over two areas. It will generate 25% of demand, will have a payback period of 16 years and the LCOE price is estimated at 0.13 €/kWh.
[100]	2011	Queensland University (Australia)	PV	1200	Installed	-
[97]	2013	West Texas University	PV	42	Simulated	Estimated at 71,000 kWh/year, saving $6390 per year and reducing carbon dioxide emissions by 49.7 tons.
			Wind turbine	50	Simulated	Estimated at 184,500 kWh/year, with annual savings of $11,945 with the wind characteristics of the area.
[101]	2015	University of Murcia (Spain)	PV	2750	Installed	-
[73]	2016	4 Public buildings in Italy	PV	210	Simulated	The energy efficiency level of each building is improved, reducing the energy consumed per square meter.
			CHP	-	Proposal	This system can produce 30% of the electricity and 55% of the thermal energy needed, with losses of 15%. It is the most expensive measure.
[95]	2016	University of New Haven (New England)	PV	67.27	Installed	Generation in 2015 was estimated at 82,800 kWh, although it was actually 85,244 kWh. The price of the installation was 4.29 $/W, which is lower than the state average.
[91]	2017	Technical University of Crete (Greece)	PV	2000	Simulated	The PV installation will supply 47% of the campus’s annual electricity consumption, with an estimated payback of 4.2 years and an LCOE of €0.11/kWh.
[94]	2018	University campus of Sichuan (China)	PV	156	Installed	Between 33% and 46% of the electricity demand is covered thanks to the photovoltaic systems in place.
[52]	2020	Polytechnic University of Madrid (Spain)	PV	3300	Simulated	Coverage of 40% of total consumption, with a payback period of 11 years and a 13% to 30% reduction in campus emissions in 2026.
[93]	2020	University of Ciputra (Indonesia)	PV	Only the area and type of module is provided.	Simulated	PV could replace between 6% and 22% of the maximum energy demand required.
[83]	2021	University Campus of Bangladesh	PV	10.65	Calculated	There is a decrease in the energy price from 3.8 DBT/kWh to 2.52 BDT/kWh, which is 33.7% lower. This system has 140 storage batteries, and its total cost makes the proposal viable.
[98]	2022	Public buildings in Japan	PV	42	Installed	After its implementation in 2010, an 80% reduction was observed in 2013. Considering the solar energy generated, which was 55,540 kWh, this reached a value of −32 MJ/m2, achieving ZEB status.
			Hydrogen production	Surplus PV generation	Planned	Annual hydrogen production is expected to be 10,378.9 kWh, which could reduce standby power consumption by 51%.
[53]	2024	PHC Facility (Nigeria)	PV	10	Simulated	The price of energy is reduced from 2.31 €/kWh to 0.58 €/kWh, thanks to the photovoltaic system and its accumulators.

In Figure 6, a series of characteristics identified across the studies reviewed are presented, including the installed peak capacity of each photovoltaic plant, the reduction in consumption from the external electrical grid, and the payback period of the respective plants. In this box plot, it can be observed that the total capacity between the 25th and 75th percentiles of the installations, representing the normal range, spans from very small values of up to 1250 kWp, with typical values reaching up to 2750 kWp. However, a red cross indicates an outlier exceeding 3300 kWp. Regarding the percentage reduction in electricity consumption due to photovoltaic installations, the normal range is between 15% and 42% of total energy consumption, with the average being close to 30%. In this case, outliers are also present, such as a 100% reduction observed in a study of a photovoltaic plant with energy storage systems. Finally, Figure 6 also shows the payback periods of the installations. It can be observed that the normal range is between 5 and 11 years, with an average of 9 years, and values reaching up to 17 years.

3. Discussion

This work reviews a broad group of studies related to electric energy consumption in public buildings or institutions, with a focus on three main areas: analyzing their energy use, implementing energy-saving measures, and installing renewable energy systems to reduce demand from the external grid. The methodology used and results obtained are examined in depth. Subsequently, the implications and interpretation of these findings are discussed within the field, including practical implications, identified limitations, and a comparison of methodologies.

Throughout the review, it was observed that energy consumption monitoring aims to examine the level of consumption over a specific time scale and, in some cases, its sources. Therefore, data monitoring proves to be a necessity across studies in this area. For large public institutions such as universities, advancing energy efficiency requires addressing three key levels [102]: creating specific policies, addressing individual buildings according to specific needs, and developing initiatives at the departmental level. One common approach found in several studies is the classification of buildings by type [48,62,66], which allows similarities to be identified among buildings of the same type. Monitoring consumption is crucial for implementing energy-saving measures, as these depend on the specific adjustments required [18].

In the set of studies on consumption monitoring and analysis, various limitations were identified, predominantly centered on the data monitoring process itself. Several studies rely on data from electronic sources and surveys [22,34,43,48], leading to non-real consumption data, often represented as monthly or annual accumulated values, lacking details on daily behavior or consumption patterns. Other studies include real measurement systems, but still rely on monthly or annual accumulated data [44,51,52], limiting insights into consumption patterns. This issue is also observed in cases where consumption data is derived from monthly invoices [50,56]. In contrast, studies with real-time monitoring on shorter timescales, such as hourly data, have the potential to establish consumption patterns that enable more accurate analysis. Another limitation is the relatively short timespan for data collection, as most studies cover less than three years of data. Currently, low-cost and efficient methods based on Internet of Things protocols and the use of contactless sensors are being developed, complemented by time series data logging. This approach eliminates the difficulty of obtaining complete real measurement data without the high cost and the limitation of the number of meters [28].

As illustrated, a thorough analysis and understanding of a building’s electric consumption enable more effective the implementation or proposal of energy-saving measures that aim to reduce demand. This importance is evident in studies on buildings implementing or proposing energy efficiency measures, where several studies show real data monitoring, although some continue to face the earlier-mentioned deficiency of non-real data from surveys and electronic sources [46] or monthly billing data [56], which can hinder the effectiveness of efficiency proposals. Additionally, within the set of studies reviewed, it was observed that building consumption can be simulated using specialized software [72], a useful approach when actual consumption data are unavailable or only monthly accumulated consumption data are available, and daily patterns are sought. Another limitation found is that the majority of studies fail to examine actual electric energy consumption once the measures are effectively implemented, relying instead on estimates based on the nominal power of various installed systems, such as lighting, air conditioning, or office equipment, as shown in Table 2. Another limitation identified in several of the studies reviewed is that they calculate energy savings from switching to LED lighting based on an average daily number of hours throughout the year [26]. This approach presents certain drawbacks, as both interior and exterior lighting schedules vary across the months due to changes in solar altitude, which in turn affects the availability of natural daylight [103].

A renewable energy generation facility fundamentally serves as an energy-saving measure aimed at eliminating the demand for electricity, as evidenced in Section 2.2. The evidence from the studies reviewed clearly shows, that large public buildings, due to their structural characteristics, such as expansive roofs and facades, predominantly employ solar PV systems as seen in Table 4. While several studies present buildings with existing renewable installations, many others focus on feasibility studies, employing simulations to assess the technical and economic viability of implementation. In contrast, systems such as CHP, HP, and hydrogen production are considerably less prevalent than solar PV systems [73,96,98].

With regard to limitations, several studies report metrics such as demand coverage, payback periods, and renewable generated energy. However, a valuable complement to this research would be the acquisition of average daily energy generation and building demand patterns. Such data could enhance the application of measures that optimize the daily peak in photovoltaic or other renewable energy generation. For instance, adjusting public building operational hours to midday, when solar radiation is at its highest, could increase energy utilization, given that these installations often operate off-grid. Furthermore, an in-depth analysis of generation data from either simulations or existing installations, combined with consumption data, could yield additional technical insights. These insights might include correlations between renewable generation behavior and building demand patterns, potentially demonstrating the extent to which renewable generation aligns with or supports the building’s consumption behavior.

Several limitations were identified in the references within the scope of the collected works. Firstly, a limited number of recent references from the past three years were found, with the majority of sources spanning from 2011 to 2021. Regarding the type of public building, this presented a particularly challenging task, as public entities typically do not provide energy consumption or electricity billing data, making this aspect difficult to address. Concerning the building types, studies on educational institutions, offices, and studies encompassing various building types were more numerous, while research focused on hospitals and other types of buildings was comparatively scarce.

4. Conclusions

In summary, this review highlights the trends, limitations, and opportunities related to electricity consumption in public buildings, as well as energy efficiency strategies aimed at reducing demand. It provides a comprehensive perspective on how proper monitoring and understanding of a building’s consumption can guide the implementation of energy-saving measures. The review of the studies served to identify various trends and significant gaps, underlining the need to improve both the monitoring of consumption data and the tracking of the impact of implemented energy-saving measures. This highlights important challenges for future research and advancements in practice.

It was observed that monitoring electricity consumption data and demand-side management strategies enables the identification of different consumption patterns and the source of these data, achieving savings of more than 15%. It was demonstrated that consumption depends on the number of loads and the type of building, with average consumption in offices being from 50 kWh/m² to 200 kWh/m² depending on the activities, and with greater differences in hospitals and university campuses depending on the different activities carried out. In universities, average consumption values of 170 kWh/m² and upwards are obtained, although this value also depends on the different activities carried out and the types of buildings owned. It has been shown that teaching buildings have the lowest consumption, with much higher consumption in research buildings due to the systems used, which are typically very energy intensive.

Another key aspect in the studies identified is the percentage of consumption by type of load, be it lighting, office equipment or air-conditioning equipment. In public buildings, it was found that lighting accounts for up to 35% of total electricity consumption, although in most studies these values are lower. In offices, office equipment typically accounts for approximately 17%. On the other hand, most studies show that the highest consumption in public buildings comes from air-conditioning systems, accounting for between 35% and 50% in some cases, as these devices have high installed power. Hence, it is necessary to continue studying new methods and new energy efficiency measures in order to reduce these large rates of consumption. The knowledge derived from these conclusions, through data monitoring, leads to the proposal and implementation of various energy efficiency strategies aimed at achieving substantial energy savings in public buildings, impacting not only the lowering of operational costs but also the reduction of the institutional carbon footprint. It was observed that applying energy efficiency measures plays a key role in the consumption of electrical energy, as they are able to reduce a large part of such expenditure. In the works collected in this research, it was found that the measures are based on five fields of application, including lighting, air-conditioning systems, building elements, consumption monitoring, and office equipment. More work has been done on energy efficiency measures in the areas of lighting, air conditioning, and building components. In the area of lighting, the most common measure is to replace luminaires with more efficient ones, in this case LED technology. In the area of air conditioning, systems are predominantly replaced with more efficient ones, while in the area of building elements, the predominant action is to replace doors and windows with others with better insulating qualities and to add insulating envelopes to the buildings. In terms of the percentage reduction in electricity consumption, measures in the area of air-conditioning systems achieve the highest percentage reduction, averaging 40%. Below this value, lighting measures have an average reduction of around 20%, and finally, building measures and monitoring have average reduction values of around 14%. The success of these initiatives relies on adapting technological solutions to the specific characteristics of each building, as well as fostering an energy awareness culture among users and administrators, which will allow long-term benefits to be maximized. In addition to incorporating innovative technologies, it is essential to promote a comprehensive approach that considers both system optimization and occupant behavior, aligning with global sustainability goals.

The majority of renewable energy installations in the public buildings studied were found to be are solar PV systems, due to the availability of roofs and walls without interfering with daily activities within the buildings. It was also observed that buildings implementing two different renewable energy systems always include a PV system, confirming this as the preferred choice. The implementation of these systems as an energy-saving measure results in reduced energy costs, with savings of up to 40% and coverage of electricity consumption of up to 50%, depending on the type of installation and the solar characteristics of the area. Additionally, other renewable energy installations, such as HP systems, can provide up to 80% of the required thermal energy.

This review represents a crucial contribution to the scientific field, providing a thorough and integrated understanding of the topic through the study of research with diverse methodologies and varied results. By combining these approaches from different perspectives, the analysis not only bolsters existing knowledge but also significantly enhances the understanding of the field. This review, by creating a comparative framework that facilitates the identification of patterns, limitations, and areas for improvement, offers a solid foundation that helps provide a clearer view of strategies and findings in the field, emphasizing the importance of understanding electricity consumption, energy efficiency measures, and community awareness.

After reviewing the existing research, a new avenue emerges in the study of various methods to reduce electricity consumption and billing. This includes exploring innovative renewable energy solutions within public buildings, such as combined heat and power plants or even small-scale hydroelectric systems. Furthermore, a promising area for future research lies in the development of energy communities, specifically examining the potential benefits of future energy procurement strategies in reducing electricity costs for public buildings. This evolving field offers significant opportunities for enhancing energy efficiency and sustainability in the public sector.