Smart Energy Systems

Topic Information

Dear Colleagues,

There are some definitions for what a Smart Energy System is. Words such as: cost-effective, sustainable, secure, renewable energy production, storage systems, demand side response, electrical vehicles, energy efficiency, active users, and intelligent networking are often associated with the Smart Energy System concept. It is a broader term than Smart Grid, in the sense that it includes more sectors (electricity, heating, cooling, industry, buildings, transportation, water) rather than focusing exclusively on the electricity sector. Smart Energy Systems are closely related to the ongoing energy transition towards a 100% renewable energy system. We are pleased to invite the research community to submit review or regular research papers on, but not limited to, the following relevant topics related to Smart Energy Systems:

• Hydrogen systems;
• Storage technologies and systems;
• Demand side response;
• Electrical Vehicles;
• Planning, operation, control, and management;
• Modeling, simulation, and data management;
• Power electronic converters and drives;
• Smart thermal grids;
• Smart gas grids;
• Smart electricity grids;
• Energy efficient systems;
• Virtual power plants;
• Renewable energy production and integration;
• Micro-Grids;
• Off-grid hybrid renewable systems;
• Artificial intelligence and optimization;
• Demand, Production and weather forecast;
• Smart homes, cities, and communities;
• Efficient buildings and Net Zero Energy Buildings;
• Power quality;
• Protection systems and reliability;
• Sensors, communications, and intelligent networking;
• Smart metering;
• Security and privacy of data exchange;
• Life cycle assessment;
• Public policies;
• Local markets;
• Flexibility markets;
• Education.

Prof. Dr. Rui Castro
Prof. Dr. Hugo Morais
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Batteries batteries	4.6	4.0	2015	19.7 Days	CHF 2700
Buildings buildings	3.1	3.4	2011	15.3 Days	CHF 2600
Electricity electricity	-	4.8	2020	27.9 Days	CHF 1000
Electronics electronics	2.6	5.3	2012	16.4 Days	CHF 2400
Energies energies	3.0	6.2	2008	16.8 Days	CHF 2600

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Published Papers (15 papers)

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16 pages, 557 KiB  

Open AccessArticle

Risk-Averse Stochastic Programming for Planning Hybrid Electrical Energy Systems: A Brazilian Case

by Daniel Kitamura, Leonardo Willer, Bruno Dias and Tiago Soares

Energies 2023, 16(3), 1463; https://doi.org/10.3390/en16031463 - 2 Feb 2023

Cited by 2 | Viewed by 1865

Abstract

This work presents a risk-averse stochastic programming model for the optimal planning of hybrid electrical energy systems (HEES), considering the regulatory policy applied to distribution systems in Brazil. Uncertainties associated with variables related to photovoltaic (PV) generation, load demand, fuel price for diesel [...] Read more.

This work presents a risk-averse stochastic programming model for the optimal planning of hybrid electrical energy systems (HEES), considering the regulatory policy applied to distribution systems in Brazil. Uncertainties associated with variables related to photovoltaic (PV) generation, load demand, fuel price for diesel generation and electricity tariff are considered, through the definition of scenarios. The conditional value-at-risk (CVaR) metric is used in the optimization problem to consider the consumer’s risk propensity. The model determines the number and type of PV panels, diesel generation, and battery storage capacities, in which the objective is to minimize investment and operating costs over the planning horizon. Case studies involving a large commercial consumer are carried out to evaluate the proposed model. Results showed that under normal conditions only the PV system is viable. The PV/diesel system tends to be viable in adverse hydrological conditions for risk-averse consumers. Under this condition, the PV/battery system is viable for a reduction of 87% in the battery investment cost. An important conclusion is that the risk analysis tool is essential to assist consumers in the decision-making process of investing in HEES. Full article

(This article belongs to the Topic Smart Energy Systems)

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23 pages, 5429 KiB  

Open AccessFeature PaperArticle

Live Field Validation of an Islanded Microgrid Based on Renewables and Electric Vehicles

by Daniel Heredero-Peris, Cristian Chillón-Antón, Francesc Girbau-Llistuella, Paula González-Fontderubinat, Oriol Gomis-Bellmunt, Marc Pagès-Giménez, Antoni Sudrià-Andreu, Samuel Galceran-Arellano and Daniel Montesinos-Miracle

Electricity 2023, 4(1), 22-44; https://doi.org/10.3390/electricity4010002 - 12 Jan 2023

Viewed by 2628

Abstract

This paper presents a live field experience of creating an isolated microgrid for the Expoelectric fair during 2018 and 2019. The islanded microgrid comprises a Master Inverter with grid-forming capabilities and fault management. The Master Inverter and stationary batteries, and EVs with V2G [...] Read more.

This paper presents a live field experience of creating an isolated microgrid for the Expoelectric fair during 2018 and 2019. The islanded microgrid comprises a Master Inverter with grid-forming capabilities and fault management. The Master Inverter and stationary batteries, and EVs with V2G capabilities provide storage. A PV generation system supplies the microgrid. The loads are the fair booths, mainly lighting and chargers for personal mobility vehicles. All the equipment used in the experimental microgrid is from different manufacturers. The operation and control of the islanded microgrid are based on the VDE-AR-N-4105 standard. The paper also presents the operation of the Master Inverter during faults. The live field experience shows that the proposed operation method is valid for operating different converters from different manufacturers without needing any communication layer between them. The experimental results also show that faults can be handled correctly by the Master Inverter to operate the entire microgrid safely. In conclusion, islanded microgrids based on power electronics are feasible to replace diesel generators in faires, conventions or temporary events. Full article

(This article belongs to the Topic Smart Energy Systems)

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14 pages, 402 KiB  

Open AccessArticle

Benchmark of Electricity Consumption Forecasting Methodologies Applied to Industrial Kitchens

by Jorge Amantegui, Hugo Morais and Lucas Pereira

Buildings 2022, 12(12), 2231; https://doi.org/10.3390/buildings12122231 - 15 Dec 2022

Cited by 6 | Viewed by 2772

Abstract

Even though Industrial Kitchens (IKs) are among the highest energy intensity spaces, very little work has been done to forecast their consumption. This work explores the possibility of increasing the accuracy of the consumption forecast in an IK by forecasting disaggregated appliance consumption [...] Read more.

Even though Industrial Kitchens (IKs) are among the highest energy intensity spaces, very little work has been done to forecast their consumption. This work explores the possibility of increasing the accuracy of the consumption forecast in an IK by forecasting disaggregated appliance consumption and comparing these results with the forecast of the total consumption of these appliances (Virtual Aggregate—VA). To do so, three different methods are used: the statistical method (Prophet), classic Machine Learning (ML) method such as random forest (RF), and deep learning (DL) method, namely long short-term memory (LSTM). This work uses individual appliance electricity consumption data collected from a Portuguese restaurant over a period of four consecutive weeks. The obtained results suggest that Prophet and RF are the more viable options. The former achieved the best performance in aggregated data, whereas the latter showed better forecasting results for most of the individual loads. Regarding the performance of the VA against the sum of individual appliance forecasts, all models perform better in the former. However, the very small difference across the results shows that this is a viable alternative to forecast aggregated consumption when only individual appliance consumption data are available. Full article

(This article belongs to the Topic Smart Energy Systems)

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10 pages, 895 KiB  

Open AccessArticle

Analysis of the Productivity Dynamics of Electricity Distribution Regions in Ghana

by Clement Tengey, Nnamdi Ikechi Nwulu, Omoseni Adepoju and Omowunmi Mary Longe

Energies 2022, 15(24), 9414; https://doi.org/10.3390/en15249414 - 12 Dec 2022

Cited by 5 | Viewed by 2077

Abstract

Electrical power distribution is the most important division in the power supply chain. However, its sustainability in terms of efficiency is very important for the growth of every country. This main objective of the paper is to assess the productivity dynamics of this [...] Read more.

Electrical power distribution is the most important division in the power supply chain. However, its sustainability in terms of efficiency is very important for the growth of every country. This main objective of the paper is to assess the productivity dynamics of this process using the data envelopment analysis (DEA) methodology to analyse the effectiveness of the electricity distribution regions (EDRs) over a period of 7 years. The paper adapts the biennial Malmquist productivity index by infusing it with the slacks-based measure (SBM) to assess the productivity dynamics of EDRs in Ghana. Productivity dynamics were assessed by decomposing the SBM-BMPI productivity scores into the efficiency, technology, and scale change. It was discovered that the productivity of EDRs in Ghana progressed by 16.23% per annum over the sample period. Productivity was driven mainly by technological change and not the efficiency changes and scale changes. Full article

(This article belongs to the Topic Smart Energy Systems)

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13 pages, 1290 KiB  

Open AccessArticle

Research on the Optimal Economic Power Dispatching of a Multi-Microgrid Cooperative Operation

by Haipeng Wang, Xuewei Wu, Kai Sun and Yuling He

Energies 2022, 15(21), 8194; https://doi.org/10.3390/en15218194 - 3 Nov 2022

Cited by 14 | Viewed by 1880

Abstract

The economic power-dispatching model of a multi-microgrid is comprehensively established in this paper, considering many factors, such as generation cost, discharge cost, power-purchase cost, power sales revenue, and environmental cost. To construct this model, power interactions between the two microgrids and those between [...] Read more.

The economic power-dispatching model of a multi-microgrid is comprehensively established in this paper, considering many factors, such as generation cost, discharge cost, power-purchase cost, power sales revenue, and environmental cost. To construct this model, power interactions between the two microgrids and those between the micro- and main grids are considered. Furthermore, the particle swarm optimization (PSO) algorithm is utilized to solve the economic power-dispatching model. To validate the effectiveness of the proposed model as well as the solution algorithm, a practical project case is studied and discussed. In the case study, the impact of multiple scenarios is first analyzed. Then, the system operation economic costs under different scenarios are described in detail. Moreover, according to the optimization power-dispatching results of the multi-microgrid, power interactions between the two microgrids and those between the micro- and main grids are fully discussed. Full article

(This article belongs to the Topic Smart Energy Systems)

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20 pages, 93318 KiB  

Open AccessArticle

Non-Linear Clustering of Distribution Feeders

by Octavio Ramos-Leaños, Jneid Jneid and Bruno Fazio

Energies 2022, 15(21), 7883; https://doi.org/10.3390/en15217883 - 24 Oct 2022

Cited by 3 | Viewed by 1505

Abstract

Distribution network planners are facing a strong shift in the way they plan and analyze the network. With their intermittent nature, the introduction of distributed energy resources (DER) calls for yearly or at least seasonal analysis, which is in contrast to the current [...] Read more.

Distribution network planners are facing a strong shift in the way they plan and analyze the network. With their intermittent nature, the introduction of distributed energy resources (DER) calls for yearly or at least seasonal analysis, which is in contrast to the current practice of analyzing only the highest demand point of the year. It requires not only a large number of simulations but long-term simulations as well. These simulations require significant computational and human resources that not all utilities have available. This article proposes a nonlinear clustering methodology to find a handful of representative medium voltage (MV) distribution feeders for DER penetration studies. It is shown that the proposed methodology is capable of uncovering nonlinear relations between features, resulting in more consistent clusters. Obtained results are compared to the most common linear clustering algorithms. Full article

(This article belongs to the Topic Smart Energy Systems)

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21 pages, 13207 KiB  

Open AccessArticle

Directed Representative Graph Modeling of MEP Systems Using BIM Data

by Junjun Han, Xiaoping Zhou, Weisong Zhang, Qiang Guo, Jia Wang and Yixin Lu

Buildings 2022, 12(6), 834; https://doi.org/10.3390/buildings12060834 - 15 Jun 2022

Cited by 9 | Viewed by 3600

Abstract

Mechanical, electrical, and plumbing (MEP) systems are crucial to a building, which directly affect the building safety, energy saving, and operational efficiency. Building information models (BIMs) help engineers to view the connection structure of MEP elements, reducing the time for reading drawings and [...] Read more.

Mechanical, electrical, and plumbing (MEP) systems are crucial to a building, which directly affect the building safety, energy saving, and operational efficiency. Building information models (BIMs) help engineers to view the connection structure of MEP elements, reducing the time for reading drawings and training costs. However, existing MEP systems bring a tremendous challenge to monitoring due to issues with the complicated spatial structure, large scale, and intuitiveness. In addition, there is still a lack of feasible methods to model a representative graph in MEP systems. To address this problem, this study proposes an approach to model a directed representative graph of MEP systems using BIM data. The proposed approach contains two parts, the representative edge extraction and the direction identification. Firstly, MEP elements are converted into triangular meshes on which boundary points are extracted. Secondly, representative sets are developed to extract the representative points. Thirdly, representative points are connected to generate representative edges. Meanwhile, there are topological connection relationships among MEP elements and the flow directions of MEP ports, all of which are extracted to obtain the graph direction based on Industry Foundation Classes (IFC). Subsequently, representative edges and directions are combined to obtain the directed representative graph. Finally, experiments of directed representative graph extraction are evaluated on six BIM models. The experimental results show that directed representative graphs are extracted successfully. Furthermore, a simulated system is developed to integrate the directed representative graph and the Internet of Things (IoT) to realize the intelligent monitoring of MEP systems. The proposed directed representative graph model lays a solid foundation for the development of MEP systems monitoring management in smart buildings. Full article

(This article belongs to the Topic Smart Energy Systems)

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12 pages, 859 KiB  

Open AccessCase Report

Reducing Energy Consumption in the Workplace via IoT-Allowed Behavioural Change Interventions

by Alfonso P. Ramallo-González, Cleopatra Bardaki, Dimosthenis Kotsopoulos, Valentina Tomat, Aurora González Vidal, Pedro J. Fernandez Ruiz and Antonio Skarmeta Gómez

Buildings 2022, 12(6), 708; https://doi.org/10.3390/buildings12060708 - 24 May 2022

Cited by 20 | Viewed by 3016

Abstract

The arrival of the Internet of Things (IoT) paradigm has opened the door to a variety of services for building users. Considering the long-lasting issue of high energy use by buildings and low-energy literacy, it is tempting to use this new technology for [...] Read more.

The arrival of the Internet of Things (IoT) paradigm has opened the door to a variety of services for building users. Considering the long-lasting issue of high energy use by buildings and low-energy literacy, it is tempting to use this new technology for increasing the literacy of users. This paper shows the results of a study performed in two pilot buildings with real users that have interacted with a series of energy educational interventions that encourage them in a timed and personalised way to reduce their energy consumption. The interventions aimed at reducing the consumption of energy and a close follow-up of the intervention from a behavioural aspect has been performed. The results show that the users, when interacting with the intervention and staying active, can reduce the energy consumption in the building by more than 30%, but the average savings are of 20%. This is in consensus with the literature, but in our case, the intervention has been one showing that personalised methods can result in energy reductions as large as those of more standard interventions. Full article

(This article belongs to the Topic Smart Energy Systems)

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23 pages, 5264 KiB  

Open AccessArticle

Load Frequency Control (LFC) Strategies in Renewable Energy-Based Hybrid Power Systems: A Review

by Muhammad Majid Gulzar, Muhammad Iqbal, Sulman Shahzad, Hafiz Abdul Muqeet, Muhammad Shahzad and Muhammad Majid Hussain

Energies 2022, 15(10), 3488; https://doi.org/10.3390/en15103488 - 10 May 2022

Cited by 95 | Viewed by 8243

Abstract

The hybrid power system is a combination of renewable energy power plants and conventional energy power plants. This integration causes power quality issues including poor settling times and higher transient contents. The main issue of such interconnection is the frequency variations caused in [...] Read more.

The hybrid power system is a combination of renewable energy power plants and conventional energy power plants. This integration causes power quality issues including poor settling times and higher transient contents. The main issue of such interconnection is the frequency variations caused in the hybrid power system. Load Frequency Controller (LFC) design ensures the reliable and efficient operation of the power system. The main function of LFC is to maintain the system frequency within safe limits, hence keeping power at a specific range. An LFC should be supported with modern and intelligent control structures for providing the adequate power to the system. This paper presents a comprehensive review of several LFC structures in a diverse configuration of a power system. First of all, an overview of a renewable energy-based power system is provided with a need for the development of LFC. The basic operation was studied in single-area, multi-area and multi-stage power system configurations. Types of controllers developed on different techniques studied with an overview of different control techniques were utilized. The comparative analysis of various controllers and strategies was performed graphically. The future scope of work provided lists the potential areas for conducting further research. Finally, the paper concludes by emphasizing the need for better LFC design in complex power system environments. Full article

(This article belongs to the Topic Smart Energy Systems)

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23 pages, 890 KiB  

Open AccessFeature PaperArticle

IoT Middleware Platforms for Smart Energy Systems: An Empirical Expert Survey

by Qamar Alfalouji, Thomas Schranz, Alexander Kümpel, Markus Schraven, Thomas Storek, Stephan Gross, Antonello Monti, Dirk Müller and Gerald Schweiger

Buildings 2022, 12(5), 526; https://doi.org/10.3390/buildings12050526 - 21 Apr 2022

Cited by 21 | Viewed by 5501

Abstract

Middleware platforms are key technology in any Internet of Things (IoT) system, considering their role in managing the intermediary communications between devices and applications. In the energy sector, it has been shown that IoT devices enable the integration of all network assets to [...] Read more.

Middleware platforms are key technology in any Internet of Things (IoT) system, considering their role in managing the intermediary communications between devices and applications. In the energy sector, it has been shown that IoT devices enable the integration of all network assets to one large distributed system. This comes with significant benefits, such as improving energy efficiency, boosting the generation of renewable energy, reducing maintenance costs and increasing comfort. Various existing IoT middlware solutions encounter several problems that limit their performance, such as vendor locks. Hence, this paper presents a literature review and an expert survey on IoT middleware platforms in energy systems, in order to provide a set of tools and functionalities to be supported by any future efficient, flexible and interoperable IoT middleware considering the market needs. The analysis of the results shows that experts currently use the IoT middleware mainly to deploy services such as visualization, monitoring and benchmarking of energy consumption, and energy optimization is considered as a future application to target. Likewise, non-functional requirements, such as security and privacy, play vital roles in the IoT platforms’ performances. Full article

(This article belongs to the Topic Smart Energy Systems)

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14 pages, 5369 KiB  

Open AccessArticle

Monitoring Approaches for New-Generation Energy Performance Certificates in Residential Buildings

by Graziano Salvalai and Marta Maria Sesana

Buildings 2022, 12(4), 469; https://doi.org/10.3390/buildings12040469 - 11 Apr 2022

Cited by 5 | Viewed by 3224

Abstract

In 2002, the Energy Performance of Building Directive (EPBD) introduced energy certification schemes to classify and compare building performances to support reaching energy efficiency targets by informing the different actors of the building sectors. However, since its implementation, the Energy Performance Certifications (EPCs) [...] Read more.

In 2002, the Energy Performance of Building Directive (EPBD) introduced energy certification schemes to classify and compare building performances to support reaching energy efficiency targets by informing the different actors of the building sectors. However, since its implementation, the Energy Performance Certifications (EPCs) remained unexploited with limited impact on the energy savings targets. In this context, the EPC RECAST project aims at studying a new generation of EPCs with a focus on the residential sector. More in detail, the paper presents and frames a monitoring approach based on low-cost and non-invasive technology for real data collection in existing residential apartments/houses. The method is based on different levels of monitoring selected according to the typology of the building (e.g., detached house, apartment), services (e.g., centralized or local energy generation), and energy vectors (e.g., natural gas or electricity). Three different levels have been identified (named as: basic, medium, and advanced) and for each one, different plug and play monitoring sensor kits have been selected. Six representative pilot buildings have been identified and selected to verify the approach in general and, in particular, the sensors’ applicability and communication, the data reliability, and the monitoring platform. The presented work highlights, on the one hand, the general feasibility of the proposed monitoring approach; on the other, it highlights the difficulty of fully standardizing the sensors kits considering that each building/apartment has specific characteristics and constraints that have to be carefully analyzed. The use of the ultrasonic flow meters represents a good technical option for reducing the cost and the impact on the existing plant system; however, their installation must be verified considering that the logger needs to be powered and the sensors calibrated for collecting reliable data. Full article

(This article belongs to the Topic Smart Energy Systems)

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17 pages, 2737 KiB  

Open AccessArticle

Optimal Control Strategies for Demand Response in Buildings under Penetration of Renewable Energy

by Yongbao Chen, Zhe Chen, Xiaolei Yuan, Lin Su and Kang Li

Buildings 2022, 12(3), 371; https://doi.org/10.3390/buildings12030371 - 17 Mar 2022

Cited by 20 | Viewed by 4098

Abstract

The penetration rates of intermittent renewable energies such as wind and solar energy have been increasing in power grids, often leading to a massive peak-to-valley difference in the net load demand, known as a “duck curve”. The power demand and supply should remain [...] Read more.

The penetration rates of intermittent renewable energies such as wind and solar energy have been increasing in power grids, often leading to a massive peak-to-valley difference in the net load demand, known as a “duck curve”. The power demand and supply should remain balanced in real-time, however, traditional power plants generally cannot output a large range of variable loads to balance the demand and supply, resulting in the overgeneration of solar and wind energy in the grid. Meanwhile, the power generation hours of the plant are forced to be curtailed, leading to a decrease in energy efficiency. Building demand response (DR) is considered as a promising technology for the collaborative control of energy supply and demand. Conventionally, building control approaches usually consider the minimization of total energy consumption as the optimization objective function; relatively few control methods have considered the balance of energy supply and demand under high renewable energy penetration. Thus, this paper proposes an innovative DR control approach that considers the energy flexibility of buildings. First, based on an energy flexibility quantification framework, the energy flexibility capacity of a typical office building is quantified; second, according to energy flexibility and a predictive net load demand curve of the grid, two DR control strategies are designed: rule-based and prediction-based DR control strategies. These two proposed control strategies are validated based on scenarios of heating, ventilation, and air conditioning (HVAC) systems with and without an energy storage tank. The results show that 24–55% of the building’s total load can be shifted from the peak load time to the valley load time, and that the duration is over 2 h, owing to the utilization of energy flexibility and the implementation of the proposed DR controls. The findings of this work are beneficial for smoothing the net load demand curve of a grid and improving the ability of a grid to adopt renewable energies. Full article

(This article belongs to the Topic Smart Energy Systems)

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18 pages, 2977 KiB  

Open AccessArticle

On Increasing the Energy Efficiency of Wireless Rechargeable Sensor Networks for Cyber-Physical Systems

by Efe Francis Orumwense and Khaled Abo-Al-Ez

Energies 2022, 15(3), 1204; https://doi.org/10.3390/en15031204 - 7 Feb 2022

Cited by 10 | Viewed by 2342

Abstract

In recent times, wireless energy transfer has become an effective solution to charge devices due to its efficiency and reliability. In a typical Wireless Rechargeable Sensor Networks (WRSN), wireless energy transfer technique can solve the energy depletion problem with the aid of a [...] Read more.

In recent times, wireless energy transfer has become an effective solution to charge devices due to its efficiency and reliability. In a typical Wireless Rechargeable Sensor Networks (WRSN), wireless energy transfer technique can solve the energy depletion problem with the aid of a Wireless Charging Vehicle (WCV), thereby enabling the network to extend its lifetime. However, sensor nodes in a WRSN still have their energies depleted before it gets replenished by the WCV. In this paper, we proposed a scheme that prioritizes sensor nodes for charging and also developed efficient algorithms to improve on existing charging schemes so as to extend the lifetime of the WRSN. Firstly, an inspection algorithm was developed to visit and inspect sensor nodes in the network so as to determine the sensor nodes to charge. Secondly, a greedy charge algorithm was introduced to ascertain the shortest distance the WCV needs to travel and, lastly, an energy for nodes’ algorithm was proposed to determine the stopping point and when the WCV needs to return to the base station. Simulation experiments were also conducted to determine the performance of our scheme. The simulation experiments revealed that our proposed scheme made significant improvements when compared to other schemes in literature using several metrics. Full article

(This article belongs to the Topic Smart Energy Systems)

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12 pages, 4673 KiB  

Open AccessArticle

Wearable Shoe-Mounted Piezoelectric Energy Harvester for a Self-Powered Wireless Communication System

by Se Yeong Jeong, Liang Liang Xu, Chul Hee Ryu, Anuruddh Kumar, Seong Do Hong, Deok Hwan Jeon, Jae Yong Cho, Jung Hwan Ahn, Yun Hwan Joo, In Wha Jeong, Won Seop Hwang and Tae Hyun Sung

Energies 2022, 15(1), 237; https://doi.org/10.3390/en15010237 - 30 Dec 2021

Cited by 10 | Viewed by 7990

Abstract

This study covers a self-powered wireless communication system that is powered using a piezoelectric energy harvester (PEH) in a shoe. The lead-zirconate-titanate (PZT) ceramic of the PEH was coated with UV resin, which (after curing under UV light) allowed it to withstand periodic [...] Read more.

This study covers a self-powered wireless communication system that is powered using a piezoelectric energy harvester (PEH) in a shoe. The lead-zirconate-titanate (PZT) ceramic of the PEH was coated with UV resin, which (after curing under UV light) allowed it to withstand periodic pressure. The PEH was designed with a simple structure and placed under the sole of a shoe. The durability of the PEH was tested using a pushing tester and its applicability in shoes was examined. With periodic compression of 60 kg, the PEH produced 52 μW of energy at 280 kΩ. The energy generated by the PEH was used to power a wireless transmitter. A step-down converter with an under-voltage lockout function was used to gather enough energy to operate the wireless transmitter. The transmitter can be operated initially after walking 24 steps. After the transmitter has been activated, it can be operated again after 8 steps. Because a control center receives signals from the transmitter, it is possible to check the status of workers who work outside at night or mostly alone, to detect emergencies. Full article

(This article belongs to the Topic Smart Energy Systems)

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23 pages, 1551 KiB  

Open AccessArticle

Optimization of a Mobile Energy Storage Network

by Luiz Eduardo Cotta Monteiro, Hugo Miguel Varela Repolho, Rodrigo Flora Calili, Daniel Ramos Louzada, Rafael Saadi Dantas Teixeira and Rodrigo Santos Vieira

Energies 2022, 15(1), 186; https://doi.org/10.3390/en15010186 - 28 Dec 2021

Cited by 2 | Viewed by 2274

Abstract

This paper introduces the mobile battery network for electronic devices through powerbanks in a city, and proposes an optimization model to find the optimum site and set-up of the network considering costumers demand, logistics components, the batteries degradation, and terminal’s charger regime. To [...] Read more.

This paper introduces the mobile battery network for electronic devices through powerbanks in a city, and proposes an optimization model to find the optimum site and set-up of the network considering costumers demand, logistics components, the batteries degradation, and terminal’s charger regime. To this end, a series of degradation tests were carried out on lithium-ion batteries, in four different charger regimes, in which the battery voltage amplitude and the charging electric current were varied. The results of these tests were incorporated into the optimization model as the depreciation rate and charge time over battery life. The mathematical modeling innovates by including new components designed specifically for this new problem: battery availability according to charging time; different types of customer service; objective function modeling that includes the logistical costs of battery relocation, terminal maintenance, and battery depreciation. The results indicate that the network performance using batteries in the fastest charging configuration tends to have a positive impact on their efficiency and profitability. The model can be used as a reference for other applications that require recharge points that enable the use of mobile batteries, such as electric scooters, electric bicycles, and drones, among others. Full article

(This article belongs to the Topic Smart Energy Systems)

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