Energy-Saving Design Strategies for Industrial Heritage in Northeast China Under the Concept of Ultra-Low Energy Consumption

Abstract

Countries around the world have developed standards for ultra-low energy consumption building design and future plans. Unfortunately, these standards lack specific requirements for industrial heritage. As an important carrier of urban context, history, and the transmission of residents’ memories, industrial heritage cannot be overlooked in urban development. This study uses DesignBuilder energy simulation software to model industrial heritage (taking the Changchun Tractor Factory as an example) and compares the energy consumption before and after renovation strategies. The results show that in the Case 4 plan, after implementing the renovation strategy, heating energy consumption can be reduced by about 11,648 (kWh/m²) over the heating season, the total primary energy was reduced by about 4 million (kgce/tce), and total energy consumption decreases by approximately 95%. This demonstrates the effectiveness of the industrial heritage reuse design strategy proposed in this paper. It provides a new direction for reuse design under ultra-low energy consumption requirements in related case studies.

1. Introduction

The global building roadmap released by the International Energy Agency (IEA) aims to achieve zero emissions for new and existing buildings gradually from 2020 to 2050 [1]. Governments worldwide have prioritized the building sector’s focus on low carbon and ultra-low energy consumption. In March 2024, the Central Committee of the Communist Party of China and the State Council issued the Opinions on Accelerating the Comprehensive Green Transformation of Economic and Social Development, which stated that ultra-low-energy buildings in China are expected to achieve large-scale development by 2027. It emphasized that advancing green and low carbon development in urban and rural areas should begin with a strong focus on the development of ultra-low-energy buildings [2]. Globally, 39% of carbon emissions originate from the construction industry and buildings themselves. The issues of energy consumption and sustainability in buildings have become focal points for countries worldwide [3,4]. Various nations have established standards and regulations for energy-efficient, low-energy, and green buildings. Unfortunately, these standards lack specific considerations for industrial heritage [5].

The first project for the conservation and adaptive reuse of industrial heritage was the Ironbridge Gorge in the UK, repurposed in the 1960s [6]. In fact, the process of protecting industrial heritage evolved from architectural heritage. As such, like architectural heritage, it is essential to the development of a city, as it symbolizes and represents the historical period of the past [7]. However, extending the lifespan of industrial heritage and sustaining its historical and cultural value requires consideration of not only the impacts and limitations of traditional codes [5], the influences of sustainability requirements [8], and regional differences [7,9], but also energy consumption [10] and the balance between conservation and reuse [11]. Among these influencing factors, aligning with current global energy development requirements, the greatest and most pressing issue is achieving low energy consumption and ultra-low energy consumption.

However, a review of existing research literature reveals a significant lack of studies and practices related to low energy consumption and ultra-low energy consumption in the context of architectural heritage, particularly in the field of industrial heritage, which undoubtedly hinders the conservation and sustainable development of industrial heritage severely [12]. In addition, a disconnect exists between China’s industrial heritage reuse cases and the critical international and domestic strategic objectives, such as carbon peaking and sustainable development. It is a significant risk to the full lifecycle utilization of industrial heritage. The research on the energy consumption aspects of industrial heritage still has large gaps. On one hand, since most early industrial buildings were constructed to meet the needs of industrial production at minimal cost, their envelope structures were designed with the lowest standards for insulation and heating. Therefore, such buildings are inherently vulnerable in terms of energy-saving. On the other hand, industrial heritage is an important and continuous branch of the architectural field, which cannot be overlooked.

In addition, building simulation and computational technologies have been widely applied in architectural design for decades [13]. Building energy simulation tools have consistently assisted architects, designers, engineers, and researchers in identifying the most suitable and the most cost-effective energy-saving measures to reduce and optimize building energy consumption during the design, construction, and operation phases [14]. Currently, these software tools have become critical in the design phase of energy-efficient buildings [15]. Among them, DesignBuilder, as one of the most comprehensive energy simulation software tools, ranks among the top three in terms of usage frequency [16].

In summary, given the research gaps regarding industrial heritage under the concept of ultra-low energy consumption, the urgent need for renewal, and the alignment with sustainable development goals, this study proposes a novel reuse strategy based on the current status and needs of representative cases. DesignBuilder energy simulation software is utilized to conduct comparative studies of reused plans under different strategies. This research employs a combination of the Case Study Method, Simulation Analysis Method, and Comparative Analysis Method. By integrating theory and case studies, as well as qualitative analysis and quantitative simulations, this study develops instructive reuse strategies. Furthermore, the effectiveness and applicability of these strategies are demonstrated through scientific simulations and data validation methods. The main goals of this study are as follows:

• To investigate the current energy consumption status and energy-saving potential of industrial heritage buildings in Northeast China using DesignBuilder energy simulation software.
• To propose the “Two Enhancements and Two Reductions” design strategy, which balances ultra-low energy consumption design principles with the imperative to conserve and adaptively reuse industrial heritage structures.
• To verify the effectiveness of the “Two Enhancements and Two Reductions” strategy and demonstrate its potential for achieving ultra-low energy consumption in practice.

2. State of the Art

2.1. Ultra-Low-Energy Buildings

Ultra-low-energy buildings are a subset of green buildings, a concept that can be traced back to the energy crisis following World War II [17]. In 1969, Italian architect Paolo Soleri first introduced the concept of “arcology”, or ecological architecture [18]. In 1976, Torben V. Esbensen conducted theoretical and experimental research on using solar energy for building heating, proposing the concept of “zero-energy buildings” for the first time [19]. In 1990, the British Building Research Establishment introduced the world’s first green buildings assessment method, Building Research Establishment’s Environmental Assessment Method (BREEAM), marking a significant step toward the formalization of green buildings practice [20]. In 1991, German physicist Wolfgang Feist constructed the first “Passive House”, initiating extensive research into green buildings development worldwide [21]. In 2006, the UK proposed the concept of low-carbon buildings and introduced the goal of “zero-carbon homes”, propelling the advancement of low-carbon and zero-carbon buildings [22]. By 2010, Germany raised the energy-saving standards for buildings, combining low-energy building standards with passive house standards and introducing the concept of ultra-low-energy buildings. These architectural concepts originated from global energy crises, climate change, and the need for sustainable development. As a result, building standards in different countries have evolved into distinct systems and regulations worldwide [17,23,24]. In China, the development of green buildings began with energy-saving. Since the standard of its first design standard in 1986, the central and local governments have issued hundreds of building energy-saving codes, revising many standards regularly [25,26,27]. The evolution and derivation of these related concepts have been complex and lengthy, but they remain interconnected and share commonalities. The relationships between some of these concepts are illustrated in Figure 1.

2.2. Reuse of Industrial Heritage

As early as 1965, UNESCO proposed the establishment of the International Council on Monuments and Sites (ICOMOS) [28], initiating global attention to the conservation and adaptive reuse of architectural heritage. Currently, 168 countries are signatories to ICOMOS, with the ranking of countries by the number of World Heritage Sites shown in Figure 2 (Data from ICOMOS official website) [29]. Among them, Italy, China, Germany, France, and Spain occupy the top five positions. Notably, among these top five countries, all except China include industrial heritage within their World Heritage Sites. Examples include Italy’s Rhaetian Railway and the 20th-century industrial city of Ivrea; Germany’s Völklingen Ironworks; France’s Nord-Pas de Calais Mining Basin; and Spain’s Almaden mercury mining area. Additional examples include Belgium’s Major Mining Sites of Wallonia, Japan’s Tomioka Silk Mill, and the United Kingdom’s famous Ironbridge Gorge. This highlights the insufficient conservation and utilization of industrial heritage in China. However, this does not imply a severe lack of industrial heritage in China. On the contrary, China possesses a significant amount of industrial heritage.

China’s industrial development started relatively late. However, for a significant period after 1949, the country’s economy was primarily driven by heavy industry, light industry, and handicrafts [30]. With the continuous advancement of technology and urban development, the transformation of former industrial cities has become inevitable in the face of urban and architectural renewal. Within these cities, a large amount of industrial heritage has been preserved, serving as a new type of historical and cultural reserve resource for urban development, which is significant and cannot be overlooked [31,32,33].

The research on ecological architecture, ecological conservation, and architectural site preservation originated in the 1960s. Subsequently, studies on ecological architecture in various countries gradually diversified, giving rise to fields such as building carbon emissions and energy-saving technologies. Around the same time, research on industrial heritage began to emerge as an independent discipline from the broader category of architectural heritage, with architects and researchers extensively debating the issues of preservation versus renewal. However, it was not until the 1980s that energy-saving technologies were first applied to architectural heritage, while B. Jankovich et al. retrofitted passive and active solar energy systems and cooling systems suitable for architectural heritage [34]. From that point onward, the conservation and reuse of architectural and industrial heritage started to address energy consumption issues, as shown in Figure 3.

2.3. Selection of Energy Simulation Software

In the 1970s, the United States took the lead in developing energy simulation software, the BLAST and DOE-2. Subsequently, the United Kingdom developed BREDEM, China created DeST, and Japan produced HASP. By the end of the 20th century, many European countries had also developed their own building energy simulation software, as shown in Figure 4 [35]. Although there are more than 30 types of energy simulation software globally, after 50 years of updates and eliminations, a relatively mainstream selection has emerged. Choosing software suitable for the specific project has become an essential step in the research process. A comparison of these tools is shown in

Table 1. Comparison of major international building energy simulation softwares.

	TRNSYS	PHPP	EnergyPlus	eQUEST	DeST	DesignBuilder
Country	United States	Germany	United States	United States of America	China	United Kingdom
Development Company	University of Wisconsin	Passive House Institute	U.S. Department of Energy (DOE)	JB Engineering	Tsinghua University	DesignBuilder Software Ltd.
Development	1975	1996	1999	2000	2004	2006
Load Simulation Methods	Modular Thermodynamic Modeling	Heat Balance Method	Heat Balance and Fluid Dynamics	Simplified Models	Heat Balance Method	Heat Balance and Fluid Dynamics
Model Complexity	high	medium	high	low	medium	medium
System Restructuring	highly flexible	limited	flexible	limited	limited	flexible
Accurate Temperature Calculations	accurate	accurate	accurate	accurate	accurate	accurate
Applicable Structures	all types of complex systems	primarily for passive houses	all types of buildings	residential and small businesses	Chinese buildings	all types of buildings
Photovoltaic Module	support	partial support	support	partial support	partial support	support
Data Input Method	manual or script	manual	manual or batch input	simple import	manual	graphical input
Output of Results	reports and data output	reports	graphs and data tables	graphs and reports	reports	graphs and reports

.

Attia, Shady conducted a comparative analysis of mainstream building energy simulation tools in the early 21st century, evaluating them from five aspects: usability, intelligence, accuracy, process suitability, and interoperability. Among these, DesignBuilder demonstrated the best overall performance [35]. Sağdıçoğlu, M. S., using Vosviewer and Bibliometrix tools, performed bibliometric analyses on the usage of energy simulation software, revealing that DesignBuilder ranked first in terms of usage frequency [36]. Haidong Wang et al. found that DesignBuilder integrates environmental simulation with building energy modeling, constructing an integrated simulation program that significantly enhances the accuracy of predictions for thermal and flow behaviors [37]. Subsequently, more scholars began utilizing DesignBuilder to simulate and calculate various building components. Piero Bevilacqua et al. used DesignBuilder to evaluate the performance of new envelope materials [38]. M.M. Rahman et al. compared energy-saving under various HVAC systems and high COP chiller investment strategies using the software [39]. Yang Liu et al. explored the relationship between the window/wall ratio and energy consumption [40]. Meanwhile, A. Goenaga-Pérez et al. conducted simulations to verify whether Spain’s nZEB standards are applicable to the various regional climate conditions within the country [41]. Moreover, DesignBuilder has demonstrated extensive applicability in energy simulation and is widely employed in studies analyzing overall building energy performance [42,43,44]. Based on previous research, DesignBuilder simulation software is applicable to almost all types of buildings. In summary, given DesignBuilder’s applicability and precision in simulating building energy consumption, this study selects DesignBuilder as the software for representative case simulation and analysis.

3. Methods and Strategies

3.1. Experiment Overview

This study focuses on ultra-low energy consumption and energy-saving to address the practical conditions of industrial heritage. We comprehensively consider sustainable development, urbanization, technological progress, adaptive reuse, social needs, and ecological balance to explore more suitable reuse strategies, providing reference and direction for the development and reuse of industrial heritage. The flowchart of this study is illustrated in Figure 5: Firstly, based on a comprehensive analysis of geographical location, specific conditions, and typical characteristics, the Changchun Tractor Factory in Changchun, Jilin Province, is selected as the research subject. Subsequently, the original case is simulated and analyzed to evaluate its current features, surrounding context, and urban development demands, forming a “Two Enhancements and Two Reductions” design strategy tailored to industrial heritage reuse. Finally, using this strategy, four schemes are developed for the case. These schemes are then subjected to comparative analysis and validation calculations using DesignBuilder (v 7.0.2) software to determine the potential of the strategy for achieving ultra-low energy consumption.

3.2. The Case Study

Among the list of old industrial bases released in China, there are 95 prefecture-level cities, 23 of which are located in Northeast China (Including Heilongjiang, Jilin, and Liaoning Provinces), accounting for 24.2% of the total. Within the “156 Projects” of the “First Five-Year Plan” implemented in the early years of the People’s Republic of China, Northeast China hosted 56 projects, accounting for 35.9% of the total, as shown in Figure 6. Additionally, the three provincial capitals in Northeast China are all key cities for revitalizing old industrial bases [45]. As a critical area for the old industrial base revitalization, Northeast China, compared to other regions of the country, has undergone more profound industrial transformations, shifts in dominant sectors, adjustments in industrial structures, urban development demands, and significant policy changes. These factors have resulted in a larger number of abandoned or underutilized industrial heritage resources in need of renewal and reuse. Furthermore, Northeast China belongs to the severe cold B and C zones in China’s building thermal design classification, making it the coldest region in the country. Its unique geographical and climatic conditions are also among the critical factors influencing energy consumption.

China’s Ministry of Housing and Urban-Rural Development has divided thermal design zones into primary levels based on the coldest average temperatures and secondary levels based on heating degree days, as shown in

Table 2. Some thermal design zoning in China.

Name of the First-Level Zone	Main Indexes of the Classification	Name of the Second-Level Zone	Main Indexes of the Classification
Severe cold zone	tmin·m ≤ −10 °C	Severe cold zone A (1A)	6000 ≤ HDD18
		Severe cold zone B (1B)	5000 ≤ HDD18 < 6000
		Severe cold zone C (1C)	3800 ≤ HDD18 < 5000
Cold zone	−10 °C < tmin·m ≤ 0 °C	Cold zone A (2A)	2000 ≤ HDD18 < 3800 CDD26 ≤ 90
		Cold zone B (2B)	2000 ≤ HDD18 < 3800 CDD26 > 90

[46]. Most cities in the northeastern region fall under the severe cold zone, with cities in the severe cold zones B and C accounting for 72.5% of the total cities in the northeast, as indicated in

Table 3. Number of thermal design zones for cities in Northeast China.

Provinces in Northeast China	Number and Percentage of 1A	Number and Percentage of 1B	Number and Percentage of 1C	Number and Percentage of 2A
Heilongjiang Province	6; 30%	14; 70%	0	0
Jilin Province	0	3; 30%	7; 70%	0
Liaoning Province	0	0	5; 50%	5; 50%
Total number	6	17	12	5
Total Percentage	15%	42.5%	30%	12.5%

. The northeastern region, located in the northern part of China, is one of the coldest areas in the country. Moreover, the cold climatic conditions are a critical factor in building energy consumption, directly resulting in heating energy use being the highest throughout a building’s lifecycle. Therefore, selecting a representative case from the cold northeastern region, which also has the highest concentration of industrial heritage in China, adds significant value to the development of energy consumption research for industrial heritage. Among the three provincial capitals in the northeast, Changchun is centrally located, and its thermal design zone is classified as severe cold zone C, representing a midpoint within the thermal zoning range of all northeastern cities. Consequently, this study selects industrial heritage in Changchun as a representative case.

Through field research on the present situation of industrial heritage in the region, the following was found: First, most industrial buildings were constructed with assistance from the former Soviet Union, showing specific characteristics of that era. Second, northeast China primarily had developed heavy industry, resulting in most industrial sites containing similar large-span factory buildings. Third, due to the rapid development of heavy industrial areas in Northeast China during the early years of the People’s Republic of China, many of the industrial heritage sites in this region are located in relatively favorable geographical positions. And some projects are even located in city centers, meaning that their abandonment or demolition would impose a burden on surrounding residents and the environment [30].

Based on the background conditions, a comparative analysis of the existing industrial heritage in the Changchun region was conducted. Ultimately, a tractor factory located in the Erdao District (within the Second Ring Road) of Changchun was selected as the representative industrial heritage case. This selection was made because the site is situated in the city center, making it urgently in need of renovation. Additionally, most industrial heritage sites in the area are large-space factory buildings, which are the most prevalent and representative building type among industrial heritage sites in Northeast China. Established in 1958, the factory covers an area of 26.9 km² and was once the largest production base for wheeled tractors in China [47]. Over more than half a century of development, the surrounding area of the case study has transitioned to residential and educational land use. However, the site itself is still in a vacant situation, representing not only a waste of land resources but also a disconnection from the functional integration of the surrounding areas. This situation urgently calls for improvement.

It is worth noting that partial demolition and renovation have been carried out on the No. 3 Production Workshop within the factory site, while the other workshops remain vacant. Notably, the No. 2 Machining Workshop, located at the core of the factory, holds a superior geographical position and sunlight intensity compared to other workshops in the area. At present, it is being used as a temporary parking lot. We focus on conducting simulation calculations and reuse design for the overall structure of the No. 2 Machining Workshop and its A space. Based on the status analysis and development needs outlined in Section 3.3, the renovation is primarily focused on commercial use. Thermal zone setup is detailed in Section 3.5. The historical site layout is shown in Figure 7 (left), while the current site layout is depicted in Figure 7 (right). The current condition of the No. 2 Processing Workshop is illustrated in Figure 8.

3.3. Model Construction and Simulation Settings

Based on the analysis in Section 2.2, the selected representative building—Factory No. 2—was originally a machining workshop located at the center of the Changchun Tractor Factory area. Surrounded by internal factory roads, it has a building area of 18,300 m², a total building length of 154 m, a total building width of 119.2 m, and an average interior clear height of 8 m. For various reasons, it is still unused and temporarily utilized as a parking space. Its structural form combines reinforced concrete columns with a prefabricated steel roof truss, categorized as a row of reinforced concrete column structures. Through field surveys and investigations, we redrew the floor plan and section of Factory No. 2, as shown in Figure 9. Subsequently, a model was constructed in DesignBuilder based on the measurement results.

• Construction and Glazing Template: Factory No. 2 exhibits distinct characteristics of an industrial factory building in terms of structural form and internal space. According to China’s Code for Thermal Design of Civil Buildings (GB50176-2016) [46], the external opaque envelope consists entirely of 490 mm-thick red brick walls, is lightweight mortar masonry clay brick with a thermal conductivity of 0.76 (W/m·K), and exposed both internally and externally. The transparent envelope consists of double-layer ordinary glass, with a thermal conductivity of 0.76 (W/m·K). The roof is composed of prefabricated concrete slabs combined with composite steel plates. The thermal conductivity of the concrete slab is 1.74 (W/m·K), while that of the composite steel plate is approximately 0.04 (W/m·K). And the roof skylights are made of non-operable single-layer ordinary glass. Based on these features, the corresponding original structural model was established as shown in Figure 10.
• Climatic Conditions: The project is located in Changchun, the capital city of Northeast China, classified as a Severe Cold Zone C in China’s building thermal design zoning. The annual total solar radiation on a horizontal plane is 5000 MJ/m², with an average annual outdoor temperature of 4.9 °C. The climate here is short and warm in summers, while cold and long in the winters, and there are significant daily temperature variations in spring and autumn. DesignBuilder software supports the CSWD’s (Chinese Standard Weather Data) weather database, which was developed by Dr. Jiang Yi, Department of Building Science and Technology at Tsinghua University and China Meteorological Bureau, and calculates heating and cooling loads using the heat balance method [48,49]. Therefore, the meteorological data of the Changchun area in the CSWD database selected for this project, detailed information, and outdoor temperature changes are shown in

  Table 4. Weather information and daily frequency of site outdoor air dewpoint temperature and dry bulb temperature in Changchun.

  Location Templates		Daily Frequency of Site Outdoor Air Dewpoint Temperature and Dry Bulb Temperature in Changchun
  Location
  Source	ASHRAE/CSWD
  WMO	541,610
  ASHRAE climate zone	6A
  Latitude	43.90
  Longitude	125.22
  Elevation (m)	238.0
  Standard pressure (kPa)	98.5
  Time zone	(GMT+8:00) Beijing
  Winter design weather
  Outside design temperature	−25 °C
  Wind speed	2.0
  Wind direction	220.0

  .
• Activity Template: This study combines the Design Standard for Energy Efficiency of Public Buildings by Jilin Province (energy efficiency 72%) (DB22/T 5160-2024) [50], the Design standard for Green Building by Jilin Province (DB22/T 5055-2021) [51], and other standards. Additionally, the surrounding Points of Interest (POIs) were considered and analyzed. Based on this, the project is preliminarily defined with a focus on a cultural and creative business and educational template, supported by flexible structural forms, to expand the building’s adaptability and enhance its sustainability, thereby meeting more diverse user needs. The time-by-time parameterization for various types of room use requirements are shown in Figure 11.
• Other Templates: During the previous use of the factory building, the indoor temperature was maintained at the minimum standard to prevent freezing, primarily due to the heat generated by machinery, technical limitations, and cost-saving considerations. Human comfort limits and other requirements were not taken into account. Field investigations revealed that the building was originally equipped with a boiler heating system but lacked an air conditioning system. Therefore, the original model parameters exclude mechanical ventilation and cooling systems. Based on the average temperature during the heating period in Changchun, the heating temperature was set to 24 °C. The heating time was set to the annual heating cycle schedule of Changchun from October 20 of each year to April 6 of the following year.

The DesignBuilder software calculates heating and cooling loads based on the ASHRAE-approved heat balance method in EnergyPlus. Below are some commonly used ASHRAE heating and cooling load calculation formulas, which are used to determine the heating or cooling capacity required for a building [13].

The overall cooling load calculation formula is as follows:

$$\mathrm{Q}=\mathrm{U}\times \mathrm{A}\times \mathrm{C}\mathrm{L}\mathrm{T}\mathrm{D}$$

(1)

Here, Q is the cooling load (W); U is the conduction heat flow of the building shell (W/m² K); A is the surface area (m²); and CLTD is the color decorated temperature difference (K).

The overall heat load calculation formula is as follows:

$$\mathrm{Q}=\mathrm{u}\times \mathrm{A}\times (∆\mathrm{T})$$

(2)

Here, Q is the heat load (W); U is the conduction heat flow of the building shell (W/m² K); A is the surface area (m²); and ∆T is the temperature difference (K).

3.4. Building a Reuse Strategy

3.4.1. Analysis of Current Situation

This study explores the reuse of industrial heritage under ultra-low energy consumption theories, emphasizing the conservation of the historical value of the building envelope while integrating new eco-friendly materials and low-energy technologies. The analysis is conducted from the following three views:

• Current status and development needs of the Changchun Tractor Factory surrounding: A data analysis was performed on six categories of POIs (Points of Interest) within a 5 km radius of the Changchun Tractor Factory, using data sourced from Gaode Map [52]. The project samples were visualized and organized into a dataset using Kepler.gl software, as illustrated in Figure 12. It can be observed that education categories in this area are distributed very densely, followed by sports categories and mall categories. Additionally, the data obtained from POIs after data analysis are shown in

  Table 5. The POI data of Changchun Tractor Factory.

  Categories Name	Area	Number	$\mathbf{Percentage} {\mathit{P}}_{\mathit{i}}$	Deviation Average (Di)	Normalized Percentage ${\mathit{P}}_{\mathit{i}}^{\mathit{\prime }}$
  sports	Surrounding	197	5.04%	−0.0317	10.23%
  	Citywide	3912
  malls	Surrounding	94	12.00%	−0.0380	24.37%
  	Citywide	783
  parks	Surrounding	15	6.73%	−0.0148	13.66%
  	Citywide	223
  tourism	Surrounding	26	4.20%	−0.0401	8.53%
  	Citywide	619
  education	Surrounding	435	9.44%	0.0123	19.17%
  	Citywide	4610
  exhibition hall	Surrounding	9	11.84%	0.0363	24.03%
  	Citywide	76

  . To verify the accuracy of the data, we used the triple standard deviation method, and the guidelines were shown as follows:

Data Di (Deviation Average) that satisfy Di < 2σ are considered as normal; 2. Data Di that satisfy 2σ < Di < 3σ are considered early warning data, requiring expert assessment to determine their adherence to expectations; 3. Data that satisfy Di > 3σ are regarded as abnormal and necessitate re-collection and recalculation (σ is standard deviation) [53].

The results of the calculations are: σ = ±0.0309, 2σ = ±0.0619, and 3σ = ±0.0928. Based on the data computed in Table 5, it is evident that all of the data fall within two times the standard deviation range, and the validation passes. In order to make the data more readily available for statistical purposes, the results were normalized in this study. From the data in Table 5, it can be concluded that exhibition category and mall category have the highest share in the entire city, followed closely by education category, with only a small difference. Currently, after renovation of the Changchun Tractor Factory’s Building #3, it is primarily focused on shopping mall use, with the addition of multiple fitness and children’s entertainment facilities. In the update design for Building #2, this study takes into account the city’s evolution and development. The reuse of industrial heritage should prioritize long-term applicability and sustainability. By integrating the density and regional proportion data from POIs, this study ultimately focuses on the demand for education category, exhibition category, and some mall spaces.

2.

Key concerns for the conservation and inheritance of industrial heritage: The U.S. Department of the Interior, through discussions with experts, identified windows as a consistently significant element of historical buildings. This point has also been recognized in European countries, where windows are considered a unique and integral part of historical architecture, warranting maximum restoration and preservation efforts [54,55,56,57]. Consequently, this project focuses on protecting the external envelope and overall form, specifically preserving historically valuable windows, red brick walls, and building façades. Meanwhile, reuse strategies are applied to enhance the adaptability and flexibility of internal spaces [48].

3.

Sustainability of reuse projects: This study employs ultra-low energy concepts to reduce building energy consumption and extend the service life of the structure. However, due to the large spatial volume of factory buildings and the principle of preserving external enclosures, calculations using DesignBuilder indicate that achieving ultra-low energy performance while maintaining the existing enclosure is nearly impossible with current technologies. Consequently, this study incorporates the “loggias” retrofitting concept proposed by Reina Oki et al. from Waseda University in Japan [54,58] and combines it with the design of interior walking spaces, resulting in a sustainable, low-energy, and adaptable prefabricated design solution.

In addition, we learned from the design requirements outlined in China’s Code for Design of Underground Air Defense Shelters, which mandates a one-time conversion between peacetime and wartime functions [59]. This adaptable form addresses spatial limitations, technological evolution, and changing user needs. In summary, this study innovatively proposes the “Two Enhancements and Two Reductions” strategy for industrial heritage reuse design.

3.4.2. “Two Enhancements”: Increasing Functionality of Space and Diversity of Energy-Saving Materials

In terms of spatial functionality, after analyzing the spatial, structural, and regional characteristics of various industrial factory buildings, it is concluded that the reuse of industrial heritage can accommodate multiple service-oriented space functions: Under regular circumstances, it serves as a multi-school joint practice base integrating teaching, experimentation, and practical application, with additional spaces for cultural innovation business spaces; during summer and winter breaks and public holidays, it hosts exhibitions, sales events, or similar projects with commercial objectives to increase economic income, while under special requirements, it provides full dismantling capability to offer larger usable spaces when necessary. Accordingly, a variable structural design is adopted for the spatial layout, aiming to meet the requirements of different spatial volumes through flexibility and thereby enhancing utilization over time. Similarly, for other design parameters mandated by the codes, a full-coverage design is employed.

In terms of materials, new energy-saving products available on the market are selected. Research by Dorota Chwieduk has found that recent energy-saving materials—especially envelope materials—exhibit total heat transfer coefficients approximately 0.15–0.45 [W/(m²·K)] lower than those of traditional envelope materials, undoubtedly providing a better foundation for low-energy buildings [60]. The physical properties of building materials determine a building’s energy consumption [61]. In recent years, building materials have transitioned from traditional, singular options such as reinforced concrete and masonry to composite materials [62], laminated materials [63], and phase change materials [64]. Moreover, these new materials share the common characteristic of effectively reducing building energy consumption and carbon emissions. Therefore, in the structural system constructed under this strategy, the load-bearing frame utilizes prefabricated H-section steel beams and columns, offering excellent tensile and compressive strength while ensuring ease of construction and dismantling. For short-term non-removable walls, dual-cavity ultra-low energy light steel composite panels are employed, with a tested thermal conductivity value of 0.25 (W/m² K), providing exceptional insulation, soundproofing, and measures to reduce thermal bridging. Movable walls are constructed using rock wool composite panels paired with perimeter steel tracks, achieving a thermal conductivity value of 0.41 (W/m² K). These panels are lightweight, soundproof, and easily repositioned, enabling flexible spatial configurations. The glazing components feature triple-glass, two-cavity windows filled with inert gas, designed for adjustable top-and-bottom tilting, ensuring excellent insulation and soundproofing while maximizing natural light penetration. The selection of new energy-saving materials and their performance characteristics are derived from the “China Passive Ultra-Low Energy Building Annual Development Research Report 2022”.

3.4.3. “Two Reductions”: Reducing Profile Sizes and Carbon Emissions

The term “modular architecture” originated in the late 19th century and has evolved with continuous technological advancements, offering more diverse forms. Research indicates that if a building features repetitive spaces, the advantages of modularity are significantly enhanced [65]. Therefore, to meet diverse service demands, the strategy in this study minimizes the variety of structural profiles and establishes standardized modular dimensions to shorten construction periods, facilitate transportation, storage, and assembly, and enable easy disassembly and reconfiguration. Based on the factory building’s floor height, vertical structural components are standardized with a 4m module to meet the height requirements of various functional spaces and reserve enough space for natural ventilation. Horizontal structural components are modularized with dimensions of 4.5 m × 3 Nm (where N represents a multiple of the extended module), enabling seamless transitions between different functional uses and faster, simpler implementation in expansion projects.

Compared to traditional house construction, the use of steel structures and new environmentally friendly materials can effectively reduce carbon dioxide emissions. The use of numerous prefabricated steel structural components can effectively reduce carbon emissions. According to the China Annual Development Report on Building Energy Efficiency 2022 (Public Building Edition), the carbon emissions during the production of building materials primarily originate from steel and cement production, which together account for over 70% of the total energy consumption in the construction industry [66]. Furthermore, steel structures produce approximately 27% lower carbon emissions during production and transportation compared to concrete structures, with minimal differences observed during construction [67]. Therefore, this project extensively employs steel structures, prefabricated components, and modular systems, significantly reducing resource consumption, environmental pollution, construction-related pollution, and carbon emissions. This strategy primarily adopts steel structures, prefabricated components, and precast construction to significantly reduce carbon dioxide emissions. Additionally, when selecting material suppliers, we prioritize those located closer to the project site to minimize transportation energy consumption and carbon emissions. Furthermore, by implementing a standardized modular design strategy, the reusability of components is enhanced, thereby reducing resource consumption, environmental pollution, construction-related pollution, and carbon emissions. The overall technical pathway for the “Two Enhancements and Two Reductions” reuse design strategy is presented in

Table 6. The overall technical pathway for the “Two Enhancements and Two Reductions” reuse design strategy.

Reuse Strategy Deconstruction	Technology Pathway	Technology Support
Increase the functionality of the space	Constructing Variable Composite Structure System	Movable wall panel track system Foldable three-glass, two-cavity inert gas-filled windows Removable dual-cavity ultra-low-energy light steel composite panels
Increase the diversity of energy-saving materials	Reducing the energy consumption of renewed buildings	Reduction of heating (cooling) loss through the high performance of new energy-saving materials themselves
reducing profile sizes	Modular architecture	Reduced profile sizes of modularized buildings 4.5 m × 3 Nm as the standard module size
reducing carbon emissions	New energy-saving materials and standardization	Carbon reduction advantages and reuse of energy-saving materials

.

3.5. Model Construction and Simulation Settings Under the “Two Enhancements and Two Reductions” Strategy

Given the vast scale and high spatial repetition of the factory, this study selects the A space of Changchun Tractor Factory’s Factory No. 2 as a representative case. The total building area of the original Factory No. 2 is approximately 18,300 m², while the A space covers about 2376 m², with a total length of 72 m and a width of 33 m, accounting for roughly 12% of the total area.

To achieve an enhanced ultra-low-energy design, this study constructs a progressive technical verification model based on the sustainable development principles of industrial heritage and the “Two Enhancements and Two Reductions” design strategy, comprising four cases as presented in

Table 7. Explanation of the technical program level for the application of the “Two Enhancements and Two Reductions” strategy to the case.

	Program Level	Characterization	Validation Objectives
Case 1	L0—Baseline model	Partial area of the original plant	Establishing a Baseline for building energy consumption
Case 2	L1—Energy Complement Model	+The structural system of the “Two Enhancements and Two Reductions” strategy + Solar panel	Effectiveness of spatial reconfiguration and renewable energy
Case 3	L2—Thermal control model with spatial reconfiguration zoning	+The structural system of the “Two Enhancements and Two Reductions” strategy + Solar panel + Zone temperature control	Effectiveness of spatial reconfiguration, renewable energy, and zonal temperature control
Case 4	L3—Comfort Optimization Model	+The structural system of the “Two Enhancements and Two Reductions” strategy + Solar panel + Zone temperature control + Dynamic natural lighting	Dynamic optimization of energy consumption changes and comfort

. Case 1, the baseline model, simulates the energy consumption of reuse without altering the original conditions. Case 2 integrates the “Two Enhancements and Two Reductions” structural system while accounting for the advantageous aspects of photovoltaics. Case 3 not only incorporates the “Two Enhancements and Two Reductions” structural system but also simulates zonal control and the addition of photovoltaic solar panels. Building on Case 3, Case 4 addresses the lighting shortcomings caused by the factory’s 8 m clear height and internal partitioning by introducing internal structural skylights. It should be noted that while Case 1 serves as the baseline, Cases 2–4 represent progressive scheme models developed by combining the “Two Enhancements and Two Reductions” design strategy with various technical measures. The basic information for Cases 1–4 is provided in

Table 8. Basic information for Cases 1–4.

	Cooling System	Solar Panels	Zone Temperature Control	Internal Space
				Internal Enclosure Dividing	Interior Structure Roof Lighting
Case 1	Applicable	-	-	-	-
Case 2	Applicable	16 groups	-	-	-
Case 3	Applicable	30 groups	Applicable	Applicable	-
Case 4	Applicable	30 groups	Applicable	Applicable	Applicable

and

Table 9. Material information for Cases 1–4.

	Roof Material	Envelope (Restoration Only)	Internal Space
			Removable Dividing Wall	Interior Side Windows	Interior Roof	Internal Roof Windows
Case 1	250 mm prefabricated concrete panel + 80 mm laminated steel panel	490 mm red brick repair	-	-	-	-
Case 2			-	-	-	-
Case 3			Rockwool composite panel	Triple-glazed, double-cavity inert gas-filled windows	Double-cavity ultra-low energy consumption light steel composite panel	-
Case 4						Double-cavity inert gas-filled windows

, and the model construction is illustrated in Figure 13.

These usage spaces can be categorized into commercial, educational, and exhibition types, which achieve more efficient utilization by staggering their use over time. Consequently, during the construction of the energy model in DesignBuilder, the division of thermal zones becomes more complex. Considering that actual usage scenarios are complex and variable—with the time proportions allocated to different functions over the year being unpredictable and subject to uncontrollable changes—it is impossible to accurately determine the operating time and proportional duration of each function. Therefore, a full-coverage design is adopted in the simulation, while in practice, some equipment can be manually adjusted according to varying usage demands. In the model constructed using DesignBuilder, all spaces, except for corridors, are designated as usage spaces (i.e., spaces that meet the requirements for commercial, educational, and exhibition uses). Their full-coverage design parameters are presented in

Table 10. Full-coverage design parameter information for use of space for Cases 1–4.

Spaces	Lighting Power Density for Different Functional Spaces (W/m2)	Lighting Power Density with Full-Coverage Design (W/m2)	Equipment Power Density for Different Functional Spaces (W/m2)	Equipment Power Density with Full-Coverage Design (W/m2)	Fresh Air Volume for Different Functional Spaces (m3/h·person)	Fresh Air Volume with Full-Coverage Design (m3/h·Person)
Usage spaces of Case 1–4	General commercial = 10 Upscale commercial = 16 General classroom = 9 Art classroom = 15 Exhibition = 10	16	General commercial = 13 Upscale commercial = 13 General classroom = 5 Art classroom = 5 Exhibition = 10	13	General commercial = 19 Upscale commercial = 19 General classroom = 24 Art classroom = 20 Exhibition = 20	24
Spaces	Personnel Density for Different Functional Spaces (m2/h·Person)	Personnel Density with Full-Coverage Design (m2/h·Person)	Room Summer Set Temperature for Different Functional Spaces (°C)	Room Summer Set Temperature with Full-Coverage Design (°C)	Room Winter Set Temperature for Different Functional Spaces (°C)	Room Winter Set Temperature with Full-Coverage Design (°C)
Usage spaces of Case 1–4	General commercial = 4 Upscale commercial = 4 General classroom = 1.39 Art classroom = 4 Exhibition = 4	4	General commercial = 26 Upscale commercial = 26 General classroom = 26 Art classroom = 26 Exhibition = 20	26	General commercial = 20 Upscale commercial = 20 General classroom = 18 Art classroom = 18 Exhibition = 20	20

, and the corridor parameters for Cases 2–4 are provided in

Table 11. Parametric information for the hallway for Cases 1–4.

Name	Lighting Power Density (W/m2)	Equipment Power Density (W/m2)	Personnel Density (m2/Person)	Fresh Air	Lighting Power Density (W/m2)	Equipment Power Density (W/m2)
Case 2 hallway	7	13	4	19	26	20
Cases 3–4 hallway	7	13	4	19	26	10

. These data are sourced from the Chinese building code: Standard for Green Performance Calculation of Civil Buildings (JGJ/T 449-2018) [68]. In addition, there are auxiliary usage spaces such as restrooms and storage rooms; however, since this study simulates the same case using different techniques, the impact of these constant-parameter usage spaces on the simulation results is minimal. To more intuitively analyze the effectiveness of the “Two Enhancements and Two Reductions” design strategy, detailed simulations of auxiliary spaces are not conducted. Furthermore, based on the requirements of China’s General Code for Energy Efficiency and Renewable Energy Application in Buildings (GB55015-2021) [69], the nominal efficiency of each piece of equipment is determined, as detailed in

Table 12. Nominal efficiency of individual equipment.

Type	Nominal Efficiency
Heating system: coal-fired boiler	η = 85%
LED lighting	η = 95%
Cooling system: inverter air conditioner (GB 21455-2019 standard) [70]	Annual Performance Factor: APF = 4.8
Domestic Hot Water systems (DHW)	CoP = 0.85
Solar Panel	PV Constant Efficiency = 20%

.

4. Results

4.1. Analysis of the Original Model—Current Situation with No Modifications

We input the normal commercial usage requirements, including parameters for lighting, heating, and other factors, into the unrenovated factory to obtain the energy consumption data for the original building (referred to as the Original Model). The calculation results from the Original Model show that during winter, due to the large factory space, the heating system can only maintain a temperature range of indoor temperatures between 5 °C and 18 °C. In summer, due to the lack of proper passive ventilation, mechanical ventilation, and cooling systems, indoor temperatures significantly exceed outdoor levels, peaking at 30 °C. These conditions fail to meet human comfort requirements, making reuse infeasible. The monthly temperature results output by DesignBuilder are shown in

Table 13. The monthly temperature results output by DesignBuilder.

Date	Relative Humidity (%)	Fanger PMV	Fanger PPD (%)	Air Temperature	Radiant Temperature	Operative Temperature	Outside Dry-Bulb Temperature
Jan	12.11028	−1.83746	53.03131	14.68633	12.92066	13.80349	−15.3989
Feb	12.35588	−1.64383	49.12699	15.3051	14.26906	14.78708	−9.48382
Mar	20.13476	−1.33774	42.95947	16.39322	15.94101	16.16712	−3.31946
Apr	27.02408	−2.21599	68.80729	17.31706	18.46242	17.88974	7.259167
May	35.56598	−1.04275	34.4886	21.04499	22.70672	21.87586	15.05538
Jun	50.80415	2.65 × 10−2	21.27699	24.16246	25.99894	25.0807	20.20503
Jul	64.01617	0.660134	20.49438	25.74809	27.90072	26.8244	22.94425
Aug	61.84307	0.349352	19.19988	24.87872	26.87755	25.87814	21.30336
Sept	45.78144	−0.798	27.5013	21.51686	23.48149	22.49918	15.21132
Oct	36.45867	−0.67075	22.966	18.53919	19.57963	19.05941	7.616667
Nov	21.47486	−1.39804	43.77863	16.21113	15.43637	15.82375	−5.01031
Dec	16.05555	−1.75822	51.64983	14.96786	13.30296	14.13541	−11.6448

. Additionally, the monthly energy consumption throughout the year, illustrated in

Table 14. The monthly energy consumption throughout the year.

Date/Time	Room Electricity (kWh)	Lighting (kWh)	Heating (kWh)
Jan	134,958.4	114,195.5	1.00 × 108
Feb	121,897.9	103,144.4	6.51 × 107
Mar	134,958.4	114,195.5	4.63 × 107
Apr	130,604.9	110,511.8	4,406,595
May	134,958.4	114,195.5	0
Jun	130,604.9	110,511.8	0
Jul	134,958.4	114,195.5	0
Aug	134,958.4	114,195.5	0
Sept	130,604.9	110,511.8	0
Oct	134,958.4	114,195.5	7,094,450
Nov	130,604.9	110,511.8	5.27 × 107
Dec	134,958.4	114,195.5	8.21 × 107
Annual all	1,589,026	1,344,561	3.58 × 108
Energy consumption per unit area (kWh/m2)	86.83	73.47	19,562.84

, clearly demonstrates that heating energy consumption far exceeds that of lighting and equipment, with the energy consumption per unit area reaching as high as 19,562.84 kWh/m². In this context, the energy consumption attributable to equipment and lighting is almost negligible. Moreover, according to current Chinese building energy consumption standards—which stipulate that the energy consumption per unit area should not exceed 300 kWh/m²—it is evident that the factory building’s energy consumption far exceeds acceptable usage standards.

4.2. Analysis of Modeling Results for the “Two Enhancements and Two Reductions” Strategy

As shown on the left side of Figure 14, the indoor temperature for Case 1 is not ideal, particularly in winter, with an average temperature below 20 °C. In comparison, the indoor temperatures for the mall space in Cases 2–4 are relatively similar. However, the maximum temperatures in Cases 3 and 4 are significantly lower than in Case 2, and the annual temperature fluctuation in Case 4 is slightly smaller than in the other two cases. On the right side of Figure 14, which represents the air temperature variation of the month period in the walking space, the overall temperature in Case 2 is relatively high without zoned temperature control, exceeding the normal temperature range for its mall spaces. After implementing zoned temperature control, the minimum temperature requirement was reduced. However, Case 4 still demonstrates better annual temperature fluctuation compared to Case 3.

Indoor temperature variation is only a minor aspect of reflecting indoor comfort. According to international standards, the PMV (Predicted Mean Vote) model is adopted as the basis for assessing thermal comfort requirements in building interiors [71]. PMV was developed by Fanger in the 1960s and specifies that the standard indoor comfort range should fall between −0.5 and 0.5 [72]. However, some researchers argue that variables (such as age, health status, body mass index, and other characteristics) also influence human perceptions of comfort [73]. Nevertheless, this metric primarily predicts the average comfort level for the majority of people. In China, the government has similarly used this as a standard, implementing codes as shown in

Table 15. Human comfort evaluation standard according to Chinese standard [74].

Level	Evaluation Indicator 1	Evaluation Indicator 2	Explanation
Level I	−0.5 ≤ PMV ≤ +0.5	PPD ≤ 10%	Thermal environment in which 90% of the population is satisfied
Level II	−1 ≤ PMV < −0.5 or +0.5 < PMV ≤ +1	10% < PPD ≤ 25%	Thermal environment in which 75% of the population is satisfied
Level III	PMV < −1 or PMV < +1	PPD > 25%	Thermal environment in which less than 75% of the population is satisfied

[74]. Given the context of this study, the standard is sufficient to hold on the analysis of whether the proposed reuse strategies are effective.

Figure 15 presents the results for the month period, showing consistent abnormal variations in April, primarily related to the heating schedule. These discrepancies can be addressed by adjusting the heating cutoff time based on actual conditions. In the mall space, the PMV values under zoned control are closer to the Class I standard, with Cases 3 and 4 being nearly identical. For the walking space, Case 4 demonstrates better PMV performance. Figure 16 compares the results over the run period. For the mall space, the PMV values for Cases 2–4 all meet the Class I standard, while the PPD values meet the Class II standard, with Case 1 being slightly higher. In contrast, for the walking space, the PMV and PPD results for Case 2, without zoned control, are more favorable compared to the other cases.

Figure 17 and Figure 18 display the average monthly energy consumption for Cases 1–4 as simulated by DesignBuilder. Additionally, by comparing the heating and cooling energy consumption data for each month, the peak months (January and July) are selected as representative of winter and summer, respectively, for a horizontal comparative analysis of the four cases, as shown in Figure 19 and Figure 20. It is evident that Room Electricity shows minimal variation across cases. For Lighting, after adding interior skylights in Case 4, the monthly energy consumption decreased by approximately 0.169 (kwh/m²), resulting in an annual reduction of about 2.028 (kwh/m²). For Heating, after implementing zoned control (Case 3 and Case 4), monthly consumption decreased by approximately 1665 (kwh/m²), leading to a reduction of about 8325 (kwh/m²) over the heating season. For Cooling (Electricity), zoned control (Case 3 and Case 4) reduced average summer monthly consumption by approximately 0.35 (kwh/m²). In Case 4, photovoltaic energy production, combining solar panels and photovoltaic tiles, achieved a maximum monthly energy generation of 25,166 (kWh) and an annual total of approximately 203,946 (kWh). After deducting the energy used for Lighting, the remaining photovoltaic energy per year can supplement Room Electricity consumption or be stored in energy storage facilities for backup use.

5. Discussion

To comprehensively evaluate the energy-saving of the design strategy proposed in this study, the energy consumption output from DesignBuilder simulations is converted into primary energy, thereby providing a more scientifically accurate reflection of actual energy usage. According to the calculation method for coal-fired heating and the standard coal conversion coefficient specified in the General Rules for Calculation of the Comprehensive Energy Consumption (GB/T 2589-2020) [75] published by China, 1 kg of raw coal, with a lower heating value of 20,934 KJ/kg (5000 kcal/kg), is equivalent to 0.7143 kgce/kg. The formula for calculating primary energy is as follows:

$$PEC={\displaystyle \frac{E_{heat}\times 3600}{Q_{coal}\times \eta }}\times f_{coal}$$

(3)

Here, PEC is Primary Energy Consumption (kgce/tce); $E_{heat}$ is the energy consumption demand (kWh); $Q_{coal}$ is the lower heating value of raw coal (KJ/kg); $f_{coal}$ is the standard coal conversion coefficient for raw coal (kgce/kg); and η is the nominal efficiency of the boiler.

According to the “Limits on Energy Consumption per Unit Product for Coal-Fired Power Generation Units” issued in China, the coal used for power supply must not exceed 300 g of standard coal per kWh. Furthermore, public data from the Chinese Resources Bureau indicate that the maximum energy conversion efficiency of power plants is 38%, with a transmission loss rate of approximately 6%. The primary energy calculation formula for coal-fired power generation is as follows:

$${PEC}_{device}={\displaystyle \frac{E_{device}}{{\eta }_{device}}}\times {\displaystyle \frac{CEB}{{\eta }_{plant}\times f_{coal}\times (1-{\eta }_{loss})}}$$

(4)

Here, $E_{device}$ is the energy consumption demand of the equipment (kWh); CEB is the nationally prescribed upper limit for coal supply for power; ${\eta }_{device}$ is the efficiency of the equipment; ${\eta }_{plant}$ is the energy conversion efficiency of the power plant; $f_{coal}$ represents the standard coal conversion coefficient for raw coal; and ${\eta }_{loss}$ is the transmission loss rate. The unit for PEC is standard coal (kgce/tce).

By consolidating and calculating the data,

Table 16. The energy consumption and its proportions for Cases 1–4 in the run period.

Category	Indicator	Original Model	Case 1	Case 2	Case 3	Case 4
Room	Energy consumption (kWh)	1,589,026	155,024	153,890	153,890	139,916
	Energy consumption per unit area (kWh/m2)	86.832	65.49	65.01	65.01	59.11
	Percentage	0.44%	0.5445%	0.5408%	19.0981%	15.5237%
	PEC	1,966,692.91	191,868.86	190,465.34	190,465.34	173,170.11
Lighting	Energy consumption (kWh)	1,344,561	56,926	62,509	62,532	57,713
	Energy consumption per unit area (kWh/m2)	73.47	24.05	26.41	26.42	24.38
	Percentage	0.37%	0.1999%	0.2196%	7.7604%	6.4032%
	PEC	1,664,125.44	70,455.71	77,365.64	77,394.10	71,429.76
Heating	Energy consumption (kWh)	358,000,000	28,186,467	28,077,519	424,385	551,408
	Energy consumption per unit area (kWh/m2)	19,562.84	11,908.10	11,862.07	179.29	232.96
	Percentage	99.19%	99.0029%	98.6612%	52.6673%	61.1787%
	PEC	51,736,260.18	4,073,358.63	4,057,614.05	61,329.87	79,686.56
Cooling	Energy consumption (kWh)		71,934	85,452	85,824	80,303
	Energy consumption per unit area (kWh/m2)		30.39	36.10	36.26	33.93
	Percentage		0.2527%	0.3003%	10.6510%	8.9096%
	PEC		17,620.66	20,931.97	21,023.10	19,670.69
DHW	Energy consumption (kWh)	-	-	79,154	79,154	71,967
	Energy consumption per unit area (kWh/m2)			33.44	33.44	30.40
	Percentage			0.2781%	9.8232%	7.9847%
	PEC			116,335.44	116,335.4	105,772.5
All	Energy consumption (kWh)	360,933,587	28,470,350	28,458,524	805,784	901,307
	Energy consumption per unit area (kWh/m2)	19,723.15	12,028	12,023	340.42	380.78
	PEC	55,367,078.53	4,353,303.86	4,346,376.99	350,212.40	343,957.12
Generation (Electricity)		-	-	−163,978	−203,946	−203,946

presents the energy consumption and primary energy usage for different project models over one operational cycle. It is evident that the total primary energy consumption for Case 1 and Case 2 reaches as high as 4,353,303 (kgce/tce), with heating energy consumption being the predominant contributor at 4,073,358 (kgce/tce), accounting for 98–99% of the project’s total energy consumption and an energy intensity of up to 11,908 (kWh/m²). Therefore, the primary objective in reducing energy consumption is to decrease the heating load. By employing the “Two Enhancements and Two Reductions” design strategy along with zonal temperature control technology, Case 3 and Case 4 successfully reduced the heating energy consumption to approximately 50–60% of the total energy consumption, lowering the primary energy by about 4 million (kgce/tce) and reducing the energy intensity to around 180–230 (kWh/m²)—a reduction of roughly 90–95% compared to the first two cases. Additionally, the installation of 30 sets of photovoltaic solar panels is capable of providing approximately 203,946 kWh of actual power generation annually, thereby substituting a portion of the primary energy. Considering the 95% efficiency of the LED lighting system, this substitution can effectively replace all coal-fired electricity. In the Lighting sector, this results in a reduction of about 71,429 (kgce/tce) of primary energy, which accounts for 20% of the total primary energy consumption for this case.

Moreover, to verify whether the updated simulation results using the “Two Enhancements and Two Reductions” design strategy meet the ultra-low energy consumption design standards, we compare the project’s simulation outcomes with the regulatory requirements. Unfortunately, there are currently no specific standards in China for ultra-low energy consumption in industrial and architectural heritage. Therefore, we refer to the requirements for energy-saving renovations of existing buildings—which mandate that such renovations should begin with an energy diagnosis, followed by the development of renovation plans, energy-saving indicators, and testing and acceptance procedures—and to the “Ultra-Low Energy Consumption Requirements for Public Buildings in Jilin Province (DB22/T 5128-2022)” [76] issued by Jilin Province in China.

Table 17. Comparison of energy-saving requirements for ultra-low-energy public buildings and the situation of this project.

Energy Efficiency Requirements for Public Buildings with Low Energy Consumption	Limit Values	This Project
Building envelope’s airtightness (N50, h−1)	≤1.0	New structures under the “Two Enhancements and Two Reductions” reuse strategy (Case 3,4) Original factory > 1.0
Comprehensive energy-saving rate η	≥50%	92% (Case 3,4)
Energy-saving of the building itself	≥25%	10%
Renewable energy utilization rate	≥10%	14.82% (Case 3,4)

presents a comparison between the ultra-low energy requirements for public buildings and the conditions of this project. In order to preserve the historical value of the peripheral structure of the industrial heritage, the “Two Enhancements and Two Reductions” reuse strategy was implemented. While the building envelope’s airtightness, comprehensive energy-saving rate, and renewable energy utilization rate meet the requirements for ultra-low-energy public buildings, the energy-saving rate of the building itself is adversely affected by the original enclosure of the industrial heritage and thus does not meet the standards. Given the unique characteristics of industrial heritage buildings, the ultra-low-energy renovation requirements cannot be directly replicated from those of public buildings. As a result, the current simulation results of the renovation strategy essentially satisfy most of the ultra-low-energy public building requirements.

To assess whether the updated simulation using the “Two Enhancements and Two Reductions” design strategy improves occupant comfort, we utilized the indoor comfort data derived from DesignBuilder simulations. These data not only reflect the occupants’ experiences but also directly influence their satisfaction, constituting one of the indispensable criteria for sustainable development. According to the results shown in Figure 15 and Figure 16, the comfort levels of the mall space in Cases 2–4 meet Class I of the Chinese standard, achieving a 90% satisfaction rate. However, for the walking space, Case 2 meets the Class II standard, while Case 3 and Case 4, after implementing zoned temperature control, only meet the Class III standard. The walking space refers to usage areas similar to semi-enclosed corridors, semi-enclosed pedestrian streets, and loggias, where the primary goal is to maintain a comfortable level of warmth in winter and a pleasant coolness in summer, providing pedestrians with a more comfortable passage compared to outdoor conditions. Additionally, the walking space serves to seamlessly connect mall areas, creating an integrated environment for both strolling and shopping. Based on the simulation results of the “Two Enhancements and Two Reductions” reuse strategy, the comfort levels in Case 3 and Case 4 are sufficient to meet the usage needs of the walking space.

In comparison to Case 3, Case 4 introduces internal roof skylights, which, while causing some negative impacts on heat loss and other factors, are essential for regions in Northeast China, where natural lighting is in high demand to enhance user comfort by increasing natural daylight, particularly during the winter months. Therefore, even though Case 3 already demonstrates excellent energy reduction results compared to the original factory condition, Case 4 was designed with further improvements in mind, incorporating natural light for user comfort. Ultimately, whether the space is utilized as a cultural and creative commercial street, a shared educational space, or a temporary exhibition area, the design enables flexibility and adaptability to meet the varying needs of users, allowing for seamless transitions between different functions.

In summary, the analysis of the aforementioned results demonstrates that the “Two Enhancements and Two Reductions” industrial heritage reuse strategy significantly facilitates the reuse of industrial heritage within an ultra-low energy consumption framework. The development of an indoor walking space model with zonal control offers the following advantages:

• Preservation of the external envelope, conserving the historical value of industrial heritage.
• Utilization of large spaces and high ceilings in factory buildings, transforming the indoor walking space into more than just a transitional commercial area. It also provides an improved walking environment during the five-month winter period in cold regions, with an annual temperature maintained between 8 °C and 26 °C (as shown in Figure 21).
• Significant reduction in total energy consumption—compared to Case 1, total energy consumption was reduced by approximately 95%, with an annual decrease in primary energy of 4,009,346 (kgce/tce).
• Ensuring the usability and thermal comfort of the mall space, with an annual temperature maintained between 18 °C and 26 °C (as shown in Figure 21), meeting human comfort standards.

Therefore, zoned temperature control not only satisfies human thermal comfort but also optimally regulates temperature requirements for different functional spaces. Additionally, it serves as a crucial step in reducing energy consumption during the adaptive reuse of large industrial heritage factory buildings.

Although it does not possess an absolute advantage in reducing energy consumption compared to newly constructed buildings, industrial heritage—whether viewed from the perspective of historical continuity or urban transformation—demands sustainable development even more critically than new constructions. Based on the simulation results of the representative case in the DesignBuilder software, the “Two Enhancements and Two Reductions” strategy is applicable to most factory-type, high-ceiling, and large-space industrial heritage structures. During the investigation of industrial heritage in Northeast China, it was found that these types of structures were originally used for heavy industry and mechanical production. Since heavy industry accounts for approximately 70% of the “156 Project” in China, these data increase the universal applicability of the “Two Enhancements and Two Reductions” industrial heritage reuse design strategy in China.

However, the application of the “Two Enhancements and Two Reductions” industrial heritage reuse design strategy has certain limitations. This strategy may not be universally applicable to multi-story industrial buildings left by light industry. In addition, DesignBuilder’s energy consumption simulations still have certain limitations in terms of accuracy, particularly when it comes to the continuous changes over a building’s lifecycle (e.g., building deterioration). It cannot provide precise simulations of energy consumption under these evolving conditions, which restricts the ability to model and calculate sustainable low-energy performance for reused industrial heritages. Additionally, this study lacks comparisons with simulation data from other cities in Northeast China. Different regions may have varying conditions, but overall, the approach can still achieve relatively better energy consumption reduction results.

6. Conclusions

The perfect conservation and development of industrial heritage is not merely about preserving historical buildings but also about reusing them while maintaining protection. Balancing the tension between conservation and reuse is essential for the sustainable development of industrial heritage. At the same time, in the face of the global ecological crisis, industrial heritage, as part of the built environment, also faces the issue of achieving low energy consumption. Therefore, to realize a successful industrial heritage reuse project, it is necessary to balance the relationship between energy consumption, conservation, and reuse. This study integrates quantitative energy modeling with heritage conservation goals, addressing both energy consumption and cultural sustainability in the context of China’s industrial heritage. Additionally, this study identifies two main advantages of industrial heritage in Northeast China:

• The high ceiling and large space provide a high level of flexibility for reuse, accommodating diverse functional needs.
• Most are located in the city center, offering excellent foot traffic and geographical location advantages.

However, the disadvantages of these industrial heritage buildings are more pronounced:

• The large spaces result in excessively high demands for heating and cooling.
• To preserve the historical value of the industrial heritage, the factory’s envelope structure is retained, but these structures have poor thermal insulation properties.
• The large spans and multiple bays of these factories also impose significant limitations on natural daylight.

This study leverages the advantages of this industrial heritage using Factory No. 2 of Changchun Tractor Factory as a case example. It analyzes the architectural form, structural form, spatial configuration, and available space characteristics. By employing DesignBuilder software for simulation and calculation, this study integrates ultra-low energy consumption building theories, industrial heritage conservation requirements, and the “Two Enhancements and Two Reductions” strategy for the reuse of industrial heritage. This study approaches the problem from multiple angles, dimensions, and perspectives, constructing four comparative models to comprehensively address the building’s deficiencies. The final Case 4 results in a reduction of about 11,648 (kWh/m²) over the heating season. With the addition of photovoltaic solar panels, the total lighting energy consumption for the entire year is fully compensated. Although there is an increase in domestic hot water (DHW) and equipment energy consumption, the total primary energy was reduced by about 4 million (kgce/tce), and the total energy consumption still decreased by approximately 95%. This verifies the ultra-low energy consumption advantages of the “Two Enhancements and Two Reductions” reuse design strategy for factory-type industrial heritage.

In conclusion, the “Two Enhancements and Two Reductions” reuse design strategy for industrial heritage proposed in this study breaks through the limitations of traditional reuse perspectives. It provides a new approach to reducing energy consumption in factory-type industrial heritage reuse in cold regions while ensuring the preservation of historical value. This strategy proactively aligns with ultra-low energy consumption building design requirements, filling a gap in the field of industrial heritage reuse. The innovative “Two Enhancements and Two Reductions” industrial heritage reuse design strategy for industrial heritage reuse not only plays a regulatory role in the future development of industrial heritage reuse but also provides valuable reference for architects and scholars. In the future, we will consider applying this strategy to different cases, seeking a balance between commonalities and uniqueness, and continuously exploring the ultra-low energy consumption potential of industrial heritage reuse. This ongoing effort will further refine and perfect the reuse strategy. Of course, this study has certain limitations, as it does not conduct a universal analysis across more projects. However, the findings still hold significant guidance for industrial heritage reuse, particularly in cold regions, and are applicable to factory-type industrial heritage worldwide.