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This paper aims to develop a machine-learning model based on a gradient-boosting algorithm to predict the energy-saving awareness of households using a questionnaire survey and 11-month energy data collected from more than 200 smart houses in Kitakyushu, Japan. We utilize the LightGBM (light gradient boosting machine) classifier to perform feature selection for the prediction. By using this approach, we demonstrate that the key features are the standard deviations of electricity purchased between 8 a.m. and 9 a.m. and electricity consumed between 7 p.m. and 9 p.m. Next, by using k-means clustering we split the households based on the obtained features into three groups. Finally, by using statistical hypothesis testing, we prove that these three groups have statistically distinct levels of energy-saving awareness. This model enables us to detect eco-friendly households from their energy data, which may support energy policymaking.

Under rapid urbanization-induced global warming and resource depletion, growing interest in zero-energy building (ZEB) and zero-emission building (ZEB) technologies have emerged globally to improve energy performance in homes and shape sustainable cities. Although several countries have released ZEB-enhanced strategies and set national standards and policies to promote ZEBs, construction projects are still limited to demonstration projects. This paper reviews global ZEB activities and state-of-the-art technologies for energy-efficient residential building technologies [based on an evaluation of 40 residential buildings]. Over 40 residential buildings on different continents were reviewed, and their technical details and performance were evaluated. Our results show that 62.5% of the buildings achieved the +ZEB standard, 25% of the buildings were net-zero energy buildings, and only 12.5% of the buildings were near-zero energy buildings. Solar PV is the most widely used renewable energy source in the studied cases, while in warmer climates, advanced cooling technologies and heat pumps are the preferred technologies. A building envelope and thermal ventilation with heat recovery are essential in cold climates. Our systematic analysis reveals that the thermal performance of the building envelope and solar energy are the most effective mechanisms for achieving energy efficiency and shaping sustainable cities.

As the field of zero energy building design and research continues to progress, the use of data analysis methods is on the rise. These methods are applied to create assessment criteria, compare performance, and aid in design decision making. Decision trees, as a data-driven approach, offer interpretability and predictability, assisting designers in summarizing their design experience and serving as a foundation for design references. However, the current application of decision tree methods in the zero energy house sector primarily focuses on HVAC systems, lacking a comprehensive exploration from an architectural design perspective. Therefore, this study presents an empirical method for building and applying models based on decision trees, using zero energy house cases in severely cold regions of China as samples. Through an analysis of the interactions among various passive design parameters and the use of EnergyPlus for performance simulations, a decision tree model is established. This model aids in determining the recommended combinations of passive design parameters that meet the criteria of low energy consumption. Moreover, feature weighting highlights the most influential passive design parameters on building energy consumption, including the length of the architectural gestalt plane, the roof shape, and the ground thermal resistance. This research provides valuable methods and guidance for the design and construction of zero energy houses in severely cold regions of China.

ZEHs (Zero Energy House) featuring energy-efficient designs and on-site renewable integration are being widely developed. This study introduced Japanese ZEHs with well-insulated thermal envelopes and investigated their detailed operational performances through on-site measurements and simulation models. Measurement data show that ZEHs effectively damped the variation of indoor air temperature compared to conventional houses, presenting great ability to retain inside heat energy, and are expected to potentially deliver energy flexibility as a virtual thermal energy storage medium. We developed a simplified thermal resistance–capacitance model for a house heating system; response behaviors were simulated under various scenarios. Results compared the variations of indoor temperature profiles and revealed the dependence of load flexibility on the building’s overall heat loss performance. We observed that overall heat loss rate played a crucial role in building heat energy storage efficiency; a well-insulated house shortened the heat-up time with less energy input, and extended the delayed period of indoor temperature under intermittent heating supply; a high set-point operative temperature and a low ambient temperature led to lower virtual thermal energy storage efficiency. The preheating strategy was simulated as an effective load-shifting approach in consuming surplus PV generation; approximately 50% of consumed PV generation could be shifted to replace grid import electricity for room heating during the occupied period.

In this study, we assessed a lifestyle in which occupants adjust the fittings based on climate, weather, and time, in terms of energy efficiency and thermal conditions. The proposed solution is a Zero Energy House (ZEH) with high thermal performance. The thermal performance of the building envelope can be adjusted by changing the operation of fittings based on the indoor and outdoor environments, as well as air conditioning usage. Many studies have achieved zero energy by increasing the thermal performance of an envelope and using highly efficient energy-saving facilities; however, uniquely, here we focus on occupant behavior to change the building envelope condition. In this paper, numerical analysis was used to investigate the effect of adjusting the fittings on buildings with different thermal performances of the envelope. The analysis demonstrates that, while more research into measures is needed in the summer, the adjustment of fittings and thermal storage properties in the winter season can reduce the heating load by 48–59% compared to the normal ZEH and improve the indoor environment. In terms of the heating and cooling load throughout the year, the results also showed that applying fittings adjustment and heat storage to an ordinary house can provide nearly the same energy-saving effect as a highly insulated house.

Over the past 20 years, net-zero energy house (NZEH) construction costs have steadily decreased because of many reasons, such as technical progress, energy-saving design obligations, and dramatic cost reductions in renewable energy systems, especially solar power systems. Currently, the costs of NZEH are estimated to be about 5% higher than similar-sized houses. These additional costs are mainly for installing PV systems, which can be offset by energy saving costs. This study assessed energy performance and load matching through remote monitoring systems, and energy costs were analyzed for two-family houses. The two houses were all-electric houses and different in both size and location. A 6 kWp grid-connected PV system and 16 kW air source heat pump for space heating and domestic hot water were equally implemented. After data analysis, 100% of the energies were supplied through the PV system for 3 years, thus achieving net-zero energy. According to the Korean residential electricity tariff system, the annual electricity charges were, on average, between USD 105.1 and USD 121.4 after adding demand charges and value-added tax for import electricity charges. The energy cost reduction rate, compared to the same house without a PV system, was about 95%, and the simple payback period of the 6 kW PV system in NZEH was about 6 years. In addition, the annual load cover factor and supply cover factor as load-match indices between electricity generation and the load were in a range of 0.39–0.49 and 0.37–0.42, respectively.

This paper addresses the critical challenge of multi-objective optimization in residential Home Energy Management Systems (HEMS) by proposing a novel framework based on an Improved Multi-Agent Proximal Policy Optimization (MAPPO) algorithm. The study specifically targets the low convergence efficiency of Multi-Agent Deep Reinforcement Learning (MADRL) for coupled Battery Energy Storage System (BESS) and Air Source Heat Pump (ASHP) operation. The framework synergistically integrates an action constraint projection mechanism with an economic-performance-driven dynamic learning rate modulation strategy, thereby significantly enhancing learning stability. Simulation results demonstrate that the algorithm improves training convergence speed by 35–45% compared to standard MAPPO. Economically, it delivers a cumulative cost reduction of 15.77% against rule-based baselines, outperforming both Independent Proximal Policy Optimization (IPPO) and standard MAPPO benchmarks. Furthermore, the method maximizes renewable energy utilization, achieving nearly 100% photovoltaic self-consumption under favorable conditions while ensuring robustness in extreme scenarios. Temporal analysis reveals the agents’ capacity for anticipatory decision-making, effectively learning correlations among generation, pricing, and demand to achieve seamless seasonal adaptability. These findings validate the superior performance of the proposed centralized training architecture, providing a robust solution for complex residential energy management.

This research introduces a residential net-zero energy house named i-Yard 2.0, which was built by a team from Beijing Jiaotong University for the 2018 Solar Decathlon China competition. The concept was based on the needs of an aging population and achieves energy self-sufficiency through both active (i.e., solar energy) and passive design strategies. With the growing recognition of the need for better environmental protection, green building strategies have become mainstream in building development. A building’s energy balance is one of the most important indexes for assessing green buildings. The i-Yard 2.0 adopts an integrated design strategy with a sustainable development background. It takes a senior citizen-oriented design as the starting point and innovates in aspects such as community modeling, building strategies, passive spatial planning, the energy and building environment, and intelligent building control. The community comprises a new residential model called “cooperative living.” The building strategy adopts a modular assembly approach in order to achieve rapid construction suitable for this type of competition. The passive spatial plan uses the notion of the courtyard as a green core to regulate the microclimate. The building environment achieves net-zero energy by improving active energy access and reducing passive energy consumption. The internet control model was designed to incorporate intelligent building control. The i-Yard 2.0 provides not only a new form of senior residential housing for developing areas, it also provides a novel and worthy reference for net-zero energy housing in China.

The implementation of renewable energy systems (RESs) in the agricultural sector has significant potential to mitigate the negative effects of fossil fuel-based products on the global climate, reduce operational costs, and enhance crop production. However, the intermittent nature of RESs poses a major challenge to realizing these benefits. To address this, thermal energy storage (TES) and hybrid heat pump (HHP) systems are integrated with RESs to balance the mismatch between thermal energy production and demand. In pursuit of clean energy solutions in the agricultural sector, a 3942 m2 greenhouse in Yeoju-si, South Korea, is equipped with 231 solar thermal (ST) collectors, 117 photovoltaic thermal (PVT) collectors, four HHPs, two ground-source heat pumps (GSHPs), a 28,500 m3 borehole TES (BTES) unit, a 1040 m3 tank TES (TTES) unit, and three short-term TES units with capacities of 150 m3, 30 m3, and 30 m3. This study evaluates the long-term performance of the integrated hybrid renewable energy and thermal energy storage systems (HRETESSs) in meeting the greenhouse’s heating and cooling demands. Results indicate that the annual system performance efficiencies range from 25.3% to 68.5% for ST collectors and 31.9% to 72.2% for PVT collectors. The coefficient of performance (COP) during the heating season is 3.3 for GSHPs, 2.5 for HHPs using BTES as a source, and 3.6 for HHPs using TTES as a source. During the cooling season, the COP ranges from 5.3 to 5.7 for GSHPs and 1.84 to 2.83 for ASHPs. Notably, the HRETESS supplied 3.4% of its total heating energy directly from solar energy, 89.3% indirectly via heat pump utilization, and 7.3% is provided by auxiliary heating. This study provides valuable insights into the integration of HRETESSs to maximize greenhouse energy efficiency and supports the development of sustainable agricultural energy solutions, contributing to reduced greenhouse gas emissions and operational costs.

The integration of battery energy storage systems (BESS) with renewable energy is a potential solution to address the disadvantages of renewable energy systems, which is irregular and intermittent power. In particular, residential BESS is advancing in numerous countries. The residential BESS connected to the photovoltaic system (PV) can store the PV power in the battery through charging, and supply the PV power, which was stored in the battery, to the load through discharging when there is no PV power. Therefore, the utilization of residential BESS with PV reduces the daily electric power consumption and the electricity bills that households have to charge. However, it is understood that there is no case of installing and using residential BESS in Korea yet. Most residential houses in Korea are apartment houses, and thus residential BESS can be used with balcony PV. This paper presents operation modes of residential BESS with balcony PV for apartment houses. The BESS capacity was estimated by considering the balcony PV capacity, which can be installed in households, and power consumption. The applicability of the residential BESS was analyzed through performance and economics evaluation under current and various conditions. The operation modes of BESS were divided into four types according to PV power supply priority and battery charging source, and a test took place in a demonstration house. The risk of fully discharging the battery has been discovered when PV power is first charged to the battery or when only PV power is charged with the battery. As a result, preferential charging of the battery with PV power and then with PV and grid power was found to be the most optimal operation mode. In addition, additional functions were proposed for residential BESS in apartment households. The results will contribute to effective application of residential BESS with balcony PV in the near future.