Energy Efficiency最新文献

Energy efficiency (EE) is widely recognized as a strategy to reduce greenhouse gas emissions. However, some empirical studies highlight the presence of rebound effects—where improvements in EE lead to increased overall energy consumption, ultimately resulting in higher CO₂ emissions. This study argues that such pollution-augmenting effects of EE are primarily observed in countries with poor governance quality. In contrast, economies with strong institutional frameworks—characterized by effective policy implementation and well-functioning markets—are better able to translate EE gains into actual reductions in emissions. To test all these hypothesized relationships, we use Environmental Kuznets Curve (EKC) framework and rely upon a large panel data of 112 economies over the period from 1996 to 2020. Our econometric results, based on dynamic OLS and system-GMM techniques, support the contingency effects of institutional quality in the EE–CO₂ emissions nexus. Furthermore, the empirical findings also support the relevance of the EKC theory for the selected panel economies. The study suggests that the global economy must improve the overall governance quality for reducing energy intensity and experiencing the desirable effects of EE for sustainable economic development.

Investments in energy efficiency are widely recognized as a cornerstone of sustainable energy strategies and climate change mitigation efforts, offering not only environmental benefits but also delivering substantial socio-economic gains. However, conventional evaluation frameworks tend to focus predominantly on operational energy savings, often neglecting broader lifecycle effects associated with manufacturing, packaging, installation, and maintenance phases. These include wealth and job creation, as well as embodied energy and emissions. This study introduces a comprehensive approach that integrates the Hybrid Input–Output Lifecycle Assessment methodology into Portugal’s 2021 Energy Consumption Efficiency Promotion Plan framework. By incorporating Gross Value Added, Impact on the Public Budget and embodied energy and greenhouse gases emissions this approach extends conventional Primary Energy Savings, Net Present Value and Benefit–Cost Ratio calculations typically employed in cost-effectiveness analysis, allowing a comparative evaluation of the results. The findings reveal significant variations in evaluation outcomes, with Net Present Value rising by over 4,000%, Benefit–Cost Ratio increasing by more than 34%, and two measures changing position in the funding priority ranking. These results highlight the transformative potential of the proposed methodology for guiding energy policy, supporting a more equitable and effective allocation of public funds. By incorporating broader lifecycle impacts and societal benefits, the approach also enhances the robustness of energy efficiency evaluations, paving the way for improved decision-making in national and international energy programs.

The recent progress report on the Sustainable Development Goals (2023) highlights that despite the current pace of positive and accelerating growth, developing nations are lacking the attainment of SDG7 by 2030 owing to their continuing reliance on traditional energy sources, and India is confronting an analogous situation. Therefore, at COP26, India committed to acquiring 50% of its energy consumption from renewables by 2030 and attaining net zero emissions by 2070. Thus, this study examines whether transition efforts toward renewable energy will lead to carbon neutrality. The study uses MTNARDL to confirm the asymmetric effect of renewable energy on the carbon neutrality target at various quantiles. Furthermore, we also examine how far India’s current economic growth pattern is from the achievement of SDG12 under the cubic specification of the EKC via both conditions (necessary and sufficient) from 1971–2021. The study confirms the asymmetric effect of renewable energy on carbon neutrality target and further reveals that renewable energy is effective for attaining carbon neutrality at lower quantiles. Moreover, the employed model ensures both conditions; hence, we confirm an inverse N-pattern EKC with two real tipping points. Furthermore, the estimated turning points reveal that India is currently experiencing a phase of rising CO₂ emissions. Besides, it is predicted to decline after 2036, when the per capita GDP reaches 3824.4 USD. For the economic growth-CO₂ nexus to exhibit a downwards trend, more stringent environmental policies must be implemented. Furthermore, the promotion of the renewable energy transition could contribute to the achievement of a carbon neutral economy.

Electric buses often face significant energy-consumption challenges, as air-conditioning units alone consume over 30% of such buses’ battery power at maximum capacity. To address this problem, we propose a distributed collaborative cooling method employing multiple refrigeration devices to reduce energy consumption by electric vehicle air-conditioning systems. Initially, numerical analysis is used to determine the heat load inside a vehicle, thereby facilitating the establishment of power and component models for multiple small refrigeration devices. Furthermore, a hybrid approach utilizing cameras and thermal infrared sensors is employed to detect passenger occupancy within a vehicle. The vehicle’s interior is divided into three zones—front, middle, and rear—each of which is equipped with a small refrigeration unit, rather than using a conventional single-unit configuration. The concept of the relative number of people ratio is introduced to gauge the requisite cooling capacity within the vehicle. Additionally, a novel method is proposed for pulse width modulation control of a refrigeration compressor, predicated on a comparison between the number of passengers and the interior temperature. High-temperature tests are conducted on an electric bus to evaluate the cooling performance and energy consumption of the novel refrigeration system across varying passenger loads. The results demonstrate that the system achieves the desired cooling effect while reducing energy consumption by up to 83.6% compared with traditional electric vehicle air-conditioning systems, thereby effectively extending the range of electric vehicles.

This study assessed a residential prototype located in the Global South, enhanced with thermal insulation and phase change material (PCM) in the envelope. The goal was to minimize discomfort hours and cooling energy demand while addressing the impact of climate change through future predicted weather files. To achieve this, EnergyPlus, coupled with the jEPlus + EA tool, employed the Non-dominated Sorting Genetic Algorithm II (NSGAII) for multi-objective optimization, while the CCWorldWeatherGen tool was used to generate future predicted weather files. The optimization centered on a case study located in the three hottest Brazilian bioclimatic zones. Various passive parameters related to the envelope were optimized, including building orientation, glazing solution, window size, shading device depth, thermal insulation, and PCM thickness, along with PCM melting temperature. Results highlighted the importance of optimizing the building’s orientation, glazing properties, window size, and shading devices for enhancing thermal-energy performance. As for the future weather conditions, combining these strategies with thermal insulation in cooling-dominant regions reduced the discomfort hours and energy demand by up to 80% and 60%, respectively. Although the findings were based on the Brazilian context, they are applicable to similar climates, especially in Global South countries.

Electricity plays a fundamental role in modern society, supporting essential services and contributing to economic and technological development. However, the centralized architecture of the traditional power grid and its dependence on fossil fuels have raised concerns regarding inefficiency, environmental impact, and limited operational flexibility. In response, Smart Grids (SG) and the Energy Internet (EI) have emerged as advanced paradigms that facilitate decentralized energy exchange, including peer-to-peer (P2P) energy trading. These systems introduce new challenges, particularly in energy routing, load forecasting, and demand response. Despite growing research in these areas, the literature remains fragmented, with limited integration across these interdependent components. This review addresses this gap by examining the development of the Energy Internet, comparing it with Smart Grids, and analyzing its physical and software infrastructure. The operational principles of the EI are briefly outlined, and the main challenges related to energy routing, demand response, and load forecasting are discussed. The study presents a comprehensive analysis of energy routing within the SG and EI frameworks, highlighting its dependencies on load forecasting and demand response. Existing solutions in the literature are classified by method into graph theory, game theory, autonomous, and heuristic-based approaches, and are systematically compared. The findings presented in this review serve as a valuable resource for researchers and practitioners seeking to advance the field of energy routing in the context of Smart Grids and the Energy Internet.

This research investigates using a box-window double-skin facade with semi-transparent photovoltaics in an office building located in Iran's cold and dry climate to reduce energy consumption. Simulations were conducted using EnergyPlus and LadybugTools to analyze the facade's impact on heating, electricity generation, thermal comfort, and daylighting, with two air gap depths of 0.25 m and 0.5 m. Findings show that decreasing the air gap depth from 0.5 m to 0.25 m results in higher interior temperatures. During hot periods, the Outdoor Air Curtain mode of the box-window facade achieves greater indoor temperature reduction than the Air Exhaust mode. The study found that a 20% transparent PV configuration on the exterior of the façade generates less AC power than a 40% PV position inside. The AC power output for the whole year and the lowest amount of illuminance in June are 2099 kWh and 311 (20-Ex). For optimal daylighting throughout the year, the study recommends the 20% transparent PV setup, which results in 5.6% more energy savings compared to reference glass. This configuration achieved a maximum Predicted Mean Vote (PMV) of 1.04 in July while shading devices effectively reduced overheating.

Pakistan relies almost entirely on fossil fuels, producing significant greenhouse gas (GHG) emissions that pose a serious threat to the ecosystem, particularly by contributing to global warming. Mitigating these effects requires a strong emphasis on the adoption of renewable energy sources. Prioritizing renewable energy sources not only reduces environmental harm but also helps bridge the gap between energy demand and supply, which continuously pushes a large portion of the population into energy poverty. This brings us to our principal questions: What are the determinant factors in the adoption of Solar Home Systems (SHS), and what problems are being faced by current users? To answer these questions, we surveyed 300 households through face-to-face interviews in two selected villages in Khyber Pakhtunkhwa province in Pakistan. We employed the binary logistic regression model and frequency distributions coupled with percentages. The binary logistic regression results were found significant (χ² (9) = 224.3 and P = 0.000) with the non-significant value (P = 0.290 > 0.05) of the Hosmer and Lemeshow test. Age and gender of the respondents have a negative influence on SHS adoption. In contrast, factors that positively impact adoption include education, income, family size, the cost-effectiveness of SHS compared to other alternatives, knowledge of SHS initial costs, knowledge of its operation and maintenance, and knowledge of its potential compared to other renewable energy sources. Despite the benefits of SHS, users face several challenges. The most significant issues include solar panel breakage due to strong winds, a lack of training opportunities for sustainable SHS use, higher-than-expected operational costs, and limited access to technical experts for troubleshooting. Additionally, we examined SHS users’ willingness to expand the capacity of their SHS in the future. The findings indicate that while households express interest in expansion, financial constraints limit their ability to scale up SHS capacity. SHS can be considered as a smart strategy in addressing the Sustainable Development Goals (SDGs) such as the SDG 7 (emphasizing affordable and clean energy) and SDG 13 (climate action). This research serves as a baseline study, providing stakeholders the awareness related to the factors affecting SHS adoption. This research suggests that the government should work intensively on renewable energy promotion, including SHS to deal with the power shortage and the growing climate changes in the country. They should work closely with different organizations and companies providing quality SHS through public–private partnerships. The introduction of government subsidies, enhancing technical support and focusing on capacity building will attract widespread adoption of SHS. Moreover, regulatory and policy measures should be taken by allowing excess solar energy from SHS to be fed into the national grid (net metering) a