Energy Efficiency最新文献

Energy efficiency (EE) is our “first fuel” and an essential resource in reaching climate goals, reducing dependence on fossil fuels, increasing security of supply, and many other “Multiple Benefits.” However, by their nature, savings are intangible. Demand-side EE measures are typically decentralized, heterogeneous, and small-scale opportunities. The difficulties in measurement and verification (M&V) of “Negawatts” are an important and often overlooked barrier to their greater application.

M&V is a prerequisite to assess the performance of any energy, water, or CO₂-saving measure, and to quantify the savings into physical and monetary units for reporting, re-financing, GHG accounting, or other purposes. However, in practice, M&V is often perceived (particularly by clients) as cumbersome, incomprehensible, and costly.

In the broader context, energy cost savings alone are often not a sufficiently strong project driver because they lack strategic relevance for decision makers. As “Multiple Benefits” of EE become better understood, the value of quantifying savings to a high degree of accuracy may be declining, creating opportunities for more flexible M&V standards.

As a new methodology, this conceptual paper proposes to combine simplified M&V (sM&V) for individual EE measures with quality assurance instruments (QAIs) to verify functionality. This “sM&V + QAI” approach is less cumbersome, less costly, and easier to comprehend than standard M&V approaches, particularly by clients, financiers, and other non-M&V experts. It has been reviewed by international experts and successfully tested and evaluated in the field. Multiple case studies are reported to verify its practical feasibility.

This study proposes the energy conversion of vine prunings to supply energy to local wineries, with a focus on the Riunite & CIV branch winery located in Carpi (Modena, Italy), exploring the possibility of generating both electricity and heat through biomass gasification. A Matlab-Simulink model is used to evaluate the energy savings that can be achieved when an energy storage system is coupled with the combined heat and power generation system. Within this context, the results showed that it is possible to save (approx )30% of the electricity and (approx )60% of the thermal energy demanded by the winery. However, the economic viability of the project is hindered by high investment and operation costs. DPB is strongly affected by the cost of biomass and the energy prices, resulting in a profitable investment for electricity prices higher than 0.30 (div>)0.57 €/kWh according to the different scenarios investigated.

Faced with decaying networks, poor revenue collections, and substantial sunk costs and operating losses, over the last two decades, many developing countries have embarked on electricity sector reforms. This analysis examines factors driving the lack of household access to electricity in sub-Saharan Africa, including poor basic infrastructure, inadequate incentives in public service policies, geophysical barriers, and constraints in institutional environment. Based on cross-region panel datasets from Demographic and Health Surveys of 31 African countries between 2003 and 2018, a general-to-specific model selection procedure is applied to parametric regressions, with special attention to border discontinuities between power trading agreements and related border region effects. The chosen specifications are replicated in beta-function generalised linear models and kernel regressions, which specifically account for upper and lower bounds in the dependent variable. The econometric results turn out to be fairly robust to different estimation methods and data panels and suggest that sector restructuring and regional power integration initiatives have contributed to reducing the percentage shares of households without electricity access. However, remoteness from agglomeration economies of major urban centres and lack of substantive improvements in the grid and off-grid networks between neighbouring power trading pools have left many regions lagging behind, particularly in Central Africa. Programmes of poverty alleviation, including electricity services, should be more carefully targeted by strengthening local infrastructure development, access to modern energy, and cross-border integration within and between African regional power pools.

The Russian invasion of Ukraine that started on 24 February 2022 has had a dramatic impact on the energy policy of the European Union and its member states. Nonetheless, not all EU members have radically overhauled their energy sectors and policies. Looking at the period between February 2022 and December 2023, this paper argues that Slovakia’s energy sector has remained unchanged in comparison to developments within the EU and beyond. Slovakia has continued to purchase natural gas from Russia, having negotiated an exemption from the EU sanctions on Russian oil, and gas consumption decreased only minimally in the winter of 2022/2023. Furthermore, it maintained at best a lukewarm position on renewable energy sources and even struggled to implement those energy efficiency measures that were included in the post-pandemic recovery plans. Slovakia also did not reconsider its coal phase-out deadline of 2023 and its (already very supportive) nuclear policy. We explain this policy persistence with the help of a revised lock-in concept which, in the case of Slovakia, is mostly connected to nuclear energy (ʻnuclear lock-in’), which locks out alternative energy sources, especially renewables.

Due to its important role in smart grids, power system management, and smart buildings, energy consumption forecasting has gained a lot of interest in recent years, further achieving energy efficiency objectives, decreasing CO(_2) emissions, and reducing energy bill. Because of the nonlinear and non-smooth characteristics of residential building electricity consumption time series data, developing an accurate energy consumption model is a crucial task. To solve this constraint, this research proposes a short-term, hybrid model that combines variational mode decomposition and Bi-GRU with the aim to predict household energy consumption forecasting of the next 24 hours with a time granularity of 15 minutes. The VMD algorithm in this model decomposes the power consumption time series into distinct signals called IMFs, and the Bi-GRU is used to predict each IMF separately. To produce the final prediction output, the prediction results of each model are summed and rebuilt. The conclusive findings indicate that the forecasting model based on VMD-BI-GRU demonstrates exceptional performance, with a mean squared error of 0.0038 KW, a mean absolute error of 0.046 KW, a mean absolute percentage error of 0.11%, and a notably high R(^2) score of 0.98. These results collectively signify its precision as a prediction model.

Following the invasion of Ukraine and the associated energy policy tensions with Russia, the EU began looking at how it could replace Russian energy sources. One of the proposed solutions is to decrease energy consumption. Buildings have been the principal target, owing to their high energy usage – especially of natural gas, which the EU is particularly keen on reducing. This literature review article summarises existing knowledge on the potential energy savings that can be made through energy efficiency improvements to existing buildings in Central and Eastern Europe. The countries in this region share common traits due to their Communist past and associated legacy of poor energy efficiency, both generally and in buildings in particular. At the same time, Central and Eastern Europe contains a range of geographical and climatic regions, and so, the findings of this paper are applicable to other regions. This bibliometric analysis identifies three main areas (insulation, heating source and policy) in which the academic literature has identified potential for energy efficiency improvements to buildings. On the basis of these findings, this paper looks at the policy implications for reducing energy consumption in buildings and thus helps the EU to become less dependent on energy supplies from Russia.

This study proposes a novel approach that integrates demand response strategy with operational scheduling to investigate the process flexibility in the operational performance under time-sensitive electricity tariffs and to provide cost-benefit analysis to industrial consumers. The proposed approach focused on implementing a demand response strategy with integrated process flexibilities at the supply side, storage and demand side in a case study of scheduling for an industrial network of compressors for Time of Use and Enhanced Time of Use energy tariff. The optimisation framework was developed as a mixed-integer linear programming model. The implementation of the demand response strategy resulted in a total cost reduction of between 5 and 13%. Furthermore, a considerable cost saving was shown to be achievable for the Enhanced Time of Use energy tariff since it offers an extensive off-peak time zone during the night hours and on the weekend. It is concluded that the study highlights the operational performance goal of achieving cost savings by implementing a demand response strategy for energy industries.

Graphical Abstract

Municipal governments, often in collaboration with utilities, have implemented a range of energy efficiency programs to encourage homeowners and businesses to adopt energy efficiency upgrades. Energy efficiency holds promise to reduce energy consumption, reduce greenhouse gas emissions, improve public health, and reduce energy bills. However, these programs often suffer from poor participation and have typically had limited success. In this analysis, we use novel data to understand the relationship between social norms, pro-environmental identity, and household finances to understand program participation and retrofit decision-making. We find that the variables that predict retrofit decision-making do not explain a household’s initial decision to contact an energy efficiency program. We suggest that the processes that drive households to contact energy efficiency programs—a necessary first step in improving energy efficiency—are different from the processes that explain why households decide to upgrade their homes.

Following the initiatives of the United Nations Framework Convention for Climate Change (UNFCCC) and especially since the Paris Agreement of 2015, corporate environmental performance has become a critical component of corporate financial performance. Particularly, stakeholder pressure has driven environmental and financial inclusion targeted at raising corporate performance. Hence, this paper examines the link between corporations’ environmental performance (CEP) and corporations’ financial performance (CFP) using annual panel data from 130 corporations from China and 166 corporations annually over the years from 2010 to 2018. The empirical results from the FMOLS and ARDL tests show that corporations’ good emission preventive practices translate into improved financial performance in Japan but not in China, which is a reflection of the advanced earlier development of environmental governance in the former and the latecomer status of the latter. Nevertheless, environmental disclosure raises corporate financial performance in both China and Japan in the long run but CSR strategy is negatively correlated with corporate financial performance. Also, while the Dumitrescu Hurlin causality test shows that there is significant bidirectional causality between CEP and CFP in the Japan sample, this relationship is weak in the China sample. While the results confirm actions by Japan and China to strengthen corporate environmental governance, the initiatives in China should be quickened to enhance the relationship between CEP and CFP.

Appropriate thermal modeling is the first step in controlling thermal comfort and reducing energy consumption. In this article, the thermal modeling of an office room with a variable air volume (VAV) system is considered. Various thermal modeling methods are reviewed, and finally, the zonal method is selected. The main advantage of the selected method is its simple formulation but still accurate results. Furthermore, the output equations are in the state-space forms which are suitable for control applications. The thermal model is obtained by considering the airflow patterns in the office room. One of the key features of the obtained model is its applicability to winter as well as summer conditions. DesignBuilder software is also used to validate the thermal model. Results indicate the accuracy of the obtained thermal model in all weather conditions.