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In this paper, we study the Stackelberg game-based evolutionary game with two players, generators and energy users (EUs), for monetary profit maximization in real-time price (RTP) demand response (DR) systems. We propose two energy strategies, generator’s best-pricing and power-generation strategy and demand’s best electricity-usage strategy, which maximize the profit of generators and EUs, respectively, rather than maximizing the conventional unified profit of the generator and EUs. As a win–win strategy to reach the social-welfare maximization, the generators acquire the optimal power consumption calculated by the EUs, and the EUs obtain the optimal electricity price calculated by the generators to update their own energy parameters to achieve profit maximization over time, whenever the generators and the EUs execute their energy strategy in the proposed Stackelberg game structure. In the problem formulation, we newly formulate a generator profit function containing the additional parameter of the electricity usage of EUs to reflect the influence by the parameter. The simulation results show that the proposed energy strategies can effectively improve the profit of the generators to 45% compared to the beseline scheme, and reduce the electricity charge of the EUs by 15.6% on average. Furthermore, we confirmed the proposed algorithm can contribute to stabilization of power generation and peak-to-average ratio (PAR) reduction, which is one of the goals of DR.

To effectively mitigate global greenhouse gas emissions, both industrialized and developing countries should participate in the energy transition that to replace fossil fuels with renewable energy. Multilateral development banks (MDBs) have been scaling up their renewable energy finance to developing countries to help them achieve their renewable energy targets. This study examines the evolution of energy financing of the World Bank, the oldest and largest MDB, by reviewing and estimating its sector-specific energy investments made over the last 35 years (1985–2019). The results confirm that the World Bank is on the right track supporting energy transition in developing countries, overall; however, limitations exist. While the share of investments in non-hydro renewable energy (NHRE) in the World Bank’s total energy finance was expanded from 1% (1985–1990) to 16.5% (2011–2019), the share of fossil fuels contracted from 51.8% (1985–1990) to 15.2% (2011–2019). However, commitments to fossil fuels have been sustained, but financing for NHRE—US$1.2 billion per year after the adoption of the Paris Agreement—is still insufficient to meet demand. Moreover, NHRE finance tended to be concentrated in middle-income developing countries. To accelerate the energy transition in developing countries, the World Bank needs to increase NHRE finance with more support for low-income countries while reducing fossil fuel finance.

Energy transformation and environmental quality are now fundamental components of China’s economic development plans, which are being reorganized to ensure the dependability of the energy supply and protect environmental quality. Nonetheless, technical inefficiency is one of the most significant obstacles to achieving these overall objectives. Therefore, utilizing yearly data from 2000 to 2021 and the autoregressive distributed lag model, this article examines the implications of information and communication technology trade openness on China’s energy transformation and environmental quality. The findings indicate that information and communication technology trade openness has a favorable impact on environmental quality as a consequence of its negative impact on carbon dioxide emissions. Moreover, the findings indicate that information and communication technology trade openness has a beneficial impact on energy transformation due to its positive impact on renewable energy consumption and negative impact on energy intensity. In conclusion, our findings demonstrate the necessity of eliminating obstacles to information and communication technology trade in China in terms of guaranteeing energy transformation and environmental quality. Therefore, it is optimal for China’s government to progressively reduce trade barriers in order to increase cross-border flows of information and communication technology products.

Standardization in energy-saving and emission-reduction measures has become increasingly important. The impact of standardization on carbon-emission efficiency in China was explored by using panel data from 2002 to 2017. The results showed that standardization significantly improved China’s carbon-emission efficiency, which remained robust after a series of tests. Furthermore, the development of industry standards had a greater effect on the improvement of carbon-emission efficiency in the economically developed coastal areas, while the development of national standards significantly promoted the improvement of carbon-emission efficiency in the inland areas. An assessment of the impact mechanism demonstrated that standardization affects carbon-emission efficiency through technological progress, industrial modernization, and economies of scale. We compared our findings with the existing literature regarding the governance of a low-carbon economy; we also considered the subsequent policy implications of our findings in terms of sustainable economic development.

The purpose of this study is to analyze the factors that affect CO2 emissions in the electricity generation sector in 36 OECD countries during the periods 1995–2008 and 2008–2017. This paper utilized Logarithmic Mean Divisia Index method for decomposing CO2 emission into economic activity, electricity intensity that represents demand policy effort, the share of thermal generation, the mix of thermal generation, thermal efficiency that represent supply policy efforts, and carbon emission coefficient. The results showed that EU nations achieved a higher level of CO2 reduction compared to that of non-EU nations. Regarding the policy factors, the decrease in the share of thermal generation served as the key driver, followed by the decrease in electricity intensity via improvements in energy consumption efficiency. Most non-EU countries such as South Korea, Chile, Mexico, Turkey, and Japan demonstrated an increasing trend of carbon emission during this period, which could be attributed to the changes in the generation mix on the supply side or the electricity intensity on the demand side. Increase in electricity price was confirmed to cause lower electricity intensity. South Korea had the largest amount of carbon emission among OECD countries and maintained one of the lowest electricity retail prices among OECD countries.

Currently, thermal power is the largest source of power in the world. Although the impacts of climate change on cooling water sufficiency in thermal power plants have been extensively assessed globally and regionally, their economic consequences have seldom been evaluated. In this study, the Asia-Pacific Integrated Model Computable General Equilibrium model (AIM/CGE) was used to evaluate the economic consequences of projected future cooling water insufficiency on a global basis, which was simulated using the H08 global hydrological model. This approach enabled us to investigate how the physical impacts of climate change on thermal power generation influence economic activities in regions and industrial sectors. To account for the uncertainty of climate change projections, five global climate models and two representative concentration pathways (RCPs 2.6 and 8.5) were used. The ensemble-mean results showed that the global gross domestic product (GDP) loss in 2070–2095 due to cooling water insufficiency in the thermal power sector was −0.21% (−0.12%) in RCP8.5 (RCP2.6). Among the five regions, the largest GDP loss of −0.57% (−0.27%) was observed in the Middle East and Africa. Medium-scale losses of −0.18% (−0.12%) and −0.14% (−0.12%) were found in OECD90 (the member countries of the Organization for Economic Co-operation and Development as of 1990) and Eastern Europe and the Former Soviet Union, respectively. The smallest losses of −0.05% (−0.06%) and −0.09% (−0.08%) were found in Latin America and Asia, respectively. The economic impact of cooling water insufficiency was non-negligible and should be considered as one of the threats induced by climate change.

The absence of electricity is among the gravest problems preventing a nation’s development. Hybrid renewable energy systems (HRES) play a vital role to reducing this issue. The major goal of this study is to use the non-dominated sorting genetic algorithm (NSGA)-II and hybrid optimization of multiple energy resources (HOMER) Pro Software to reduce the net present cost (NPC), cost of energy (COE), and CO2 emissions of proposed power system. Five cases have been considered to understand the optimal HRES system for Kutubdia Island in Bangladesh and analyzed the technical viability and economic potential of this system. To demonstrate the efficacy of the suggested strategy, the best case outcomes from the two approaches are compared. The study’s optimal solution is also subjected to a sensitivity analysis to take into account fluctuations in the annual wind speed, solar radiation, and fuel costs. According to the data, the optimized PV/Wind/Battery/DG system (USD 711,943) has a lower NPC than the other cases. The NPC obtained by the NSGA-II technique is 2.69% lower than that of the HOMER-based system.

Currently, quality air and renewable energy are main concerns in protecting the environment. Comparing willingness to pay for quality air and renewable energy is rare in the existing literature. However, the public faces these issues simultaneously. In addition, population mobility under China’s household registration system, i.e., urban living experience, may affect the willingness to pay for environmental protection. Consequently, the difference between people’s willingness to pay for quality air and renewable energy in China is discussed. Binary logistic regression is adopted to analyze the correlation factors based on data from the China General Social Survey. The results show that willingness to pay is influenced by environmental attitudes, awareness of energy use, government responsibilities, age, household income level, and trust. The effects of urban living experience on willingness to pay weakens as age decreases. Thus, improving environmental awareness and specialized knowledge remain important means of promoting willingness to pay. Our findings can help marketers and policy designers develop balanced or targeted measures when taking joint actions.