Renewable Energy Consumption Research Articles

Multi-objective coordinated optimization of low-carbon building energy systems based on high renewable energy penetration

In the context of China's targets to achieve a "carbon peak" by 2030 and "carbon neutrality" by 2060, the operation and maintenance of buildings with low-carbon and zero-energy consumption emerge as a critical technology for accomplishing the "dual carbon" goals in the building sector. As a novel energy supply system, low-carbon building energy systems can provide low-carbon, efficient, and economical energy supplies. Accordingly, this paper initially constructs a low-carbon building energy system based on a high penetration of renewable energy sources. Subsequently, considering the benefits of economic efficiency, carbon emissions, and renewable energy utilization, a multi-objective cooperative optimization model for low-carbon building energy systems with high renewable energy penetration is established. Finally, a multi-objective particle swarm optimization algorithm is applied to solve the model, and the system is studied and analyzed using a large domestic park as a case study. The results indicate that the low-carbon building energy system with high renewable energy integration, aiming for economic efficiency, carbon reduction, and increased renewable energy consumption, achieves supply energy costs of $ 19.2/m2 and carbon emissions of 49.1 kg/m2. These values represent reductions of $ 7.4/m2 and 60.9 kg/m2 compared to separate supply systems. Lastly, the study of the low-carbon building energy system provides theoretical references for renewable energy integration and energy transition in the building sector.

Exploring the impact of renewable energy, green taxes and trade openness on carbon neutrality: New insights from BRICS countries

The world faces two significant challenges: promoting sustainable economic growth and reaching carbon neutrality. In BRICS countries, these challenges are shaped by renewable energy, green taxes, and trade openness. These countries were selected for their strategic location and the abundance of relevant data collected over the period of 1990–2021, providing a distinctive window into the energy and economic dynamics of the area. The link between renewable energy consumption, green taxes, trade openness, and natural resources and their effects on carbon emissions in BRICS countries is examined in this study using the Fully Modified Ordinary Least Square Method (FMOLS) estimator and the Drisc Kraay estimator for the robustness test. The findings indicate that using renewable energy and green taxes primarily contribute to reducing emissions, particularly at higher emissions levels. The study reveals that various factors, namely financial globalization, trade openness, efficient resource management, and population growth, substantially impact carbon neutrality. Population growth positively impacts carbon neutrality, while using renewable energy sources mitigates it. Furthermore, the empirical findings show a statistically significant positive association between financial globalization, efficient resource management, and carbon neutrality in BRICS nations. Therefore, it is necessary to implement an integrated ecological governance strategy to control and direct financial resources towards sustainable development and green energy.

Parametric Dueling DQN- and DDPG-Based Approach for Optimal Operation of Microgrids

This study is aimed at addressing the problem of optimizing microgrid operations to improve local renewable energy consumption and ensure the stability of multi-energy systems. Microgrids are localized power systems that integrate distributed energy sources, storage, and controllable loads to enhance energy efficiency and reliability. The proposed approach introduces a novel microgrid optimization method that leverages the parameterized Dueling Deep Q-Network (Dueling DQN) and Deep Deterministic Policy Gradient (DDPG) algorithms. The method employs a parametric hybrid action-space reinforcement learning technique, where the DDPG is utilized to convert discrete actions into continuous action values corresponding to each discrete action, while the Dueling DQN uses the current observation states and these continuous action values to predict the discrete actions that maximize Q-values. This integrated strategy is designed to tackle the co-scheduling challenge in microgrids, enabling them to dynamically select the most favorable control strategies based on their specific states and the actions of other intelligent entities. The ultimate objective is to minimize the overall operational costs of microgrids while ensuring the efficient local consumption of renewable energy and maintaining the stability of multi-energy systems. Simulation experiments were conducted to validate the efficacy and superiority of the proposed method in achieving the optimal microgrid operation, showcasing its potential to improve service quality and reduce operational expenses. Average rewards increased by 30% and 15% compared to the use of the Dueling DQN or DDPG only.

Analyzing banking sector development and renewable energy consumption impact on load capacity factor in Sudan

This study delves into the impact of banking sector development (BSD), renewable energy consumption (REC) and economic growth (EG) on environmental quality (EQ), using the load capacity factor (LCF) in Sudan. Utilizing time series data from 1990 to 2018 and the Autoregressive Distributed Lag (ARDL) method, this research aims to explore both short-term and long-term dynamics, and cointegration, to provide a detailed understanding of these relationships. The study's primary objective is to elucidate the effects of BSD, REC, and EG on Sudan's EQ through the LCF metric and to test the Load Capacity Curve (LCC) hypothesis. The results indicate that the squared values of per capita GDP (long-term) and REC (short- and long-term) contribute to an increase in Sudan's LCF, thereby enhancing EQ,while BSD and per capita GDP negatively affect EQ, thus confirming the LCC hypothesis. Sudan authorities are urged to prioritize environmentally friendly economic policies, sustainable urban development, and the transition to renewable energy sources. However, the revelation that BSD diminishes environmental sustainability suggests a reevaluation of the financial sector's role. Encouraging green technologies could amplify the LCF and mitigate environmental degradation, enabling Sudan to create a sustainable environment by promoting renewable energy investments and long-term GDP per capita growth while curbing financial expansion. This research provides a critical framework for policymakers to create strategies that balance economic development with ecological preservation, ensuring Sudan's long-term sustainability.Graphical

Role of energy natural resource productivity and environmental taxation in controlling environmental pollution: Policy‐based analysis for regions

The present study explores the impact of energy natural resource productivity and environmental tax on environmental sustainability in six major CO2‐emitting economies: the Euro Area, China, South Korea, Japan, the United Kingdom and the United States, from 1997 to 2019. This analysis aims to reveal novel findings and implications for different energy natural resource productivity types and environmental regulations. We employed data regarding leading national and regional CO2 emitters from 1997 to 2020 to conduct an empirical analysis using the panel non‐linear auto‐regressive distributed lag (NARDL) and panel quantile ARDL (QARDL) methods. The results show that energy natural resource productivity and environmental tax are crucial components in reducing CO2 emissions by controlling for innovation technology and renewable energy consumption. The main findings demonstrate that the impact is stronger in the presence of increased energy natural resource productivity and vice versa. These findings have novel implications for sustainable development and carbon neutrality.

Flexible resource allocation optimization model considering global K-means load clustering and renewable-energy consumption

Abstract Vigorously developing flexible resources in power systems will be the key to building a new power system and realizing energy transformation. The investment construction cost and operation cost of various flexible resources are different, and the adjustment ability is different in different timescales. Therefore, the optimization of complementary allocation of various resources needs to take into account the economy and adjustment ability of different resources. In this paper, the global K-means load clustering model is proposed and the 365-day net load is reduced to eight typical daily net loads by clustering. Secondly, a two-level optimization model of flexible resource complementary allocation considering wind power and photovoltaic consumption is constructed. The flexible resources involved include the flexible transformation of thermal power, hydropower, pumped storage, energy storage, and demand response. The upper-layer model optimizes the capacity allocation of various flexible resources with the minimum investment and construction cost as the goal and the lower layer optimizes the operating output of various units with the minimum operating cost as the goal. The results of the example analysis show that the flexible capacity of thermal power units has nothing to do with the abandonment rate of renewable energy. As the abandonment rate of renewable energy decreases, the optimal capacity of pumped storage, electrochemical energy storage, and hydropower units increases. When the power-abandonment rate of renewable energy is 5%, the optimal allocation capacity of thermal power flexibility transformation, pumped storage, electrochemical energy storage, hydropower unit, and adjustable load in Province A is 5313, 17 090, 5830, 72 113, and 4250 MW, respectively. Under the condition that the renewable-energy abandonment rate is 0, 5%, and 10% respectively, the configured capacity of pumped storage is 20 000, 17 090, and 14 847 MW, respectively.

Renewable Energy Consumption Determinants: Do They Differ between Oil-Exporting Countries and Oil-Importing Ones?

This paper delves into the critical determinants of renewable energy consumption, focusing on the contrasting roles of oil imports and exports. It aims to bridge the knowledge gap by comparing these determinants across both oil-importing and oil-exporting nations, offering a comprehensive and nuanced perspective to inform policy recommendations. Using annual data from 1990 to 2018 sourced from the World Bank database, the study employs panel multiple regression analysis and adopts a fixed effects model to explore two main questions: What drives the use of renewable energy sources? How does a country’s oil importer or exporter status affect these factors? The findings reveal a significant but inverse relationship between oil rents and renewable energy consumption (REC) for both types of countries. Additionally, there is a notable negative correlation between GDP growth and REC for both oil-exporting and oil-importing countries. Interestingly, the crude oil average closing price and inflation show an insignificant impact on REC in both contexts. The study also highlights that net energy imports significantly affect REC, with a much stronger inverse relationship in oil-importing countries compared with oil-exporting ones. For oil-importing countries, diversifying energy sources is a crucial investment. Governments should prioritize research and development in renewable energy to spur technological advancements, enhancing efficiency and affordability. Economic growth-promoting policies, such as tax incentives and subsidies for renewable energy businesses, are vital for encouraging sustainable practices. Consistent, long-term policies are essential for providing investor confidence and supporting the transition to renewable energy. For oil-exporting countries, similar strategies are recommended. Additionally, allocating a portion of oil revenues to renewable energy infrastructure and funding research and development in renewable technologies through local universities and startups are crucial steps. This dual approach will not only enhance energy diversification but also foster innovation and sustainability in the energy sector.

The Effectiveness of the EU ETS Policy in Changing the Energy Mix in Selected European Countries

In the field of economic analysis, the study of the EU ETS policy has primarily focused on the impact of renewable energy consumption on economic growth, as well as the role of legal and fiscal instruments in the development of clean energy. This study aimed to evaluate the effectiveness of the EU ETS policy in altering the energy mix of selected European countries, providing both cognitive and applicational value. The evaluation of the effectiveness of this policy focused on the structure of the energy mix and the relationship between rising CO2 emission allowance prices and the decreasing share of coal in the energy mix. The goal was achieved through statistical analysis of secondary sources, primarily sourced from Bloomberg (2016–2024). The research findings indicated that changes in the structure of energy sources varied across the studied European countries, due to the adopted energy source utilization strategy, resource availability, and geopolitical situations. Additionally, different correlation values were noted between rising CO2 emission allowance prices and the expected reduction in fossil fuel use. Therefore, the EU ETS policy does not fulfill its assigned role—its implementation contributes to disparities in the economic situations of European economies and creates conditions for unequal competition.

Two-layer optimal scheduling method for regional integrated energy system considering flexibility characteristics of CHP system

A regional integrated energy system (RIES) guarantees the fulfillment of a diversified load demand of users by coordinating all types of energy equipment and is a two-layer optimal scheduling method that takes into consideration the flexibility of the characteristics of the combined heat and power (CHP) system is proposed in this paper. First, the thermoelectric output characteristics of hydrogen fuel cell (HFC) and CHP units are analyzed to establish an energy equipment model that takes into consideration the variability of the operating conditions. Subsequently, a two-layer optimal scheduling model of the RIES is established, where the upper layer takes into consideration the operating costs, carbon emission penalties, and renewable energy consumption capacity to determine the strategy for allocating the energy flow, and the lower layer considers the energy efficiency as the optimization objective to determine the output modes of the HFC and CHP units. Finally, an adaptive closed-loop control strategy is used to avoid the continuous startup and shutdown of the CHP unit. The simulation results show that the proposed method can effectively reduce operating costs and carbon emissions, improve energy efficiency and renewable energy consumption, and promote the efficient utilization of integrated energy resources.

Historical characteristics and projection of global renewable energy consumption

Although renewable energy consumption (REC) is increasingly crucial for addressing climate change and existing literature focused on REC from various perspectives, the historical characteristics (i.e., convergence, inequality and driver) and prospective trajectory of REC are not well assessed especially at global scale, hindering the policy implications towards sustainable development. Therefore, the study presented an in-depth investigation on the historical characteristics above and projection of REC covering 39 countries over 1990–2020 using log t convergence model, Gini coefficient decomposition model, generalized Divisia index model and machine learning forecasting models, respectively. The results indicated that, first, historical tendency of global REC was recognized with two convergence clubs and divergent countries (the USA and China). Second, Gini coefficient of global REC is increasing where regional rank is the primary driver especially from the intra-inequality of non-OECD countries. Third, GDP seems to be the predominant drivers of the global REC, especially for most non-OECD countries. Forth, countries will make advancements in REC in the coming decades, with enduring trends. Consequently, collaborative efforts and concerted actions among nations in REC development are deemed essential to foster a more sustainable and equitable REC development pattern, contributing to the realization of sustainable development goals.

Strategy for Renewable Energy Consumption Based on Scenario Reduction and Flexible Resource Utilization

Strategy for Renewable Energy Consumption Based on Scenario Reduction and Flexible Resource Utilization

Macroeconomic determinants of non-renewable and renewable energy consumption in India: The roles of international trade, innovative technologies, financial globalization, carbon emissions, financial development, and urbanization

Against scenarios of rising fossil fuel dependence and slow renewable energy adoption rates, this study appraises macroeconomic factors affecting non-renewable and renewable energy consumption in India. Additionally, this study makes a novel attempt to evaluate the determinants of divide between India's non-renewable and renewable energy consumption levels. Overall, the findings are three-fold. Firstly, it is found that in the short-run India's non-renewable energy consumption levels are positively and negatively determined by technological innovation and financial globalization, respectively. Besides, in the long-run, non-renewable energy consumption is positively influenced by international trade, financial globalization, carbon emission, and financial development; conversely, technological innovation reduces non-renewable energy consumption. Secondly, India's renewable energy consumption levels, in the short-run, are positively determined by international trade and technological innovation, while financial development impedes renewable energy consumption. Moreover, in the long-run, renewable energy consumption is positively and negatively impacted by technological innovation and financial globalization, respectively. Thirdly, the results confirm that financial globalization in the short-run and technological innovation in the long-run reduce the divide between India's non-renewable and renewable energy consumption levels. Contrarily, in the long-run, carbon emissions, international trade, financial globalization, and financial development widen this divide. Accordingly, policy suggestions are provided for the Indian government.

Assessing the load capacity curve hypothesis considering the green energy transition, banking sector expansion, and import price of crude oil in the United States

AbstractThe existing literature consists of various studies that have addressed the interrelationship between banking expansion and carbon emissions but failed to consider supply‐side ecological issues. Keeping this in view, the research aims to assess the impact of green energy transition, banking sector expansion, and import price of crude oil on the “load capacity factor (LCF)” in the United States from 1990 to 2021. The “LCF” has emerged as a novel ecological proxy to date that includes both “biocapacity and ecological footprint.” Using the “bootstrap autoregressive distributed lag” model, the research found that the consumption of renewable energy can enhance the ecological quality of the United States. The results verified the acceptance of the “load capacity curve” hypothesis. Moreover, it demonstrates that banking development promotes environmental quality. Specifically, a 1% improvement in the banking industry leads to a 0.93% increase in the LCF in the short term, as well as a 1.28% increase in the long run. Furthermore, the increase in crude oil import prices has a positive impact on the LCF and eventually promotes environmental sustainability. To be precise, a 1% rise in the price of imported crude oil results in a 0.35% increase in the long‐term LCF level. These results were backed by the findings of several robustness tests. The study, lastly, recommends that the banking sector and government policymakers should use banking growth in promoting green energy to attain their target of zero carbon emissions by 2050.

Promoting Environmental Sustainability: The Role of Renewable Energy Systems and Environmental Taxes

This study examines the effects of renewable energy consumption and environmental taxes on CO2 emissions in OECD countries from 1990 to 2022, employing the cross-sectional autoregressive distributed lag (CS-ARDL) approach. The findings reveal that both renewable energy consumption and environmental taxes significantly reduce CO2 emissions in both the short and the long term, emphasizing their crucial roles in climate change mitigation and sustainability promotion. Furthermore, this study identifies that industrialization and urbanization contribute to increased emissions, whereas foreign direct investment aids in emission reduction through the facilitation of green technology transfer. Economic growth is initially associated with higher emissions, but this trend reverses as economies mature and adopt sustainable practices. These results highlight the importance of continuous investment in renewable energy infrastructure and the implementation of robust environmental tax policies to achieve long-term sustainability goals. The integration of environmental considerations into economic and urban planning, along with leveraging foreign direct investment for technological advancements, is imperative for balancing economic growth with the necessity to reduce carbon emissions and effectively address climate change. This research provides a better understanding of the diverse factors influencing CO2 emissions and offers critical insights for policymakers.

Impact of economic growth, renewable energy consumption and energy intensity on CO2 emissions in BRIC countries: An application of CS-ARDL

Impact of economic growth, renewable energy consumption and energy intensity on CO2 emissions in BRIC countries: An application of CS-ARDL

Systematic Literature Review of Heuristic-Optimized Microgrids and Energy-Flexible Factories

Decentralized renewable energy generation and consumption through microgrids, coupled with short- and long-term storage systems and enhanced demand flexibility, represent a promising strategy for mitigating grid stress and reducing emissions in the industrial sector. However, transitioning into a sustainable industry often poses challenges in terms of economic feasibility. This review surveys current optimization approaches and simulation functionalities to enhance feasibility. It follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, covering 1066 studies from 2016 to 2023 across three research areas: optimal system sizing of microgrids (OSS), optimization of electrical energy distribution to storage systems and consumers (EED), and energy flexibilization of factories (EF). As a result, 24 filtered sources from these areas were analyzed. Quantitative analysis indicated that evolutionary and swarm-inspired metaheuristics are predominantly applied in OSS, whereas exact linear problem solvers are favored for EED and EF optimization. A range of functionalities is available, and approaches often prioritize individual functionalities, such as load forecasting, dynamic electricity pricing, and statistical representation of energy generation, rather than comprehensively integrating them. Furthermore, no current approach simultaneously integrates optimization and simulation models across all three research areas.

Multi-timescale dispatch technology for islanded energy system in the Gobi Desert

The Gobi Desert has vast wilderness to utilize, and its renewable energy capacity experiencing rapid growth. To better allocate regulation resources for maintaining power balance and frequency regulation capacity, an islanded grid optimization model considering multi-timescale dispatch optimization is constructed for integrating chemical parks with thermal power units, energy storage, and green hydrogen production. In the day-ahead optimization stage, to improve the level of renewable energy consumption, the ladder-type regulation performance of thermal power units involved in deep peak load with frequency regulation capacity is derived and established. Moving to the real-time frequency regulation stage, a novel graph neural network-based technique with infeasible region modification is proposed to rapidly acquire the operational power scheme. The input features are the time series of total power command, regulation capacity, past operating power, and past mileage command. And the output features are the mileage commands received by the resources. Training data are generated through offline optimization with the genetic algorithm, which utilizes renewable energy generation and load data with a scale of three months in the Gobi Desert. In the one-month simulation test, the proposed method demonstrated a reduction in power deviation by approximately 32.7 % and an improvement in accuracy by roughly 16 %.

The impact of renewable energy, eco-innovation, and GDP growth on CO2 emissions: Pathways to the UK's net zero target

In May 2019, the Climate Change Committee (CCC) recommended that the UK adopt a net-zero target, aiming to reduce its greenhouse gas emissions (GHG) by 100% from the 1990s baseline by 2050. The government accepted the recommendation, and the UK became the first major economy to establish a net-zero emissions law. To progress towards its climate objectives, the government took several initiatives, such as increasing its reliance on renewable energy sources and investing in climate mitigation technologies, which are commonly referred to as process eco-innovation. This study examines the impact of eco-innovation, process eco-innovation, renewable energy consumption, and economic growth on CO2 emissions in the UK using data from 1988 to 2020. We used the ARDL bound test with an error correction model (ECM) to examine the long-run and short-run cointegration between the variables of concern. We found that eco-innovation, process eco-innovation, and renewable energy consumption have significant roles in mitigating CO2 emissions, while economic growth contributes to environmental degradation in the UK. We also found that the effect of eco-innovation on CO2 emissions abatement is stronger than that of process eco-innovation in the short and long-run. Our robustness tests have confirmed the accuracy of those findings. In addition, the results from the Toda-Yamamoto causality revealed a one-way causality from process eco-innovation to CO2, renewable energy to CO2, and eco-innovation to CO2 emissions. Further, a bidirectional causality was found between GDP and CO2 emissions. The evidence presented in this paper provides great insight for shaping the energy policy in the UK and for establishing the climate budget in line with the country's net-zero target.

Green economic growth, renewable energy and food security in Sub-Saharan Africa

This study examines the impact of green economic growth and renewable energy on food security in Sub-Saharan Africa (SSA). The rationale for the study comes from the background that with a fast rate of growing population, there is a high pressure on natural resources, which often leads to resource depletion, being experienced across the globe. This study utilises panel data analysis consisting of 37 SSA countries that are members of the Official Development Assistance (ODA). Data was obtained from the Food and Agriculture Organisation (FAO) and World Development Indicators (WDI) for the period 2005–2022. To control for endogeneity, the study applies the system Generalised Method of Moments (GMM). The result shows that renewable energy and green economic growth have a positive significant impact on food security, though this impact is asymmetric across SSA sub-regions. On the other hand, industrialisation through its emissions, contributes negatively to food security. The implication is that SSA countries should focus on policies aimed at improving green economic growth and renewable energy consumption; while policies aimed at reducing the inefficient adoption of renewable electricity and discouraging industrialisation aimed at suppressing agricultural practices should be adopted.

The decoupling dilemma: Examining economic growth and carbon emissions in emerging economic blocs

This study explores whether emerging economic blocs can decouple economic growth from carbon emissions amidst global climate change concerns, integrating Environmental Kuznets Curve (EKC) theory, Stakeholder theory, and Ecological Modernization Theory (EMT). Using fuzzy-set qualitative comparative analysis (fsQCA), it examines the relationship between monetary policy and carbon emissions in two key blocs: ASEAN and GCC. Findings reveal that robust GDP growth in ASEAN correlates with higher ecological footprints, underscoring the environmental cost of rapid expansion. Conversely, the GCC region highlights renewable energy consumption as crucial for managing ecological footprints, despite challenges in energy mix adequacy. These insights offer region-specific understandings, challenging conventional views and guiding policymakers in aligning economic growth with environmental sustainability. The research underscores the need for tailored strategies to develop sustainable economic models that decouple growth from environmental degradation.