Search Results (77)

Scrutiny over land-based photovoltaic systems (LPV) infringing on agricultural land is increasing with heightened demand for electricity. As a solution, we investigated the electricity generation potential of installing photovoltaic panels on embankments of, and floating in, ~800 irrigation reservoirs covering ~11,300 ha in Arkansas. We compared floating photovoltaic systems (FPV) to LPV using a techno-economic feasibility study that quantified (1) the difference in surface area requirements and installation cost per MW, (2) reduced wave action on embankment erosion with FPV compared to uncovered reservoirs, and (3) evaporation water savings from photovoltaic panel shading. Sensitivity analyses on water area coverage and investor adoption were also performed. Assuming a 5-MW FPV, covering 25% of surface water, and comparing it to a 100-MW LPV, the annual added electricity cost was estimated at 8.99 USD (7.80–10.54) per household (max. +0.7%). With economies of size, larger than 5-MW FPV systems installed on all reservoirs could quadruple photovoltaic capacity compared to 2025 without agricultural land use diversion. Policy options analyzed included (1) subsidizing FPV using a fee on electric bills, (2) continuing federal photovoltaic investment tax credits to lessen installation cost differences between FPV and LPV, (3) encouraging renewable energy portfolio standards, or (4) using funding sources targeted at water savings. Full article

This study examines the role of political partisanship in shaping state-level renewable energy policy, with a particular focus on the temporal dynamics of Renewable Portfolio Standard (RPS) adoption. It addresses a critical gap in the existing literature by asking whether political ideology affects RPS adoption immediately or only after delayed institutional responses. Using panel data for all 50 U.S. states from 2001 to 2024, this study contributes to the literature by identifying policy lags and structural shifts in renewable energy policy development. Employing fixed-effects panel regression with clustered standard errors, this study finds that contemporaneous Democratic control is statistically insignificant, whereas the two-year lag of Democratic control is positively and significantly associated with a higher probability of RPS adoption. The three-year lag also remains positive, although it is only marginally significant in the preferred specification. These findings support the policy lag hypothesis, suggesting that political influence is mediated by institutional inertia. Electricity prices are positively associated with RPS adoption in some specifications, whereas GDP per capita remains statistically insignificant. In addition, the Hausman test supports the fixed-effects specification, and the Bai–Perron multiple breakpoint test identifies significant structural breaks in 2007 and 2015. Overall, the findings indicate that partisan influence is better understood as a delayed rather than an immediate process. Accordingly, policymakers and stakeholders should account for institutional and regulatory lags when designing long-term energy transition strategies. Full article

As China accelerates toward carbon neutrality, decrypting the causal drivers of renewable energy expansion is paramount for effective policy design. We develop a hybrid analytical framework bridging data-driven K2 structural learning with expert-informed Bayesian Networks to map the intricate interdependencies between policy instruments, resource endowments, and socio-economic variables. This causal mapping reveals a fundamental paradigm shift from resource-bound growth to institutional-steered expansion, particularly in the solar sector where the Renewable Portfolio Standard (RPS) has superseded natural radiation as the primary determinant for capacity scaling. Forward sensitivity and backward diagnostic analyses demonstrate that achieving high-growth milestones requires a synergistic convergence of technological cost reductions and mandatory consumption quotas; conversely, the absence of RPS leads to a 64% degradation in systemic causal connectivity. These findings underscore the necessity of transitioning from price-side stimuli to structural consumption-side mandates to ensure a resilient energy transition. Ultimately, this framework and the identified causal pathways provide a strategic blueprint for other emerging economies navigating the complex transition from subsidy-dependent to market-resilient renewable energy landscapes under stringent climate constraints. Full article

Renewable Energy Certificates (RECs) have emerged as critical market-based policy instruments to promote renewable energy development worldwide. This comprehensive review examines the theoretical foundations, market mechanisms, policy effectiveness, and challenges of global REC systems based on extensive international experiences spanning over two decades. RECs function by separating the environmental attributes of renewable electricity from its physical energy, creating flexible trading mechanisms that effectively channel private investment toward renewable energy projects while providing compliance tools for renewable portfolio standards. Our analysis reveals significant variations in design and implementation across major markets, including the United States, European Union, China, India, Australia, and emerging economies. Despite their widespread adoption with over 50 countries implementing various forms of REC mechanisms, these markets face persistent challenges including price volatility, limited liquidity, regulatory inconsistencies, and ongoing debates about their environmental additionality. Recent technological developments, particularly blockchain-enabled tracking systems and digital platforms, are reshaping REC markets by enhancing transparency, reducing transaction costs, and enabling smaller-scale participation. This review proposes corresponding recommendations from the dimensions of optimizing market design, promoting digital transformation and product diversification, and establishing international coordination mechanisms. Full article

A statistical analysis of wind power development in each U.S. state from 2000–2022 shows that the Production Tax Credit strongly promoted wind power development, especially when it was due to expire, and producers rushed to qualify. This implies that the Inflation Reduction Act should also have an important effect in promoting wind power, with an exaggerated effect when developers perceive that tax credits will be discontinued. Physical wind power potential is positively related to wind power development among states. States with high potential selectively pass Renewable Portfolio Standards, but they have no statistically significant influence on capacity developed among the subset of states participating in wind power development. No other policy variables considered—natural gas prices, state permitting systems, electrical restructuring, enrollment in regional transmission organizations—displayed any practically useful association with wind power development nationally over time or among states. Full article

The global transition towards a clean energy system underscores the critical role of Green Electricity Certificates (GECs), yet their effectiveness is often hampered by an inability to credibly trace environmental attributes from generation to consumption. This study provides a systematic review of technological pathways and policy implications for enhancing GEC markets through real-time electricity-carbon traceability, using China’s large-scale and rapidly evolving market as a central case. Through comparative international analysis and examination of China’s market data (2023–2025), we identified a severe oversupply of certificates and a reliance on policy-driven demand as core structural dilemmas. The aim of this study was to clarify how real-time traceability can fundamentally enhance the credibility, temporal precision, and policy applicability of GEC mechanisms, particularly under China’s rapid institutional reforms. The findings indicate that a fundamental transition towards hourly granularity in certificate issuance and matching is critical to enhance credibility, prevent double-counting, and enable high-value applications like 24/7 clean energy matching. Furthermore, deep integration between the GEC market and the carbon emission trading (CET) scheme is necessary to expand value propositions. We conclude that the synergistic integration of market design (mandatory quotas), cross-market coupling (GEC-carbon market linkage), and robust digital traceability represents the most effective pathway to transform GECs into a credible instrument for driving additional renewable energy consumption and supporting global carbon mitigation goals. Full article

This study examines the moderating effects of renewable and nuclear energy on the relationship
between transportation index (air and land) and environmental sustainability
from 1995 to 2022 across the top 27 polluting countries. The study employed a series
of pre-estimation tests, along with the novel Method of Moments Quantile Regression
(MMQR), to estimate heterogeneous effects across the lower, middle, and upper quantiles of
environmental sustainability. The MMQR results indicate that environmental sustainability
is hampered by transportation, whereas renewable and nuclear energy promote it. The
moderation effect model shows that both renewable and nuclear energy development mitigate
the negative environmental externality from the transportation sector. The controlling
factors, GDP and inflation, are found to be harmful for environmental sustainability, while
trade openness is found to be favourable. The robustness findings using Driscoll and Kray
standard errors (DKse) yielded similar results; nonetheless, the magnitude of the coefficient
varies substantially. Thus, think tanks and policymakers are recommended to integrate
renewable and nuclear energy into the transportation sector’s energy portfolio to mitigate
its negative environmental impacts. Full article

As the scale of distributed resources continues to expand, decentralization and multi-agent characteristics bring significant challenges to low-carbon dispatching and market participation of power grids. To this end, this paper proposes a collaborative optimization scheduling framework with distributed resource aggregators (DRAs) as the main body, innovatively coupling carbon Emission trading (CET) with electric vehicle carbon quota participation, and the renewable energy quota (RPS) with tradable green certificate (TGC) transaction as the carrier, as well as constructing the connection path between the two to realize the integrated utilization of environmental rights and interests. Based on the ε-constraint method, a bi-objective optimization model of economic cost minimization and carbon emission minimization is established, and a multi-dimensional evaluation system, covering the internal and overall operation performance of the aggregator, is designed. The example shows that, under the proposed CET-RPS coupling mechanism, the total cost of DRA is about 23.4% lower than that of the existing mechanism. When the carbon emission constraint is relaxed from 2700 t to 3000 t, the total cost decreases from CNY 2537.32 to CNY 2487.74, indicating that the carbon constraint has a significant impact on the marginal cost. This study provides a feasible path for the large-scale participation of distributed resources in low-carbon power systems. Full article

As states within the United States respond to future grid development goals, there is a growing demand for reliable and resilient nighttime generation that can be addressed by low-cost, long-duration energy storage solutions. This report studies the potential of including concentrating solar power (CSP) in the technology mix to support California’s goals as defined in Senate Bill 100. A joint agency report study that determined potential pathways to achieve the renewable portfolio standard set by the bill did not include CSP, and our work provides information that could be used as a follow-up. This study uses a capacity expansion model configured to have nodal spatial fidelity in California and balancing-area fidelity in the Western Interconnection outside of California. The authors discovered that by applying current technology cost projections CSP fulfills nearly 15% of the annual load while representing just 6% of total installed capacity in 2045, replacing approximately 30 GWe of wind, solar PV, and standalone batteries compared to a scenario without CSP included. The deployment of CSP in the results is sensitive to the technology’s cost, which highlights the importance of meeting cost targets in 2030 and beyond to enable the technology’s potential contribution to California’s carbon reduction goals. Full article

This study evaluates the economic feasibility of offshore wind farm development on idle coastal areas in Korea, focusing on the Wando Geumil Offshore Wind Farm (GOWF) as a representative case. Offshore wind farms are increasingly recognized as key contributors to achieving carbon neutrality, and Korea’s coastal idle zones offer strategic potential for large-scale deployment with minimal land-use conflict. To address market uncertainty—particularly the sensitivity of revenues to the Renewable Portfolio Standard (RPS) and Renewable Energy Certificate (REC) weight—this research applies both the Discounted Cash Flow (DCF) method and Real Options Analysis (ROA), incorporating expansion and contraction scenarios. Using eleven years of historical System Marginal Price (SMP) and REC data, we estimate price volatility via a Geometric Brownian Motion (GBM) model (σ = 23.04%). The DCF results indicate a negative Net Present Value (NPV) of −313.7 million USD, suggesting baseline infeasibility. In contrast, ROA adds strategic value, with the expansion option yielding 69.6 million USD and the contraction option 2.1 million USD in additional project value. These findings demonstrate that integrating policy-driven revenue uncertainty into ROA substantially alters investment recommendations, offering practical guidance for optimizing offshore wind farm deployment on Korea’s idle coastal sites. Full article

China’s carbon emission trading market (CETM), initially covering only power generators, is expanding to include key carbon emitters, like steel and cement enterprises. These high-energy-consuming industries also participate in the electricity market as major consumers. Current research lacks a systemic analysis of multi-market, multi-entity coupling under CETM coverage expansion. This study employs system dynamics to model coupling among steel, cement, thermal power, and renewable energy enterprises within both electricity and carbon markets. Multi-scenario analysis examines key indicator changes as the policy deepens. The results indicate that the impact of CETM coverage expansion unfolds in two phases: initial and deepening stages. Policy deepening will significantly influence key indicators, such as carbon prices and grid feed-in tariffs. Allowance tightening will lead to a pronounced rise in carbon prices, and the carbon trading costs for steel enterprises are significantly higher than those for cement enterprises. The increase in Renewable Portfolio Standards obligations will affect the supply–demand dynamics in the electricity market and contribute to reducing carbon trading costs for high-emission enterprises. All entities should tailor their strategies according to their specific characteristics to proactively adapt to the market changes induced by the CETM coverage expansion. Full article

The Philippines, a country with abundant natural resources, has set a high 35% renewable energy (RE) share target by 2030. However, progress is slow with the implementation of its key policy mechanisms. Through the years, the Department of Energy has slowly increased the goals from 30% to 35% by 2030 and even up to 50% by 2050%. The key legal framework for the Philippine Renewable Energy sector is the Renewable Energy Act of 2008, which outlines key policy mechanisms: Renewable Portfolio Standards (RPSs), Net Metering, the Green Energy Auction Program (GEAP), and the Green Energy Option Program (GEOP). This paper analyzes the implementation and enforcement of the key policy mechanisms along with factors affecting their intended rollout. Along with the policy mechanism issues, this paper highlights key institutional and structural issues for the stakeholders of the RE sector. The main issues can be attributed to the incoherence of government agencies such as the Department of Energy (DOE), the Energy Regulatory Commission (ERC), and the National Grid Corporation of the Philippines (NGCP). Other issues include insufficient transmission infrastructure, resistance from Distribution Utilities (DUs) and Electric Cooperatives (ECs), and weak Local Government Unit (LGU) participation. The paper provides recommendations on the key issues of policy mechanisms and structural and institutional bottlenecks. The main recommendations that will help achieve the intended purpose of the drivers of RE are to strengthen the National Renewable Energy Board (NREB) and other agency capabilities, provide financial incentives to utilities, streamline permitting and other processes, and prioritize grid development for areas with RE development. For the targets of the DOE to be achieved, the main drivers for the RE sector must be revisited and fixed at their core. Achieving the RE targets of the DOE will need strong leadership and sustained focus on renewable energy development led by the government. Full article

This study develops an integrated risk modeling framework to assess capital adequacy and optimize portfolio performance for Thai life and non-life insurers. Leveraging ARMA–GJR–GARCH models with skewed Student-t innovations, extreme value theory, and dynamic R-vine copulas, the framework effectively captures volatility, tail risks, and evolving asset interdependencies. Utilizing daily data from 2014 to 2024, the models generate value-at-risk forecasts consistent with international standards such as Basel III’s 10-day 99% VaR and rolling Sharpe ratios for portfolios integrating green bonds compared to traditional asset allocations. The results demonstrate that green bonds, fixedincome instruments funding renewable energy and other environmental projects, significantly improve risk-adjusted returns and have the potential to reduce capital requirements, particularly for life insurers with long-term sustainability mandates. These findings underscore the importance of portfolio-level capital assessment and support the proactive integration of ESG considerations into supervisory investment guidelines to enhance financial resilience and align the insurance sector with Thailand’s sustainable finance agenda. Full article

The precise forecasting of renewable energy production and usage is essential for the stability, efficiency, and sustainability of contemporary power systems. This requirement is especially urgent in South Africa, a nation currently grappling with considerable energy issues, such as recurrent load shedding, outdated coal-fired power plants, and an increasing electricity demand. As the country moves towards a more renewable-focused energy portfolio, the capacity to anticipate future energy requirements is crucial for effective planning, operational stability, and grid resilience. This study introduces a hybrid approach that combines deep learning and machine learning techniques, specifically integrating long short-term memory (LSTM) neural networks with extreme gradient boosting (XGBoost) to provide more accurate and detailed forecasts of energy demand. LSTM networks are particularly effective in capturing long-term temporal dependencies in sequential data, such as patterns of energy usage. At the same time, XGBoost delivers high-performance gradient-boosted decision trees that can manage non-linear relationships and noise present in extensive datasets. The proposed hybrid LSTM-XGBoost model was trained and assessed using high-resolution data on energy consumption and weather conditions gathered from a coastal municipality in KwaZulu-Natal, South Africa, a country that exemplifies the convergence of renewable energy potential and challenges related to energy reliability. The preprocessing steps, including normalization, feature selection, and sequence modeling, were implemented to enhance the input data for both models. The performance of the model was thoroughly evaluated using standard statistical metrics, specifically the mean absolute error (MAE), the root mean squared error (RMSE), and the coefficient of determination (R²). The hybrid model achieved an MAE of merely 192.59 kWh and an R² of approximately 0.71, significantly surpassing the performance of the individual LSTM and XGBoost models. These findings highlight the enhanced predictive capabilities of the hybrid model in capturing both temporal trends and feature interactions in energy consumption behavior. Full article

Over the past decade, China has vigorously supported the development of renewable energy and has initially established the electricity–carbon–certificate multi-market. As a typical market-oriented demand-side management model, studying the optimization process and cases of virtual power plants (VPPs) under the multi-market has significant importance for enhancing the operation level of VPPs, as well as promoting corresponding experiences. Based on the mechanisms and impacts of the electricity–carbon–certificate multi-market, this manuscript takes a VPP project in southern China as a case, constructs a sequential decision-making optimization model for the VPP under a diversified market, and solves it using reinforcement learning and Markov decision theory. The case analysis shows that, compared to energy supply income, although the proportion of income from certificate trading and carbon trading in the multi-market is relatively limited, participating in the electricity–carbon–certificate multi-market can significantly enhance VPPs’ willingness to accommodate the uncertainties of renewable energy and can significantly improve the economic and environmental performances of VPPs, which is of great significance for improving the energy structure and accelerating the process of low-carbon energy transformation. Full article