Renewable Portfolio Research Articles

The interactions between renewable portfolio standards and carbon emission trading in China: An evolutionary game theory perspective

Renewable Portfolio Standards (RPS) and Carbon Emission Trading (CET) are the policy instrument for China to achieve the low-carbon energy transition. Changes in policy combinations will affect the equilibrium state of the interactive system and bring uncertain risks to the expected effects of policy implementation. Given the assumption that the power users undertake RPS assessment and the CET market is extended to industries in addition to the power generation industry, this paper first constructs a game model in the context of RPS and CET where groups of power users and thermal power manufacturers jointly participate. Then, with China's provincial market data, it analyzed the evolution process of group strategy under different policy parameters and described the characteristics of the transition between the stable and unstable states of the system. Finally, a dynamic and differentiated mechanism design for policy parameters is proposed to restrain system oscillations. The simulation results reveal the interaction between market players' strategies, and a quantitative framework for analyzing system stability under different policy parameter combinations is proposed, which can provide an analysis framework for China to implement RPS and CET and deliver a relevant analysis basis for setting policy parameters.

Can renewable energy portfolio standards and carbon tax policies promote carbon emission reduction in China's power industry?

The carbon emissions of the power industry in China rank the highest among all industries. There is an urgent need to explore the development path of the power industry under carbon peaking and carbon neutrality. Renewable portfolio standards (RPS) and carbon tax policy are effective policy instruments for realizing the low-carbon transition in the power industry. When both RPS and carbon tax policy are implemented, can they drive carbon reduction in the power industry? This paper constructs an electricity market equilibrium model and a system dynamics (SD) model to analyse the impact of multiple policies in electricity markets to address this question. There were several important results. (1) The increase in quota ratio and carbon tax price negatively impacts the generation of thermal power firms, which raises their willingness to invest in renewable energy. (2) The intensity of emissions reduction has a significant influence on the effectiveness of emissions reduction. The greater the emissions reduction intensity, the better the carbon emissions reduction effect, but the power supply declines. (3) Under multiple policies, green power firms choose cost padding to achieve profit maximization goals, which reduces green power generation and leads to market inefficiency.

An inter-provincial cooperation model under Renewable Portfolio Standard policy

The Renewable Portfolio Standard (RPS) has been implemented by a number of the world's most economically developed nations, to address the great challenges faced regarding energy problems and climate change. However, the current non-cooperation model (NCM) of the RPS in China cannot effectively overcome the bottleneck of renewable energy development due to the disparity between renewable energy-rich regions and high energy-consuming regions. To resolve this dilemma, this study proposes an inter-provincial cooperation model (ICM) under the RPS in China. The ICM consists of two parts: (1) an optimization model to obtain the lowest RPS target realization cost and ensure efficiency, and (2) cost allocation models based on the Shapley value, core, and nucleolus methods, to ensure fairness in different situations. The cases of Beijing, Shandong, Shanxi, and Inner Mongolia show that the total cost of the four provincial regions covered by the ICM will be reduced by 57.07 × 108 CNY, or 8.25% compared with the NCM. Sensitivity analysis was conducted to test the impact of different parameter values on the ICM results. Based on these results, we propose policy recommendations to promote implementation of the ICM.

Electricity Market Reforms for Energy Transition: Lessons from China

In response to the rising importance of the climate agenda, many countries have restructured their electricity markets to facilitate the utilization of renewable energy. China is an interesting case because it has expanded its utilization of wind and solar energy with unmatched speed. This review starts with an analysis of the 2002 reforms that uncoupled electricity production from transmission. The investigation covers the period leading up to the 2022 proposal, which aimed to build a nationally integrated electricity market. The analysis suggests that a careful alignment of incentives for key market players to produce and consume renewable energy is vital during the process of energy transition. The introduction of feed-in tariffs in 2009 for wind energy, which were subsequently extended to solar energy, stimulated a high growth in installed capacity. However, a high electricity curtailment rate resulted. Since 2018, the Chinese government has resorted to curtailment caps and renewable portfolio standards to increase the utilization of renewable electricity. After the announcement of the “dual carbon goals” in 2020, the Chinese government launched a series of reforms that aimed to nurture growth in the green electricity market and the formation of a nationally integrated electricity market. The removal of interregional trade barriers is a key element of China’s current electricity market reforms and will be crucial to determining whether China can achieve its climate goals.

What affects the implementation of the renewable portfolio standard? An analysis of the four-party evolutionary game

The renewable portfolio standard (RPS) has become the primary policy tool to promote the transformation of the energy system. However, in the RPS implementation process, there are usually differences in the completion effects between provinces, so exploring the implementation influencing factors of RPS policy is significant. Given the diversity and complex interaction of subjects and strategies, we construct a four-party evolutionary game model including the central government (CG), local governments (LGs), power generation enterprises (PGEs), and power grid corporations (PGCs), and systematic analysis of the strategic behavior and main influencing factors. The results demonstrate that the CG, its strategy will change with the size of the incentive intensity. For LGs, its strategies are affected by factors such as regulatory costs, and unit fines, especially when the regulation cost is less than the penalty amount for the unfulfilled quota of PGCs; the LG is more inclined to choose strong regulation. For PGEs, the net income of different power generation forms will significantly impact the strategy of PGEs, and indirectly affect the strategy of LGs. For PGCs, increasing the incentive intensity, increasing the punishment of LG to PGCs, and reducing the operation cost of PGCs can help PGCs to complete the quota.

Influence mechanism of renewable portfolio standard on energy producers

Renewable energy Portfolio Standard (RPS) policy plays a significant role in reducing carbon dioxide emissions and promoting the development of renewable energy. Based on bounded rationality, this paper constructed an evolutionary game model to analyze energy power production decision-making, involving both fossil and renewable power producers as participants. Through the discussion of evolutionary game equilibrium, the study revealed the following findings: (1) marketised TGC price benefits the reduction of fossil energy power production: (2) Tire implementation of RPS policy does not necessarily lead to an increase in total renewable energy production; (3) Under RPS policy, the higher proportion of renewable energy quota is not always advantageous for reducing fossil energy power production.

A level-set approach to the control of state-constrained McKean-Vlasov equations: application to renewable energy storage and portfolio selection

We consider the control of McKean-Vlasov dynamics (or mean-field control) with probabilistic state constraints. We rely on a level-set approach which provides a representation of the constrained problem in terms of an unconstrained one with exact penalization and running maximum or integral cost. The method is then extended to the common noise setting. Our work extends (Bokanowski, Picarelli, and Zidani, SIAM J. Control Optim. 54.5 (2016), pp. 2568–2593) and (Bokanowski, Picarelli, and Zidani, Appl. Math. Optim. 71 (2015), pp. 125–163) to a mean-field setting.The reformulation as an unconstrained problem is particularly suitable for the numerical resolution of the problem, that is achieved from an extension of a machine learning algorithm from (Carmona, Laurière, arXiv:1908.01613 to appear in Ann. Appl. Prob., 2019). A first application concerns the storage of renewable electricity in the presence of mean-field price impact and another one focuses on a mean-variance portfolio selection problem with probabilistic constraints on the wealth. We also illustrate our approach for a direct numerical resolution of the primal Markowitz continuous-time problem without relying on duality.

The Cost of Climate Policy to Capital: Evidence from Renewable Portfolio Standards

The Cost of Climate Policy to Capital: Evidence from Renewable Portfolio Standards

Causal Effects of Renewable Portfolio Standards on Renewable Investments and Generation: The Role of Heterogeneity and Dynamics

Causal Effects of Renewable Portfolio Standards on Renewable Investments and Generation: The Role of Heterogeneity and Dynamics

긴급 에너지 자립 섬에서 신재생에너지 연계 ESS의 예비력 공급에 따른 분산전원의 최적용량 산정

In this paper, we introduce a linear programming model to find optimal capacity for distributed power generating units and energy storage systems (ESSs) directly connected to solar photovoltaic systems or wind turbine generators. The ESSs are used to relieve the variability of renewable generators and provide operating reserves. The proposed optimization model minimizes the total annualized cost including construction and operation costs for generators and ESSs. A renewable portfolio standard and carbon dioxide emissions reduction target are applied to the optimization model as environmental policies. To examine the impacts of implementing the environmental policies and providing operating reserves by the ESSs, case studies are conducted, and results are compared. The optimal results obtained from the proposed model show that the total cost is reduced, and installed capacity of fossil-fired generators is smaller compared to when ESSs do not provide operating reserves.

Do green policies produce green jobs?

AbstractObjectiveWe examine the relationship between clean energy policies and green job growth.MethodsUsing a set of meta‐regression analyses, we assess the green job creation performance of a wide variety of policies in the American states.ResultsOur findings indicate that renewable portfolio standards and public benefit funds are systematically associated with increases in green jobs, although the effects of other policy tools are ambiguous at best. Effect estimates in the existing literature are significantly driven by how the dependent and core independent variables are measured.ConclusionOverall, our findings suggest that some policies may be an effective component of an energy‐based economic development strategy, but that for others a more robust evidence base is needed in order to clarify their effects.

The driving forces of U.S. renewable energy consumption—a longitudinal analysis of data from 1997 to 2019

Climate change is a major challenge facing the United States today. Recent years have witnessed a surge of extreme weather events that brought devastating impacts on the economy and environment. One major contributor to climate change is CO2 emissions produced from fossil fuel consumption. Promoting renewable energy is one practical pathway to mitigate these emissions while also meeting energy demands. This study investigates the driving forces of U.S. renewable energy consumption. The data are a balanced panel that includes indicators for 50 states and Washington, DC, from 1997 to 2019. The time-series Prais–Winsten regression is adopted for statistical estimation. Results show that states consume more renewable energy when they have less carbon-intensive economies and suffer more climate change impacts. Also, the renewable portfolio standards represent an effective policy instrument to promote renewable consumption. The findings complement existing literature and carry policy implications. Notably, states become supportive of renewable energy when their economies are less intertwined with fossil fuels and relevant policies are in place to provide incentives for renewables.

Independent Power Producer Approach to Optimal Design and Operation of IES with Wind Power Plants

In South Korea, Renewable Energy Sources (RES) have been increasing with the application of energy policies, such as Feed in Tariff (FIT) and the Renewable Portfolio Standard (RPS). However, a rapid increase in RES supply leads to an uncertain power supply due to the intermittent output of RES. A representative example is the curtailment of Wind Turbines (WT), which frequently occurs in Jeju Island, South Korea. The proportion of RES power on Jeju Island is 67%, and there are cases where WT is curtailed among the operable sections to maintain the balance of power supply and demand. This paper applies Power-to-Gas (P2G) technology to hydrogenate, store, and utilize unused power to solve this problem. In this paper, Aewol-eup in Jeju Island is selected as a target site for case study. An Integrated Energy System (IES) for various energy operations is designed to control RES output. This paper proposes the optimal facility configuration and finally drives the optimal design and operation solution of IES by analyzing the objective functions and focusing on the Independent Power Producer (IPP) perspective.

Fairness-based Bidding Model for Renewable Portfolio Standard Policy in South Korea Standard Policy in South Korea

Fairness-based Bidding Model for Renewable Portfolio Standard Policy in South Korea Standard Policy in South Korea

Impacts of wind power on air quality, premature mortality, and exposure disparities in the United States.

Understanding impacts of renewable energy on air quality and associated human exposures is essential for informing future policy. We estimate the impacts of U.S. wind power on air quality and pollution exposure disparities using hourly data from 2011 to 2017 and detailed atmospheric chemistry modeling. Wind power associated with renewable portfolio standards in 2014 resulted in $2.0 billion in health benefits from improved air quality. A total of 29% and 32% of these health benefits accrued to racial/ethnic minority and low-income populations respectively, below a 2021 target by the Biden administration that 40% of the overall benefits of future federal investments flow to disadvantaged communities. Wind power worsened exposure disparities among racial and income groups in some states but improved them in others. Health benefits could be up to $8.4 billion if displacement of fossil fuel generators prioritized those with higher health damages. However, strategies that maximize total health benefits would not mitigate pollution disparities, suggesting that more targeted measures are needed.

Optimal Bidding Strategy Considering Bilevel Approach and Multistage Process for a Renewable Energy Portfolio Manager Managing RESs With ESS

This article presents a bilevel and multistage framework in whicha renewable energy portfolio manager (REPM) manages renewable energy sources (RESs) integrated with an energy storage system (ESS) to reduce imbalances and joins in the day-ahead market and the balancing market, including bilateral contracts. The total REPM gain is maximized in the upper level, whereas the loss of income of each portfolio participant in the lower level is minimized taking into account the specified income value. In the multistage structure, different decisions are taken regarding energy trade according to the hours of the day. Generations and price uncertainties that need to be addressed in optimum bidding problems are eliminated with a stochastic approach. Besides, risk management is evaluated through the conditional value-at-risk method. Besides, the test is carried out using real data from Spain in order to verify the effectiveness of the proposed model. According to the results obtained from the study, it can be stated that RESs with ESS increase the portfolio profit by 2%, and even in the case of expected generation, it is 4.1%, by better managing the energy imbalance of participants.

A Study on Regulations Mandating Obligation on Renewable Energy in Taiwan

The shift toward renewable energy has become a global trend today. In the past, power producers or the private sector were encouraged to install renewable energy equipment mainly through incentives (e.g., feed-in tariff, tax credits). Some countries also impose “renewable portfolio standards”, which mandate power producers to include RE. However, it is rare to see any mandatory requirements on electricity users anywhere in the world. Since 2018, Taiwan’s government has started to draft the RPS-TW to establish such obligation; but as a new mechanism, the greatest challenge lies in formulating feasible requirements that are apt to Taiwan’s circumstances. This study aimed to assist Taiwan’s government in this effort by formulating content that was feasible and meets external expectations regarding the applicable entities, scope, and methods of fulfillment. Once the draft had been revised accordingly, the public (electricity users, environmental groups, general public) were actively consulted, and the draft was modified and optimized based on widely collected feedback. The regulations were ultimately promulgated on 31 December 2020.

Harnessing the power of environmental flows: Sustaining river ecosystem integrity while increasing energy potential at hydropower dams

Hydropower comprises the largest portion of the world's renewable energy portfolio yet induces significant environmental effects in river and floodplain ecosystems. Many countries are seeking to increase hydropower capacity primarily through the construction of new dams; however, this overlooks the potential energy that can be gained from optimizing existing hydropower infrastructure. Environmental regulatory protocols globally, and especially in the US, require hydropower facilities to provide environmental flows to downstream riverine ecosystems. Most of these facilities, however, fail to capture additional hydropower energy from these releases, such as passing them through smaller turbines. Herein, we conducted a US-wide analysis of the potential additional hydropower capacity and generation that could be available if environmental flows were harnessed for energy. We used two approaches based on availability of information: one reliant on available stream flow data to identify specific optimal turbine sizes, and another using a design-envelope approach, to accommodate situations where flow data was unavailable. Using available historical flow data and plant characteristics from over 200 existing hydropower facilities, the addition of minimum flow turbines could provide up to 730 MW of capacity and generate nearly 1.8 TWh of energy annually. Across the remaining hydropower fleet, the envelope approach suggests there may be anywhere from 12 TWh to 66 TWh of additional energy, supplied from a capacity increase of 2.5 GW–13.5 GW annually. Ultimately, this suggests that uncaptured environmental flows provide anywhere from 4% to 18% potential increase in US hydropower capacity and 4%–24% increase in generation.

The value allocation model of renewable portfolio standards considering the contribution of renewable energy consumption on the demand side

Under China's current Renewable Portfolio Standards (RPS) policy system, the provincial power grid is the assessment subject, and then the assessment is conducted on the user side. However, in the centralized clearing power market, renewable energy (RE) consumption on the user side cannot be accurately identified, so accurate value transmission cannot be formed to guide users to optimize their electricity consumption behavior. To improve this problem, this paper identifies the irreplaceable role of users in RE consumption through time series simulation. We construct a three-layer RPS assessment value transmission model of “power grid company - retailers - users” based on the identified unique contributions of each user. The equilibrium state of multi-market participants is obtained based on the decentralized training framework of reinforcement learning. The following conclusions are drawn through simulation analysis:(1) the user-side RE contribution identification method can effectively identify the user's contribution to RE consumption, which can reduce about 8% or increase about 7.48% of RPS cost allocation according to different contribution degrees; (2) the RPS value allocation mode can optimize users' power consumption behavior, achieve peak shaving and valley filling, promote RE consumption, and reduce about 0.6% of the abandoned wind power; (3) Under the RPS system, the effect of improving the response-ability of the user-side is better than increasing the RPS target and the peak shaving capacity.

Bilevel programming approach for the quantitative analysis of renewable portfolio standards considering the electricity market

Many countries have introduced renewable portfolio standard (RPS) with market systems that allow transactions of renewable energy certificates (RECs) to foster investment in renewable energy (RE). The main objective of this study is to estimate long-term REC prices based on marginal-cost pricing and analyze the RPS system quantitatively. In the proposed method, a mathematical model is constructed as bilevel programming that considers the REC and electricity markets simultaneously, and the KKT conditions are used to solve the nonlinearity of the constructed model. The proposed method has the following advantages: (1) it determines the optimal capacity of RE to implement the RPS system, (2) it derives the long-term marginal cost of the REC market, and (3) it can be used to perform quantitative analyses of the RPS system. Simulation studies were performed in South Korea, and the results indicated that solar photovoltaic accounted for a major portion of the new investment. The marginal cost of the REC market and the impact of the RPS systems on retail electricity prices are estimated to be USD 14.01/REC and USD 4.59/MWh in 2031, respectively (in 2021 USD). Our study provides appropriate price signals to the market participants and serves as a reference for policymakers.