Renewable Portfolio Standards Research Articles

Renewable energy expansion: Legal strategies for overcoming regulatory barriers and promoting innovation

The expansion of renewable energy sources is pivotal in mitigating climate change and transitioning towards a sustainable energy future. However, the realization of this transition faces numerous regulatory barriers that impede the deployment and integration of renewable energy technologies. This abstract explores the legal strategies essential for overcoming these barriers and promoting innovation in renewable energy expansion. Regulatory hurdles often stem from outdated policies, complex permitting processes, and conflicting regulations at various governmental levels. Moreover, legal uncertainties surrounding property rights, land use, and interconnection standards pose significant challenges to renewable energy developers and investors. To address these barriers, legal frameworks must evolve to accommodate the unique characteristics and requirements of renewable energy projects. Effective legal strategies encompass a range of interventions, including streamlining permitting procedures, harmonizing regulations across jurisdictions, and providing clarity on legal and contractual frameworks. Furthermore, innovative policy mechanisms such as feed-in tariffs, renewable portfolio standards, and tax incentives can incentivize renewable energy deployment while ensuring regulatory compliance. Promoting innovation in renewable energy expansion requires a proactive approach to legal and regulatory reform. This involves fostering collaboration between policymakers, industry stakeholders, and legal experts to identify regulatory bottlenecks and develop tailored solutions. Additionally, flexible regulatory frameworks that allow for experimentation and adaptation to technological advancements are essential for driving innovation in the renewable energy sector. Case studies from various jurisdictions illustrate successful legal strategies employed to overcome regulatory barriers and promote innovation in renewable energy expansion. These examples highlight the importance of proactive policy interventions, stakeholder engagement, and adaptive governance structures in facilitating the transition to a renewable energy economy. In conclusion, overcoming regulatory barriers and promoting innovation in renewable energy expansion requires a multifaceted approach that combines legal, policy, and technological solutions. By adopting proactive legal strategies, policymakers can create an enabling environment that fosters renewable energy deployment, accelerates innovation, and advances the transition towards a sustainable energy future. Keywords: Legal Strategies, Promoting Innovation, Regulatory Barriers, Renewable Energy, Overcoming.

Transition towards a hybrid energy system: Combined effects of renewable portfolio standards and carbon emission trading

A hybrid energy system (HES) utilizing complementary energy sources allows for high-quality development of renewables. It is a viable pathway in achieving the low-carbon transition of the power sector. Both Renewable Portfolio Standards (RPS) and Carbon Emission Trading (CET) regulate the low-carbon behavior of conventional power enterprises. This highlights the importance of investigating how the policy mix can drive the transition towards hybrid power generation. This paper develops an evolutionary game between local governments and power enterprises to explore the influence of policy-related parameters on the transition to a hybrid energy system. We find that implementing the policy mix is imperative to the transition when the technology cost of a hybrid energy system is not competitive. Power enterprises can control investment costs through the structure of multi-energy power generation, but are also limited by the lack of renewable absorption capacity. We also find an additive effect between RPS and CET, albeit with differences. Raising the price of tradeable green power certificates (TGC) can effectively facilitate the transition under either a single RPS policy or the policy mix. Reducing initial carbon permits makes sense only under the policy mix. Moreover, the coordinated implementation of multiple policies can contribute to the transition more efficiently, but it deserves attention to avoiding policy redundancy.

A Multi-Stage Approach to Assessing the Echo-Tech Feasibility of a Hybrid SAM-CREST Model for Solar PV Power Plants in Maryland, USA

Maryland is actively working towards doubling its Renewable Portfolio Standard (RPS) target, aiming to increase the share of renewable energy from 25% by 2020 to 50% by 2030. Furthermore, Maryland stands out as a state that strongly supports solar initiatives, offering incentives and specialized programs to assist residents in adopting solar energy solutions. The paper presents a multi-stage approach: Stage 1—Location Selection Process, Stage 2—Technical Feasibility Study, and Stage 3—Economical Feasibility Study. In Stage 1, the study focuses on three potential solar farm locations in Maryland: Westover, Princess Anne, and Eden. Stages 2 and 3 involve a feasibility assessment with detailed technical analysis using the NREL System Advisor Model (SAM) and PVWatts to determine monthly power to the grid and Energy Yield. Subsequently, economic feasibility is assessed using the NREL Clean Renewable Energy Estimation Simulation Tool (CREST), focusing on competitive levelized costs of energy (LCOE), payback time, and cumulative cash flows. Results indicate that all three locations exhibit promising solar irradiance levels, system outputs, and potential energy yields. Due to high solar irradiation, the Westover area has the highest energy yield at 1583.13 kWh/kW, while Princess Anne boasts the highest system output at 333.59 GWh. The economic evaluation suggests that all three locations become profitable within a two-year payback time, with competitive levelized costs of energy (LCOE). Westover emerges as the most cost-effective option at 5.99 cents/kWh, attributed to its higher solar irradiation values and energy yield compared to Princess Anne and Eden. Cumulative cash flows provide insights into long-term profitability, with Princess Anne, MD, having the highest Cumulative Cash Flow over 25 years at $183,383,304. By evaluating technical and economic aspects, this feasibility study offers quantitative insights to guide decision-making for the installation of Solar PV, considering both technological and economic feasibility.

Data‐driven allocation of renewables quota among regional power industries under the policy of renewable electricity standard

AbstractChina is struggling to facilitate the application of renewable portfolio standards to realize sustainable economic growth. As such, improving the current distribution mechanism is crucial. In this paper, the context‐dependent data envelopment analysis and multi‐objective linear programming are combined to allocate the renewables quota for each province. This integrated approach can maximize total electricity generation while minimizing the total CO2 emission with considering the disparity of production technology level. Then, the extended Gini coefficient is employed to assess the fairness of new quota mechanism. We find that (1) the eastern region is the most efficient during the power generation process. During 2016–2019, the efficiency in the western region presents an upward trend. (2) The allocation results indicate that Inner Mongolia and Qinghai have the greatest pressure to absorb renewable energy electricity, while Guangdong and Guizhou can instead reduce the most. Shandong and Inner Mongolia face the greatest burden in conserving non‐renewable electricity. (3) Compared to 2020, the newly allocated scheme can mitigate inequality, with the Gini coefficient changing from 0.264 in 2020 to 0.248 after the allocation. Meanwhile, the reallocation reduces the Gini coefficient related to renewable electricity, non‐renewable electricity, and CO2 emissions by 0.003, 0.028, and 0.073, respectively at the 2020 level.

A cooperative interprovincial management model under renewable portfolio standard policy accounting for employment factors

The vigorous development of renewable energy (RE) is the key to mitigating climate change, realizing energy transformation and thereby guaranteeing energy security. China formally implemented the renewable portfolio standard (RPS) in 2019 and has made certain advances, however, the spatial reverse distribution of RE supply and power consumption center and interprovincial barriers hinder the further development of the RPS. Therefore, this study considers the quota completion cost and employment factors comprehensively to construct a cooperative interprovincial management model (CIMM) of the RPS and address the interprovincial barriers while giving full play to provincial advantages. The minimum cost residual saving method is used to apportion the cooperation cost reasonably. Beijing, Hebei, Inner Mongolia and Shandong are taken as case provinces to verify the model. The result shows that, compared to the territorial management model, the CIMM increases RE generation by 19.58% and employment creation by 19.19% and lowers quota completion costs by 3.84%. A sensitivity analysis verified the robustness of the model. This study provides a scientific interprovincial cooperation model and cost distribution method for the central government to realize the efficient utilization of RE, and promote the further development of RE. Finally, policy recommendations to promote RE cooperation are proposed.

The impacts of local wind power objection on the power system of the Midcontinent Independent System Operator area

Using the Regional Energy Deployment System (ReEDS) model, we estimate the deadweight loss imposed by county-level wind power development restrictions in the form of increased electricity costs due to suboptimal siting. This is accomplished by optimizing the power system of the United States' Midcontinent Independent System Operator (MISO) from 2020 to 2050. We perform the optimization with and without land-use constraints arising from simulated potential local ordinances restricting wind power development, and under multiple scenarios reflecting different renewable portfolio standards (RPS). We find that local restrictions on wind power increase the total system cost by 0.15%–0.3% and the wholesale electricity price by 1.8%–2.7%, depending on the RPS scenario. Changes in the generation and installed capacity mixes are more substantial and depend on both the level of county restrictions on wind power, and RPS requirements, thus indicating an interaction between RPS requirements and local wind power restrictions. We also find that plausible restrictions on wind development do not pose major barriers to meeting renewable energy targets in a cost-effective manner.

Economy-equity equilibrium based bi-level provincial renewable portfolio standard target allocation: Perspective from China

Renewable portfolio standards (RPS) are policy tools used in many countries to promote the use of renewable energy. However, balancing the equity and costs of RPS target allocations is very difficult. Therefore, this study proposed a bi-level framework to characterize this dilemma, in which the upper-level government, as the RPS target allocator, focuses on policy equity and maximizing global renewable energy utilization, and the lower-level government, as the policy implementer, considers the costs to achieve the RPS target. Only when the two types of decision-makers fully interact can they establish economical and equitable goals for a successful implementation. The bi-level mathematical model uses responsibility, capacity, and equality principles to measure equity and optimize the RPS target allocations. The proposed approach was applied to a Chinese case, from which it was found that the inclusion of hydropower in the RPS targets made equitable allocations more challenging, and equitable RPS target allocations have higher costs. Besides, central governments can determine equity principle weights to encourage greater renewable energy generation.

Renewable Portfolio Standards, Vertical Structure, and Investment

Renewable Portfolio Standards, Vertical Structure, and Investment

Research on Bidding Model of Electricity Selling Company Considering Green Certificate Trading and Electricity Selling Blocking

This article considers the optimal bidding model of traditional thermal power generation companies’ electricity sales companies, taking into account transmission congestion, under the influence of new policies such as the renewable portfolio standard (RPS) and the renewable exchange certificate (REC). Firstly, the transaction cost of green certificates is included in the cost of electricity sales, and an optimization model is established with the goal of maximizing the profit of the electricity sales company; Secondly, the node electricity price method is used to manage transmission congestion, and an optimization model is established with the goal of minimizing the cost of transmission congestion; Finally, multi agent technology and dynamic game theory are used to solve the optimal bidding strategy of the electricity selling company.

Can green certificates substitute for renewable electricity subsidies? A Chinese experience

While Feed-in-Tariffs (FIT) promote the growth of renewable electricity, they also impose heavy financial burdens on the government, thus leading to a shift from FIT to the Renewable Portfolio Standard (RPS) mechanism with Tradable Green certificates (TGC). Examining the pricing of green certificates from the perspective of supply and demand is the key to understanding their price changes and the basis for analyzing whether they can substitute for subsidies. However, there are few studies on the pricing mechanism of green certificates. To understand the efficiency of green certificate substitution for government subsidies, we study the green certificates market in China as an example. Firstly, we examine the factors affecting the supply of and demand for green certificates under the co-existence of FIT and RPS and study the pricing mechanism of the green certificates. Then we establish the price model to forecast the price of green certificates in China. Finally, we calculate the substitution efficiency of green certificates for subsidies in China from 2023 to 2025. The results show that in 2025, the price of China's green certificates will not exceed 246.8 CNY per certificate, and the substitution efficiency of green certificates for subsidies will be 41.8 %.

Developing a new flexibility-oriented model for generation expansion planning studies of renewable-based energy systems

This paper presents a flexibility-oriented generation expansion planning (GEP) model with the goal of increasing renewable energy penetration. The model incorporates GEP and unit commitment while considering improved reserve requirements. Utilizing GEP and unit commitment results in considering short-term operational constraints. Furthermore, given the increase in renewable portfolio standards (RPS) and the need for accurate reserve requirements determination, it is essential to consider improved reserve requirements in the proposed model. Moreover, this model utilizes a metric that measures power system flexibility deficiency and leads to flexible power system expansion by integrating it into the objective function. The flexibility-oriented GEP model is developed using mixed-integer linear programming and applied to a scaled-sized case study representing the national power system of Iran with a twenty-year planning horizon. The results show that neglecting improved reserve requirements leads to plans short on flexibility, and considering these requirements substantially declines the upward flexibility violation costs by 68% under the base scenario and 87% under increasing non-hydro RPS scenario. Furthermore, using the flexibility metric coupled with improved reserve requirements changes the optimal path for power system expansion and reduces the risk of flexibility deficiency. Also, increasing RPS by 35% would strongly depend on developing fast-response dispatchable generation units in the years before renewable energy resources expansion; however it doesn’t impose a significant extra cost of planning and the total cost will increase just by 9.43%.

Hybrid renewable energy source optimization using black widow optimization techniques with uncertainty constraints

To encourage the growth and use of renewable energy such as PV Solar Energy, Wind Energy, India is speeding up the creation of a renewable portfolio standard. Scheduling practises for thermal power and other renewable energy producers in the electric power system will shift as a result of the adoption of the standard and accompanying marketable green credits. In this study, we develop a dynamic economic emission dispatch model for wind, solar, and hydro power under tradable green certificates, taking into account many objectives simultaneously. The drive to transition towards cleaner and more sustainable energy sources has underscored the significance of optimizing hybrid renewable energy systems. This study presents a novel approach that leverages the Black Widow Optimization (BWO) algorithm to address the challenges of optimizing such systems while accounting for uncertainty constraints. The core problem revolves around the effective integration and management of multiple renewable energy sources, including solar, wind, and hydro, within a framework that ensures robustness and adaptability. In the face of variable weather conditions and equipment reliability uncertainties, the BWO algorithm excels in balancing exploration and exploitation to yield optimal solutions. Through rigorous modelling and sensitivity analysis, this study provides quantitative insights into the system's performance, offering a clear understanding of the trade-offs between cost-effectiveness and reliability. Real-world case studies validate the practicality of the proposed approach, underlining its importance in achieving sustainable and resilient energy systems. This study's goal is to minimise the yearly cost of operating a hybrid wind-solar renewable energy system to meet a specified load. The objective was to minimise the yearly cost of the system by selecting the optimal level of system components to meet the required load in an efficient and cost-effective manner. Several computational strategies inspired by nature, such as Black Widow Optimization (BWO), were used to maximise fitness. The fitness function and the techniques used to create it where both coded in MATLAB.

Electric utility plans are consistent with Renewable Portfolio Standards and Clean Energy Standards in most US states

Electric utility plans are consistent with Renewable Portfolio Standards and Clean Energy Standards in most US states

How to promote the trading in China's green electricity market? Based on environmental perceptions, renewable portfolio standard and subsidies

The behavior evolution of market players is crucial to promoting green electricity trading. This paper develops an evolutionary game model of China's green electricity market to analyze the strategic interactions among players. The model incorporates key variables such as renewable energy subsidies, renewable energy quotas, and environmental perceptions. Then, a system dynamics simulation model is constructed, and simulation experiments are designed to reveal the influence of key factors on the evolutionary path. The results indicate that: (1) Players exhibit varying sensitivities to green electricity prices under different trading modes. (2) Renewable energy projects with high subsidy intensity have no willingness to enter the market if the benefits of participating in the green electricity market cannot surpass subsidies. (3) The evolutionary stabilization trend depends on users' environmental perceptions, and the environmental perception effect exhibits a diminishing marginal trend. (4) The implementation of renewable portfolio standard is an effective way to promote green electricity trading, especially when there is a high green electricity premium. (5) There is a trade-off between low incentive participation and high incentive coefficients in the system. These findings provide valuable policy recommendations for effectively promoting green electricity trading in China.

A bi-level dispatch optimization of multi-microgrid considering green electricity consumption willingness under renewable portfolio standard policy

Under the policy of renewable portfolio standard (RPS), many microgrid (MG) users with high electricity consumption are installed with renewable energy (RE) generation devices to complete their RE consumption responsibility and reduce carbon emissions. In view of the conflict between the goals of microgrid operators (MGO) and MG users, it is a challenge to achieve economic optimization for both MGO and MG users at the same time when they participate in system dispatch and complete RE consumption responsibility. Therefore, this paper proposes a bi-level noncooperative dispatch strategy that takes into account user satisfaction and RE consumption willingness. In this bi-level model, the upper level is led by an MGO who decides electricity retail prices, while the lower level is followed by MG users who participate in demand response (DR) and change electricity purchase strategies. First, a novel comprehensive evaluation model is formulated to evaluate users' willingness to consume green electricity. Based on this, users' consumption behavior of green and thermal electricity is modeled independently not only in electricity trading but also in power dispatching. Second, optimization objectives are established with the goal of maximizing MG users' welfare, including user satisfaction improvement and energy purchase cost reduction, as well as maximizing the revenue of the MGO. Then, a Stackelberg game model is constructed, and a differential evolution algorithm nested CPLEX is used to solve the Stackelberg game problem of balancing the interests of both parties. Finally, our simulation analysis shows that under the dispatch strategy in this paper, load peak-valley difference is reduced. In addition, when the green electricity generated within the system is sufficient, based on a high level of users' willingness to consume green electricity, the total consumption of green electricity is increased by 29.5% and the overall welfare of users is increased by 0.75%.

Blockchain-Based Renewable Energy Certificate Trade for Low-Carbon Community of Active Energy Agents

The future distribution grid is a peer-to-peer (P2P) community formed by a large number of active energy agents (AEAs), and renewable energy certificate (REC) trading is an efficient way to realize a low-carbon AEA community. AEAs can trade not only electricity but also RECs among themselves to economically and efficiently meet the renewable portfolio standard (RPS) requirements. Aiming to lower the market barrier and increase the trading benefits for market participants, this paper proposes a blockchain-based renewable energy certificate (BCREC) that supports divisible and multiple transactions. The trade process includes four stages: setup, pre-transaction, transaction, and post-transaction. A scheme based on blockchain oracles and smart contracts is implemented to achieve decentralized BCREC issuance and transaction and to support a more flexible trading market. By exploring two typical market scenarios, we verify the advantages of BCREC trading and evaluate its impacts on AEA profits and market efficiency.

Impact of carbon emission trading and renewable energy development policy on the sustainability of electricity market: A stackelberg game analysis

Optimizing the electricity structure and achieving sustainable development are critical objectives in the current electricity market. To facilitate a low-carbon transition, China is planning to implement renewable energy development policies based on carbon emissions trading (CET), which includes feed-in premiums (FIP), renewable portfolio standards (RPS), and their corresponding green certificate trading mechanisms. However, it remains to be seen how these policies will work together to promote the growth and adoption of renewable energy sources in China. Accordingly, this paper aims to establish a Stackelberg game model of the electricity market under the two types of combination policy scenarios of CET-FIP and CET-RPS and compare the influence of different combination policies on the development of the renewable energy industry. The results show that: (1) Compared with a single renewable energy development policy, CET-RPS and CET-FIP policies can effectively reduce carbon emissions. (2) In the long run, the CET-RPS policy has a stronger ability to reduce emissions, and the CET-FIP policy has stronger economic benefits. (3) In the early stage of renewable energy development, electricity generation, profit of power generation companies, and social welfare are higher under the CET-RPS policy, while in the mature stage of renewable energy development, these important performance indices become better under the CET-FIP policy. (4) Under the CET-RPS policy, an increase in carbon price will result in an increase in on-grid price and a decrease in green certificate price. In contrast, under the CET-FIP policy, an increase in carbon price will lead to an increase in on-grid price and premium subsidy.

A global‐scale study on decision making in renewable energy policy: Internal and external factors driving the adoption of Feed‐in Tariffs and Renewable Portfolio Standards

AbstractTo accelerate the clean energy transition, it is necessary to better understand the global policy dynamics and motivations behind clean energy policy adoptions and diffusion. This article examines the differential roles of internal and external diffusion factors on decisions to adopt renewable energy policies, that is, Feed‐In Tariffs (FIT) and Renewable Portfolio Standards (RPS), employing a unique blend of cluster analysis and event history analysis. Cluster analysis uncovers a dichotomy in adopting countries. First, early adopters emerge as high‐income, democratic countries, mostly energy importers with high CO2 emissions, with OECD and EU membership. Conversely, the second cluster consists of adopters from middle‐income, non‐OECD, and non‐EU nations with lower CO2 emissions. Strikingly, these clusters align with UNFCCC party classifications, underscoring the pivotal role of international agreements. Event history analysis suggests that especially environmental pressure, but also democratic governance and economic development are important when adopting renewable energy policies. Interestingly, environmental endowments seem to be less important. These findings lead to an important question: Are the requisite policy tools readily available to navigate diverse socio‐economic, political, and environmental landscapes, and are they deployed in a timely fashion? Beyond these findings, the study also shows that policy diffusion especially through normative emulation and social learning—operationalized as political globalization, OECD member and following regional neighbors—are important for policy adoption, suggesting the importance of such tools for promoting policies. Moreover, distinctive factors come into play when examining the adoption of FIT versus RPS policies, emphasizing the need for nuanced policy approaches.

Climate change, costs, or jobs: How policymakers frame state clean energy laws

Renewable portfolio standard (RPS) laws are among the most important climate change policies, requiring a minimum percentage of electricity from clean energy sources. From 2015–2022 in the U.S., eleven states enacted 100 % RPS laws and seven others strengthened their targets. This study examines the issue framing behind these recent RPS laws, which reflects and affects the political context surrounding the policies, people's views, and support among stakeholders. Through coding of policy documents, the study evaluates how policymakers have framed the policies, differences in framing between states with 100 % and non-100 % RPS targets, and variation in framing connected with political party and partisan votes. Surprisingly, given recommendations in the literature to downplay climate issues and emphasize economics, lawmakers predominantly framed 100 % clean energy laws based on climate change. Policymakers that adopted non-100 % RPS laws utilized less climate framing and garnered more Republican Party legislator votes. The results indicate a distinction in framing between more modest and ambitious climate policies, raising a question about the applicability of recommendations urging minimization of climate messaging to transformative climate and clean energy policy efforts. Depending on political conditions, climate framing may be effective for ambitious energy approaches.

Competitive Equilibrium Analysis of Power Generation Transaction Subjects Considering Tradable Green Certificates

The implementation of renewable portfolio standards (RPS) and tradable green certificate schemes will exert significant influences on the market equilibrium outcomes and generation firms’ strategic behaviors. To quantitatively investigate these influences, firstly, considering the difference in power generation cost and the uncertainty of renewable energy power generation, the equilibrium model for various trade subjects in the electricity market is established. Secondly, the nondominated sorting genetic algorithm II is adopted for solving the equilibrium model to find well-distributed Pareto-optimal solutions. Finally, the grey relational projection method is used to calculate the priority membership of each decision-making scheme so as to determine the optimal compromise solution. The simulation focuses on analyzing the impact of RPS on the equilibrium results and market behavior of power generators and introduces the Lerner index to quantify the market power of generators. The results show that: (1) An increase in the quota ratio can effectively increase power generation in renewable energy generators. The game between thermal power generators and renewable energy generators raises the prices of both markets at the same time. (2) Improving the forecasting accuracy is conducive to alleviating the market power behavior of various power generators, thereby ensuring the healthy operation of the power market.