Renewable Portfolio Research Articles

Supply side incentive under the Renewable Portfolio Standards: A perspective of China

Renewable Portfolio Standards (RPS) is a mandatory institutional change to promote low-carbon energy transformation and renewable energy development. Its successful implementation requires the scientific design of relevant incentive mechanisms and rules. To make up for the defects in the current RPS mechanism design and the problems exposed in the Tradable Green Certificate (TGC) market, this paper takes China as an example and uses the system dynamics method to study the supply side incentives. The results show that: (1) Scientific setting the relevant system parameters of RPS (such as quota, benchmark price and penalty) and promoting the electricity market reform will effectively stimulate the power generation and investment on the supply side, and improve manufacturers' profit. (2) Higher quotas and lower benchmark prices can increase the manufacturers' power generation, profit and investment, and stimulate the supply side to conduct TGC transactions. However, when the penalty is set at different multiples of the benchmark price, the incentive effect on supply side power generation, investment and profit differ. (3) Marketed on-grid prices can significantly stimulate the supply side and promote renewable energy development. This paper can provide reference for the design of RPS incentive mechanism and institutional parameters.

How dynamic renewable portfolio standards impact the diffusion of renewable energy in China? A networked evolutionary game analysis

Renewable portfolio standard is an effective administrative tool to guide the behavior of electricity producers and impact the renewable energy diffusion. However, currently the renewable energy quota is generally set to be static and the efficiency is limited. In this paper, we proposed a dynamic renewable portfolio standard policy and we aimed to analyze how it will impact the renewable energy diffusion in China. The connections between electricity producers were simulated under both the perfectly competitive market and monopoly market. And a networked evolutionary game approach is applied considering dynamic linking between the electricity producers. The results show that dynamic quota policy is effective in promoting the proportion of wind power generation from 20% to 59.17% and promoting the proportion of solar power generation from 20% to 79.25%. With the sensitivity analysis, we found that renewable energy quota and the on-grid price are the most influential parameters. The proportion will reach 76.47% if quota is 0.7 and 68.1% if on-grid price is 630 Yuan/MWh. And the influence of tradable green certificate prices and generation cost is limited in promoting renewable energy diffusion. This paper offers the Chinese government a potential implementation for the perfection of national renewable energy diffusion.

A Study on India's Status of Transition Towards a Green Economy

The study represents the status of India in its adoption of green economy and suggestions to address identified gaps. The research is qualitative and quantitative wherein secondary data for green economy growth indicators is obtained from reports of Organization for Economic Co-operation and Development (OECD), World Bank Group, etc. In India, the journey of transition towards a greener economy has commenced. India has obtained membership in Partnership for Action on Green Economy (PAGE). India is making significant progress in areas of environmental policies at national level, enhancement in renewable energy portfolio, improved access to basic services. India has improved in global positions and scores of green growth indexes. India lags in factors including degraded air quality, high greenhouse gas emissions and inefficient waste management. India has progressed but has a long way ahead to achieve its goals and commitments to emerge as a successful green economy.

Green Power Trade Behavior in China’s Renewable Portfolio Standard: An Evolutionary Game-Based System Dynamics Approach

To promote the consumption of renewable energy (RE), in 2019, China introduced the Renewable Portfolio Standard (RPS) and adopted the weight of consumption responsibility to replace the quota index. This paper investigates the behavioral decisions of green power plants and power sales companies using evolutionary game theory. The results show that RPS becomes effective based on two rules: (1) the unit fine is higher than the transaction cost for power sales companies; and (2) the transaction prices of RE and Trade of Green Certificate (TGC) are greater than the unit transaction cost for green power plants. Taking Ningxia Hui Autonomous Region as an example, the scenario analysis method and a simple system dynamics model are employed to investigate the impact of fines on the green power trade behavior. With different fines, power sales companies are more sensitive than green power plants. These results provide some policy recommendations to promote the consumption of RE.

Market-based solution in China to finance the clean from the dirty

Financial incentives play a key role in promoting renewable energy investments that can help China achieve the ‘dual carbon’ goal. The national emissions trading scheme (ETS) and the renewable energy portfolio standard (RPS) are two existing market-based policy instruments that can generate stable expected returns for low-carbon projects. This paper studies the interactive distribution effects of these two market-based instruments. We use the micro-level thermal power plant data to investigate the abatement effects of the national ETS, in which the details show that the existing rate-based ETS will result in higher negative impacts on power units, whose installed capacities are smaller than 400 MW. The interactive distribution effects between the two markets will occur when the permit allocation standards of the national ETS become stricter than the existing ones. Provinces in Eastern China and Northern China will face high pressure on costs in both ETS and RPS markets. When the levels of the permit allocation standards are set as 70% of the existing ones and the carbon price is assumed to be 200 yuan/ton in 2030, the annual market size of the national ETS will be nearly 100 billion yuan, and the annual market size is predicted to be 250 billion yuan. In the existing rate-based national ETS, the China Certified Emission Reduction (CCER) mechanism will have an offsetting effect, which should be taken into serious consideration during the policy-making processes in the future.

A provincial renewable portfolio standards-based distribution strategy for both power plant and user: A case study from Guangdong, China

Renewable portfolio standards have been found to be effective in promoting renewable energy developments; however, in China, the implementation of renewable portfolio standards is not yet fully developed. Based on policy acceptance, generation costs, and renewable power target perspectives, this paper proposes a multi-objective equilibrium model to develop an annual single province power plan. A case study from Guangdong province, China, is presented to demonstrate the practicality and efficiency of the presented model. Comparison analysis with current plans are made, three scenarios which consider the non-hydro renewable targets, market competition and a tougher environmental attitude are designed to adapted to the decision maker's preferences. It was found that: (1) the optimal model reallocated policy costs between power users, distributed the generation capacity between provinces, and could obtain 35.4% renewable electricity and 4.3% of non-hydro renewable electricity consumption in Guangdong; and (2) compared with the current plan, the optimal model effectively maintained power tariffs, decreased generation costs by 2.42%, and decreased Guangdong's electricity generation CO2 emissions by 8.21%. Policy suggestions for provincial governments to better implement provincial renewable portfolio standards are given.

How do carbon cap-and-trade mechanisms and renewable portfolio standards affect renewable energy investment?

In order to promote the low-carbon transformation, Chinese government plans to implement two policies in the power industry: carbon cap-and-trade mechanisms and renewable portfolio standards. However, whether their synergy can drive the development of Chinese renewable energy industry has become a key issue. Based on China’s renewable energy industry, this paper established an optimization model with the objective function for maximizing electricity company profits. The study further employed scenario analysis to design four policy scenarios: no-policy scenario, carbon cap-and-trade mechanisms scenario, renewable portfolio standards scenario and mixed scenario. The mentioned scenarios were used to explore the impact of various policy situations on electricity companies’ investment decisions, total carbon emissions, consumer surplus and social welfare when renewable energy, new conventional energy and conventional energy are available in the market. The research findings obtained thus showed that in terms of renewable energy promotion, mixed scenario is the best. Our results also showed that at the initial stage of China’s low-carbon transformation, the social welfare level under mixed scenario is the highest. The outlined findings provide some policy suggestions for promoting the rapid development of renewable energy and accelerating the low-carbon transformation with high quality.

The Porter Hypothesis in the World of Energy: Renewable Portfolio Standards and Their Effects on Returns for Investor-Owned Utilities

The Porter Hypothesis in the World of Energy: Renewable Portfolio Standards and Their Effects on Returns for Investor-Owned Utilities

Noncooperative multiagent game model for the electricity market on the basis of the renewable energy portfolio standard

AbstractIn China, after the revision of the renewable energy policy, transactions among the main parties involved in the electricity market are becoming increasingly complicated. Nevertheless, the impact of the Renewable Energy Portfolio Standard (RPS) on market equilibrium has not been studied so far. Hence, in this study, a noncooperative multiagent game model for the electricity market was developed on the basis of the recently released RPS and by considering various factors, such as green certificate transactions and the changing of the selling entities. The improved firefly algorithm was used to solve the model, and problematic gaming was analyzed empirically. Once the new RPS is implemented, the price of bound electricity will become higher than that of nonbound electricity, and the trading volume of bound electricity will increase. Because fossil energy producers will no longer be responsible for the electricity quotas, their electricity trading volumes will now be more related to the market demand than they were earlier. Renewable energy companies will increase their revenues by reducing their bound electricity sales. If the RPS increases the electricity quota ratios, the costs incurred by electricity sales companies and large power users will also increase, leading the electricity sales companies to reduce their electricity trading volumes. The study findings will help analyze the impacts of implementing the RPS and provide a basis and a reference for policymakers to make improvements to the standard in the future.

Optimizing the provincial target allocation scheme of renewable portfolio standards in China

Renewable portfolio standards (RPS) is widely regarded as a useful policy tool to steer energy transition. China government has recently released an RPS target allocation scheme to help promote its renewable electricity consumption. Formulating an efficient and equitable RPS target allocation scheme is a vital step to ensure the effectiveness of RPS. In this paper we argue that data envelopment analysis (DEA) can be used to optimize the provincial RPS targets in China from an efficiency perspective. We first evaluate the efficiency of the officially released RPS target allocation scheme and then apply a zero-sum gains DEA model to optimize the scheme. Further, we use the Gini coefficient to verify the merits of the optimized scheme over the official scheme in equity. The results indicate that the renewable electricity consumption responsibility allocated among provinces in the official scheme may suffer efficiency loss. Central, southern, eastern, and southwestern China can obtain more renewable electricity consumption responsibility, while northeastern, northern, and northwestern China should undertake less consumption responsibility. It provides the adjustment direction for RPS targets allocation among provinces which helps optimize the electricity consumption structure.

Decision making on investments in photovoltaic power generation projects based on renewable portfolio standard: Perspective of real option

It is now a main global trend to replace the renewable energy feed-in tariffs (FIT) policy with the renewable portfolio system (RPS) policy in the reform of renewable energy policy systems. To solve the practical problem that the current main studies on the decision making about investments by renewable energy enterprises mainly focus on macroeconomic aspects such as government subsidies, renewable energy FIT and carbon taxes, rather than microeconomic aspects such as RPS and the TGC market's influence, a real option model about photovoltaic power generation projects is established to study these projects' sequential decision making about optimal investment opportunity, optimal installed capacity and phased investment. The result shows that phased investment fruit in much higher investment flexibility, longer economic lives and greater project values, and fewer risks for investors as well; lower technical costs and higher TGC prices help acquire the optimal investment opportunities. The conclusions of this study help make better decision making about investments in photovoltaic power generation projects and, from the microcosmic aspect, prove influence of the RPS policy.

At scale adoption of battery storage technology in Indian power industry: Enablers, frameworks and policies

• We evaluate cost effectiveness of renewable plus battery storage technology over new coal. • We define targets and policy frameworks for scale adoption of battery storage technology in Indian power industry. • Renewable plus battery storage technology cost competitive over new coal power starting 2022. • First study to suggest battery portfolio standard linked to existing renewable portfolio standard. • First study to suggest renewable dispatchable generation power purchase agreement for battery procurement. India's envisages uptake of 450 Giga Watt (GW) of renewable energy capacity by 2030. The resulting system flexibility needs can be met by 50 GW of 4-hour energy storage. However, system flexibility has historically been met by coal power plants, and India also plans to install 50 GW of new coal power capacity during 2022–27. Our paper answers three related questions that would maximize deployment of battery storage with appropriate policy design. First, what is the cost-competitiveness of renewable energy and battery storage compared to new coal-based power? Second, what should be the high-level policy framework for ensuring necessary deployment of battery storage? Third, what should be the appropriate procurement mechanisms for battery storage along with renewable energy? To answer these questions, we first compare forecasted levelized cost of energy for renewable energy and battery storage with coal power, and then use two frameworks to investigate policies. Our findings are as follows. First, renewable energy and battery storage is cost-competitive over new coal starting 2022. Second, India should adopt a battery portfolio standard (BPS) that is linked to existing renewable portfolio standard (RPS). Third, India should adopt the renewable dispatchable generation (RDG) power purchase agreement (PPA) to ensure that multiple policy criteria are met.

Simulating policy interventions for different quota targets of renewable portfolio standard: A combination of evolutionary game and system dynamics approach

The renewable portfolio standard (RPS) is one of the most important policies for China's goals of emission peak and carbon neutralization. Central to advancing RPS is to ensure that stakeholders have the willingness to undertake their respective obligations. As a common instrument for pushing policy forward, policy interventions are frequently used by authorities to motivate and restrain the behaviors of stakeholders. However, it is still unclear how policy interventions under different quota targets affect the behavior strategies of stakeholders involved in RPS. Thus, this paper develops an evolutionary game model considering power sales companies (PSC) and power generation companies (PGC) as the participants. Based on official Chinese statistics and data from previous studies, we employ system dynamics to investigate the impacts of single and dual policy interventions under three quota targets on participants’ behavior strategies. The results indicate that, the evolutionary game always converges to the same evolutionary stable strategy for different initial strategies, and PGC are not as sensitive to quota targets as PSC. In addition, reward or penalty as single policy intervention has diverse impacts on participants, and PSC and PGC behave differently under all the combinations of dual policy interventions. To achieve desired policy goals, government should not only adopt policy interventions according to the stages of RPS implementation and in combination with other policy instruments, but also encourage stakeholders to consciously undertake their respective quota obligations.

Do windy areas have more wind turbines: An empirical analysis of wind installed capacity in Native tribal nations.

The decarbonization of the electricity sector is leading to a substantial increase in the demand for wind energy. Will tribal nations, which account for 7.8% of utility-scale wind capacity, benefit from this policy shift? To examine why tribal nations vary in translating wind energy potential into wind installed capacity, we have constructed an original dataset of the potential as well as the location of wind turbines across tribal nations. Our statistical analysis of 286 tribal nations suggests that wind energy potential is not associated with wind installed capacity. Instead, casino square footage, a proxy for tribal nation’s administrative capacity and business acumen, is associated with wind installed capacity. Political orientation plays a role as well: tribal nations are more likely to have wind installed capacity when they value tribal sovereignty. While tribes suffering from natural disasters do not install more wind turbines, those receiving federal grants for wind energy projects, and located in states that already have a substantial number of wind turbines, are more apt to have wind turbines. Surprisingly, tribes located in states with renewable portfolio standards do not show an association with installed wind turbines capacity.

Wind Microgeneration Strategy for Meeting California’s Carbon Neutral Grid Goal

As California’s Renewables Portfolio Standard continues to phase power production from fossil fuels, carbon neutral sources will need to be implemented. This sets small-scale wind production and battery storage in a position to integrate into current grid infrastructure as means of production. This would be an “E Pluribus Unum” approach where many decentralized small production and storage units would act in combination to provide a stable grid. This is often referred to as distributed generation (DG). By distributing the grid’s production in this manner and designating predetermined regional hubs for control (in the event of a fractured grid due to natural disaster), the state and its residents will be able to maintain power for critical infrastructure and basic utilities. This work presents, in detail, a sustainable plan for achieving carbon neutral Californian grid by 2045.

Research on Capacity Allocation Optimization of Commercial Virtual Power Plant (CVPP)

Commercial virtual power plants (CVPP) connect the form of renewable energy resource portfolio to the power market and reduce the risk of the unstable operation of a single renewable energy. Combining different kinds of large-scale renewable energy in CVPP to provide capacity services like base load, peak shaving, and valley-filling, etc., for the system loads is an urgent problem to be solved. Therefore, it is valuable to analyze the capacity allocation ratio of the CVPP to maximize the utilization of all kinds of energy, especially for the large-scale multi-energy base. This paper proposed a multi-energy coordinated operation framework by considering various load demands, including base load and peak shaving for the capacity allocation of CVPP based on the world’s largest renewable energy resource base on the upstream area of the Yellow River. The main procedures of this framework are as follows: (1) A paratactic model satisfying base load and peak shaving is proposed to determine the ability of the CVPP operation model’s capacity services to meet the different demands of the power system load. (2) A hybrid dimension reduction algorithm with a better convergence rate and optimization effect solves the proposed paratactic model based on the ReliefF and the Adaptive Particle Swarm Optimization (APSO). The results show that the large-scale CVPP with different compositions can achieve both of the goals of a stable base load output and stable residual load under different weather conditions. Compared with the operation on sunny days, the base load fluctuation and residual load fluctuation of CVPP on rainy days are reduced by 14.5% and 21.9%, respectively, proving that CVPP can alleviate renewable energy’s dependence on weather and improve energy utilization.

Medium and long-term electricity market trading strategy considering renewable portfolio standard in the transitional period of electricity market reform in Jiangsu, China

The Energy Consumption Guarantee Mechanism (ECGM) of renewable energy requires the prior consumption ratio of renewable energy, and regulates the proportion of renewable energy power in each province. The implementation of Renewable Portfolio Standard (RPS) will have a great impact on the energy portfolio management and trading strategy of electricity in the medium and long-term electricity market. Grid companies (or power exchange center), as the organizers of the medium and long-term market and the primary entities responsible for renewable energy consumption, need a set of scientific trading strategies for the overall scheduling of inter- and intra-provincial power exchange arrangements. Firstly, based on the medium and long-term power market trading rules of Jiangsu, China, this paper analyzes the risk of uncertainty in the power output of renewable energy, and introduces the optimization model into the cost of risk to schedule the consumption ratio of renewable energy in the province, namely arranging the amount of renewable and non-renewable energy electricity as well as that of electricity outside the province. Secondly, the risk levels and their response are determined, and the electricity arrangements inside and outside the province in the medium and long-term market are updated based on a time window rolling method and the proposed mechanism. Finally, illustrative cases are performed to verify the effectiveness of the model and to provide a reference for the organizers' decision-making of medium and long-term power exchange.

How can the cost and effectiveness of renewable portfolio standards be coordinated? Incentive mechanism design from the coevolution perspective

Renewable portfolio standards are essential means to promote the transition to low-carbon energy by encouraging obligated subjects to purchase tradable green certificates. However, the trade-off between Renewable portfolio standards' cost and effectiveness is a challenge for the government, because they want to support the development of renewable energy at the lowest cost. This paper constructs a coevolution model for a renewable energy system incorporating Renewable portfolio standards to explore how incentive mechanisms impact the cost and effectiveness of Renewable portfolio standards. The simulation results show that with the coevolution of the RE system, Renewable portfolio standards' effectiveness gradually rises; concurrently, its cost increases first before later decreasing. However, the path-dependence of the behavioural evolution of the tradable green certificate market players hinders further improvements in Renewable portfolio standards' cost-effectiveness. In addition, high quotas and price collars close to TGC value improve the cost-effectiveness, whilst the sloped penalty mechanisms, banking mechanisms with a valid period longer than one year, and borrowing mechanisms significantly reduce costs. On this basis, the government can design dynamic incentive mechanisms to guide the market players’ behavioural evolution and decrease costs whilst also ensuring effectiveness.

Whether feed-in tariff can be effectively replaced or not? An integrated analysis of renewable portfolio standards and green certificate trading

Nowdays, both the renewable portfolio standards and the green certificate trading policy have become the critical renewable energy policies for supporting the photovoltaic power generation firms. Whether the above emerging policies can effectively replace the feed-in tariff policy or not has become a key issue for China. To explore this problem, this paper establishes an evolutionary game model to analyze the impact of photovoltaic policies on government and photovoltaic power generation firms, and constructs a system dynamics model to simulate the evolution results according to different scenarios of game strategies and photovoltaic policies. According to the study's evolution and simulation analysis, the following implications can be obtained. (1) The renewable portfolio standards policy has significant advantages over the feed-in tariff policy according to the photovoltaic development, but its incentive measures still need to be promoted to reduce the time lag in the policy response of most photovoltaic firms. (2) The initial willingness of stakeholders and the subsidy price have a significant impact on the trading volume of tradable green certificates, but the social welfare of photovoltaic firms is mainly related to the subsidy price. (3) The total amount of government cash subsidy is smaller than the social effect, is the prerequisite of obtaining the appropriate renewable energy support policy for promoting both the photovoltaic development and the economic growth.

Optimal strategy of investing in solar energy for meeting the renewable portfolio standard requirement in America

Renewable portfolio standard (RPS) is a legislative requirement for regulating the utility to increase the output of renewable energy, however, it’s not easy for the government to optimally design the target. To address this problem, this study investigates solar investing problems by theoretically investigating a novel game model. To meet the RPS requirement, the utility has to procure not only traditional energy but also solar energy. This paper aims to capture all the frictions among the stakeholders including the regulator, the utility and also a photovoltaic (PV) developer. The results show that the regulator can benefit from the strategy with higher RPS requirements if there is less resistance to regulation and a high penalty rate. Besides, the development of solar technology will increase the optimal PV panel price and investment in solar. Given a high requirement of renewable output, it’s better off to increase the solar investment for more green output. This study also finds the developer enjoys a high requirement because it promotes the PV adoption and increases the panel price as well. Additionally, a dynamic system was developed to study the players’ long-term behavior as well. The stable region and optimal strategy of behavior have been figured out. Interestingly, for the developer and the utility, a salutation of profit regarding the raising of the regulator’s adjusting speed of decision is observed. Highlights Study a novel problem of solar investment. Capture the frictions among the stakeholders under the Renewable Portfolio Standard regulation. Reveal the optimal strategy for the players. Investigate the players’ behavior in long term operations. Observe profit ramping phenomena for the developer and utility.