Renewable energy investment and carbon emissions under cap-and-trade mechanisms

Chen, Wei; Chen, Jing; Ma, Yong

doi:10.1016/j.jclepro.2020.123341

Cited by 87 publications

(31 citation statements)

References 36 publications

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“…[29] discussed the impact of renewable portfolio standard on renewable energy investment, and they found that strict renewable portfolio standard can encourage electricity-generator to invest in more renewable energy. [4] studied renewable energy investment under different cap-and-trade policy using the theory of optimization, and they found that the benchmark policy is better than the grandfather policy for renewable energy investment. [1] focused on the trade-off between renewable energy and non-renewable energy investment using the theory of optimization, and they find that carbon tax increases the value of renewable energy, while increasing carbon price may hinder renewable energy investment.…”

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confidence: 99%

Investment strategy for renewable energy and electricity service quality under different power structures

Chen

Fan

et al. 2023

JIMO

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<p style='text-indent:20px;'>This paper investigates and develops an electricity supply chain with an electricity generator and electricity retailer. The electricity generator invests in renewable energy and sells the electricity to the electricity retailer; the retailer then sells the electricity to consumers according to electricity service quality. Three models are considered: the vertical Nash game, the electricity-generator Stackelberg model, and the electricity-retailer Stackelberg model. Finally, the optimal solutions under different power-structure models are compared. Certain conclusions can be drawn from the findings: (1) the highest electricity service quality and renewable energy investment are obtained in the vertical Nash game model, the electricity generator obtains more profits in the electricity-generator Stackelberg model, and the electricity retailer obtains more profits in the electricity-retailer Stackelberg model. (2) The investment in renewable energy in the electricity-generator Stackelberg model is less than that in the electricity-retailer Stackelberg model, and the investment in electricity service quality in the electricity-retailer Stackelberg model is less than that in the electricity-generator Stackelberg model (under certain conditions). (3) Both increasing the electricity service quality sensitivity and renewable energy sensitivity could increase the optimal electricity price, electricity demand, electricity service quality, renewable energy investment, and supply-chain enterprises' profit.</p>

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confidence: 99%

Investment strategy for renewable energy and electricity service quality under different power structures

Chen

Fan

et al. 2023

JIMO

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“…;2) the influence of RPS system on the strategic behavior of power producers. W.Chen et al examined the impacts of cap-and-trade mechanisms on the decisions of a utility firm when it invests in renewable energy and has an existing conventional energy source [8]. X.Yu established system dynamic simulation model and scenario design method to improve sustainable development of Chinese power industry considering the integration impact of the green certificate market and the carbon emissions trading market [9].…”

Section: Figure 1 Rps and Tgc Mechanisms In Chinamentioning

confidence: 99%

Joint Optimization of Quota Policy Design and Electric Market Behavior Based on Renewable Portfolio Standard in China

Liu

Wang

et al. 2021

IEEE Access

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Under the perspective of carbon neutrality, the green electricity absorption target constrained by the quota system policy plays a crucial role in reducing the carbon emission of the power industry. However, the current green certificate policy has not achieved good results. On the premise of reducing the additional market burden as much as possible, the policy parameters should take into account the influence of market behavior to formulate better policy parameters in line with China's carbon emission peak goal. This paper constructs a combined hierarchical reinforcement learning with off-policy correction and multiagent deep deterministic policy gradient algorithm (HIRO-MADDPG). It realizes the benefit analysis of the existing policy parameters joint with the solution of the optimal policy parameters. The algorithm solves the problem that benefit analysis and parameter formulation cannot be jointly trained and improves the precision. The results indicate:(1)HIRO-MADDPG algorithm can reach the highest policy benefits on the premise of maintaining market fairness.(2)Under the new optimal policy parameters, the income per kilowatt hour of thermal power generator(TPG) and renewable power generator(RPG) can be maintained at 10% under the condition of abolishing subsidies.(3)With the help of the new policy parameters, China's power sector will reach the peak of carbon emissions from coal-fired power plants in 2026 ahead of schedule, and reduce carbon emissions by a further 11% by 2030.

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“…The power balance by bus is represented in (10). The sum of power output and the entering transmitted power must be equal to the storage power, leaving transmitted power, and consumed power.…”

Section: Power Transmissionmentioning

confidence: 99%

“…In Ref. 10, the presented work studies the decisions of a monopolistic company that invests in the renewable sector by using a called a cap-and-trade method. Besides, authors of 11,12 present a review of many approaches implementing to expand electric grids.…”

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A multi‐objective model for the analysis of investments to achieve an electricity cleaner production. The case of the Argentinean system

Alvarez

2021

Env Prog and Sustain Energy

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The electric power systems are in a transition to forms of generation that achieve cleaner production. In this regard, a new multi-objective model that helps with the problem of cleaner production investments is presented. The model can obtain convenient solutions where actors with opposed interests are participating. The novelty is the model considers more points of view than the classical approaches of the literature, which only consider a maximum of two actors involved in this field (the new model considers investment costs, greenhouse emissions, and operating costs).Another key contribution is that the real procedures of the generation and transmission stages and the dependences between electrical-natural gas systems are carefully represented and included in the model. It allows obtaining solutions in concordance with the real conditions. The model is applied to the energy system of Argentina by using an epsilon-constraint approach and Mixed Integer Linear Programming formulations. The test system supplies electricity to over 40 million people and neighboring countries. Besides, there is interdependency with the Argentinean Natural Gas system that operates in one of the most extended territories in Latin America. Results indicate that the solutions that are more convenient for all actors represent a mix between renewables and non-renewables technologies. Consequently, this proposal is differentiated from other ones that only consider the expansion concerning renewables technologies. The study reveals decreases in emissions up to 39% and the reduction in production costs up to 12% in comparison with the solution without investments.

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Renewable energy investment and carbon emissions under cap-and-trade mechanisms

Cited by 87 publications

References 36 publications

Investment strategy for renewable energy and electricity service quality under different power structures

Investment strategy for renewable energy and electricity service quality under different power structures

Joint Optimization of Quota Policy Design and Electric Market Behavior Based on Renewable Portfolio Standard in China

A multi‐objective model for the analysis of investments to achieve an electricity cleaner production. The case of the Argentinean system

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