Game theory-based renewable multi-energy system design and subsidy strategy optimization
- Renewable MES design and subsidy strategy optimization are presented.
- A game theory-based modeling framework is proposed.
- Real-world case study is assessed in two decarbonization scenarios.
- Optimal renewable subsidy can effectively promote renewable acceptance.
- An economic two-phase pathway is recommended for city-level decarbonization.
Renewable multi-energy systems have become a promising solution for deep decarbonization. However, government subsidy is needed to incentivize the deployment of renewable technologies for emission reduction. Here, we provide a game theory-based modeling framework along with tailored solution strategy for optimizing multi-energy system design and renewable subsidy strategies. We apply our modeling framework to four pilot towns in China for studying how government and consumers interact with each other to achieve their respective goals with minimum costs. We show that government subsidy policies can effectively promote renewable penetration or reduce carbon emissions, and photovoltaic panels and wind turbines absorb most of government subsidy in renewable penetration and emission cap cases, respectively. We also analyze in detail the optimal energy technology operations for meeting targets of government and pilot towns. We find that only increasing renewable penetration cannot achieve deep decarbonization; however, directly imposing carbon emission cap causes heavy government financial burden. Hence, we recommend an economic two-phase decarbonization pathway, namely first increasing renewable penetration to reduce dependence on fossil energy and then imposing a carbon emission cap to fulfill deep decarbonization. Our two-phase decarbonization pathway can be applied to other cities in China and worldwide, aiming to promote renewable energy penetration, reduce reliance on fossil fuels, and finally realize carbon neutral cities. Our proposed game theory-based modeling framework can also be extended to various temporal and spatial scales for studying how different entities can cooperate together for deep decarbonization.
- Access the article at the publisher: DOI: 10.1016/j.adapen.2021.100024
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