考虑灵活的能源-碳-绿色证书交易的农村虚拟电厂情景驱动分布式稳健优化模型

IF 10.1 1区工程技术 Q1 ENERGY & FUELS

Applied Energy Pub Date : 2024-11-22 DOI:10.1016/j.apenergy.2024.124904

Jinye Cao , Chunlei Xu , Zhuoya Siqin , Miao Yu , Ruisheng Diao

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引用次数: 0

摘要

随着农业与能源耦合度的提高，在农业园区利用农村虚拟电厂（RVPP）聚集和管理分布式能源资源已成为一种趋势。本文研究了可再生能源发电和能源使用的不确定性以及能源-碳-绿色证书（GC）交易的灵活性对 RVPP 规划和运行的影响。首先，构建了 RVPP 的基本架构，并设计了碳排放限额（CEA）和绿色证书（GC）的联合交易机制。在此基础上，考虑到 RVPP 规划阶段的容量配置和运营阶段的 Stackelberg 博弈，建立了两阶段确定性优化模型。然后，考虑到不确定性的相关性，生成几个典型的情景，并以情景驱动的方式将确定性模型转化为分布鲁棒优化（DRO）模型。情景概率分布的置信区间由 1 正态和无穷正态组合约束。最后，DRO 模型被分解成两个问题，使用修正克里金模型和列与约束生成（C&CG）算法迭代求解。通过对不同交易形式和求解方法的多个案例进行比较分析，验证了 DRO 模型的有效性。仿真结果表明，与固定价格的能源交易相比，基于 Stackelberg 博弈的灵活交易可降低总计划和运营成本 22.49%。与 GC 和 CEA 的单独交易相比，在联合交易机制下，随着可再生能源资源配置的增加，CEA 的交易量减少了 44.21%。

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Scenario-driven distributionally robust optimization model for a rural virtual power plant considering flexible energy-carbon-green certificate trading

With the increased coupling of agriculture and energy, there is a trend to aggregate and manage distributed energy resources in agricultural parks using rural virtual power plants (RVPP). This paper investigates the impact of uncertainties in renewable energy generation and energy usage, as well as the flexibility of energy‑carbon-green certificate (GC) trading, on the planning and operation of RVPP. Firstly, the basic architecture of RVPP is constructed, and a joint trading mechanism for the carbon emission allowance (CEA) and GC is designed. On this basis, a two-stage deterministic optimization model is developed considering capacity configuration in the planning stage and the Stackelberg game in the operation stage of RVPP. Then, several typical scenarios considering the correlation of uncertainties are generated, and the deterministic model is transformed into a distributionally robust optimization (DRO) model in a scenario-driven manner. The confidence intervals of the scenario probability distributions are constrained by a combination of 1-norm and infinity-norm. Finally, the DRO model is decomposed into two problems, solved iteratively using a revised Kriging model and a column-and-constraint generation (C&CG) algorithm. Several cases covering different transaction forms and solution methods are analyzed comparatively to validate the effectiveness of the DRO model. The simulation results indicate that, compared to the energy trading with a fixed price, flexible trading based on the Stackelberg game can reduce the total planning and operating costs by 22.49 %. Compared to the separate trading of GC and CEA, the trading volume of CEA decreases by 44.21 % under the joint trading mechanism, with the increased configuration of renewable energy resources.

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来源期刊

Applied Energy 工程技术-工程：化工

CiteScore

21.20

自引率

10.70%

发文量

1830

审稿时长

41 days

期刊介绍： Applied Energy serves as a platform for sharing innovations, research, development, and demonstrations in energy conversion, conservation, and sustainable energy systems. The journal covers topics such as optimal energy resource use, environmental pollutant mitigation, and energy process analysis. It welcomes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gap between research, development, and implementation. The journal addresses a wide spectrum of topics, including fossil and renewable energy technologies, energy economics, and environmental impacts. Applied Energy also explores modeling and forecasting, conservation strategies, and the social and economic implications of energy policies, including climate change mitigation. It is complemented by the open-access journal Advances in Applied Energy.