摘要
国家“双碳”战略目标的提出和碳交易市场的完善对微电网的调度运营提出了更高要求,该文以减排、降本为目标,综合考虑负荷约束、储能设备充放电约束、碳配额约束,构建了包括光伏、风电、柴油发电机组以及储能模块的微电网低碳运营-经济效益双层优化模型。外层规划模型引入碳资产运营机制,基于改进的遗传算法优化微电网运营策略,提高经济效益的同时确保系统低碳运行;内层需求响应模型通过激励手段改善用户用电行为,优化负荷曲线,并将执行需求响应后的负荷反馈至外层模型。内、外双层模型交互迭代直至各设备配置和负荷曲线均达到最优,从而实现负荷与碳排放的双向互动。多个场景下的仿真结果表明,所提双层优化模型能显著降低微电网运营成本、降低碳排放量。敏感性分析结果显示,碳交易价格对于运营策略和成本有较大影响。
Abstract
The proposal of the national “dual carbon” strategic goals and the improvement of the carbon trading market have placed higher demands on the dispatch and operation strategies of microgrids. Aiming at emission reduction and cost
lowering, this paper develops a dual-layer optimization model for low-carbon and economic operation of microgrids, which includes photovoltaic, wind power, diesel generator sets, and energy storage modules, while considering load constraints,charging/discharging constraints of storage devices, and carbon quota constraints. The outer-layer planning model introduces a carbon asset operation mechanism and uses an improved genetic algorithm to optimize microgrid operation strategies, improving economic benefits while ensuring low-carbon system operation. The inner-layer demand response model improves user electricity consumption behavior through incentive measures, optimizes the load curve, and feeds back the user response after implementing demand response to the outer-layer model. The inner and outer layers interact iteratively until both equipment configurations and load curves reach optimum, thereby achieving a bidirectional interaction between load and carbon emissions. Simulation results under multiple scenarios demonstrate that the proposed dual-layer optimization model can significantly reduce microgrid operation costs and carbon emissions. Sensitivity analysis results show that carbon trading prices have a significant impact on operation strategies and costs.
关键词
微电网 /
碳交易 /
需求响应 /
协同优化 /
遗传算法
Key words
microgrid /
carbon trading /
demand response /
joint optimization /
genetic algorithm
潘 森1, 王旭东2, 王 林2, 王 洋2, 周爱华1, 乔俊峰1.
考虑碳资产的微电网调度及其优化
[J].
分布式能源, 0 https://doi.org/10.16513/j.2096-2185.DE.25100370.
PAN Sen1, WANG Xudong2, WANG Lin2, WANG Yang2, ZHOU Aihua1, QIAO Junfeng1.
Microgrid Scheduling and Optimization Considering Carbon Assets[J]. Distributed Energy, 0 https://doi.org/10.16513/j.2096-2185.DE.25100370.
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基金
国家电网有限公司总部管理科技项目 (5700-202312315A-1-1-ZN)