考虑垃圾焚烧和云储能运营商的多虚拟电厂区域自治策略:一种低碳混合博弈方法

IF 1.6 Q4 ENERGY & FUELS
Xinrui Liu, Junbo Feng, Ming Li, Rui Wang, Chaoyu Dong, Liangsheng Lan, Qiuye Sun
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引用次数: 0

摘要

在低碳战略和电力市场化改革的背景下,未来配电网中将会出现多个虚拟电厂并存的情况。为了提高可再生能源高比例下虚拟电厂(VPP)的能源利用率和自主性,解决VPP之间的利益冲突和信息不对称,提出了云储能运营商(CSO)背景下配电网与虚拟电厂兼顾环境效益的混合博弈双层能源优化运行策略。首先,以上层利益最大化,下层成本最小化为目标,构建了Stackelberg博弈双层能源交易模型。其次,引入VPP成员间的合作博弈,实现VPP之间的点对点交易,并建立混合博弈优化模型;VPP中引入了垃圾焚烧发电厂和碳捕集系统的联合运行,兼顾了系统的经济性和低碳性。然后,根据模型的特点,采用结合CPLEX的遗传算法求解Stackelberg模型,采用乘法器交替方向法求解协同模型。两层模型相互作用,得到了CSO、MVPP和MVPP内混合博弈模型的平衡最优运行策略。最后,通过仿真算例验证了该策略的可行性和有效性。本文提出的低碳混合博弈策略有效地提高了CSO和MVPP的利益,保护了成员的数据隐私,提高了VPP的自主性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Regional Autonomy Strategy of Multi-Virtual Power Plant Considering Waste Incineration and Cloud Energy Storage Operator: A Low-Carbon Mixed Game Method

Regional Autonomy Strategy of Multi-Virtual Power Plant Considering Waste Incineration and Cloud Energy Storage Operator: A Low-Carbon Mixed Game Method

Under the background of the low-carbon strategy and power market reform, multiple virtual power plants (MVPP) will coexist in the distribution network in the future. In order to improve the energy utilisation rate and the autonomy of virtual power plant (VPP) under the high proportion of renewable energy sources, and solve the conflict of interest and information asymmetry among MVPP, a mixed game dual-layer energy optimisation operation strategy between the distribution network and MVPP with the consideration of environmental benefits under the background of cloud energy storage operator (CSO) is proposed. First, a Stackelberg game dual-layer energy trading model is constructed to maximise the benefits of the upper layer and minimise the cost of the lower layer. Second, a cooperative game among members of the VPP is introduced to enable peer-to-peer trading among MVPP, and a mixed game optimisation model is established. The joint operation of the waste incineration power plant and carbon capture system is introduced into the VPP, which takes into account the economy and low carbon of the system. Then, according to the characteristics of the model, the Stackelberg model is solved by using the genetic algorithm combined with CPLEX, and the cooperative model is solved by using the alternating direction method of multipliers. The dual-layer models interact with each other, and the balanced optimal operation strategy of the CSO, MVPP and mixed game model within the MVPP is obtained. Finally, the feasibility and effectiveness of the strategy are verified by simulation examples. The low-carbon mixed game strategy proposed in this paper effectively improves the interest of CSO and MVPP, protects the data privacy of members and improves the autonomy of VPP.

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来源期刊
IET Energy Systems Integration
IET Energy Systems Integration Engineering-Engineering (miscellaneous)
CiteScore
5.90
自引率
8.30%
发文量
29
审稿时长
11 weeks
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