Collaborative Optimal Scheduling and Cost Allocation of Multiload Aggregator Considering Ladder-Type Carbon Trading

REN Hongbo, WANG Nan, WU Qiong, SHI Shanshan, FANG Chen, WAN Sha

Electric Power Construction ›› 2024, Vol. 45 ›› Issue (2) : 171-182.

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Electric Power Construction ›› 2024, Vol. 45 ›› Issue (2) : 171-182. DOI: 10.12204/j.issn.1000-7229.2024.02.015
Power Economic Research

Collaborative Optimal Scheduling and Cost Allocation of Multiload Aggregator Considering Ladder-Type Carbon Trading

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Abstract

The large-scale penetration of renewable energy sources poses significant challenges to the stable operation of power systems. Driven by double uncertainties on both the supply and demand sides, demand response resources based on terminal flexible loads need to be explored. Considering the load differentiation characteristics of different types of users, multitype load aggregators based on cooperation and win-win were introduced. Flexible dispatching of the power system was performed based on the complementary characteristics of the heterogeneous load response behaviors. Moreover, each load aggregator was assigned the dual status of a carbon trading integrator to enter the carbon trading market. A carbon trading model based on a reward-punishment ladder was constructed using the electricity load forecasting method to allocate carbon emission quotas for a system free of charge. Based on this, to minimize the sum of the operating costs of a cooperative alliance of multiple load aggregators, a pre-day optimization model of the interaction and cooperation among multiple aggregators was developed and solved. The Shapley value method was introduced for the cooperative game, and the cost was shared according to the contribution of each participant to the operation of the cooperative alliance. The results show that the overall and individual operational costs and the carbon emissions of the alliance are significantly reduced under the cooperative operation mechanism.

Key words

demand response / carbon trading / load aggregator / cost allocation / cooperative game

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Hongbo REN , Nan WANG , Qiong WU , et al . Collaborative Optimal Scheduling and Cost Allocation of Multiload Aggregator Considering Ladder-Type Carbon Trading[J]. Electric Power Construction. 2024, 45(2): 171-182 https://doi.org/10.12204/j.issn.1000-7229.2024.02.015

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针对热/电联合运行下多种柔性负荷协调优化不足以及面临的风、光出力和柔性负荷等多种不确定性,文章提出了一种考虑柔性负荷下的虚拟电厂(virtual power plant,VPP)热电联合鲁棒优化调度方法。充分考虑可削减、可平移、可转移柔性负荷之间的协调互补性,分别以热/电负荷曲线标准差和系统综合运行成本最低为目标,建立了虚拟电厂热电联合双层协调优化运行模型,提高了多种柔性负荷协调优化效果;并采用鲁棒优化方法处理风、光出力和柔性负荷预测误差的不确定性,提高热电系统运行的鲁棒性。多种柔性负荷的协调优化增强了系统的灵活调节能力,使经济性更优,不同鲁棒系数下柔性负荷优化效果的对比,为适应不同需求情景下的决策者提供参考依据。算例分析验证了所提模型的有效性。
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Aiming at the lack of coordination and optimization of multiple flexible loads under combined heat and power operation and the uncertainties faced by wind, solar power, and flexible loads, a robust optimization scheduling method for virtual power plant(VPP)combined heat and power considering flexible loads is proposed. Fully considering the coordination and complementarity among the reduction, translation and transferable flexible loads, the standard deviations of the thermal and electric load curves and the lowest comprehensive operating cost of the system are chosen to be the goals, and a dual-layer coordinated optimization operation model of virtual power plant combined heat and power is established, which may improve the coordination and optimization effect of multiple flexible loads. The prediction error uncertainty of wind and solar power and flexible load is dealt with by the robust optimization method to improve the system operation robustness. The coordination and optimization of multiple flexible loads enhance the system's flexible adjustment capabilities and make the economy better. The comparison of the optimization effects of flexible loads under different robustness coefficients provides a reference for decision makers in different demand scenarios. The analysis of an example verifies the effectiveness of the proposed model.

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Funding

Science and Technology Project of State Grid Corporation of China(52094021000C)
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