Multi-microgrid System Collaborative Optimization Strategy Considering Distributed Demand Response

doi:10.12204/j.issn.1000-7229.2023.05.008

Abstract

Abstract:

With the increasing penetration of clean energy into existing power systems, the collaborative optimization of multi-microgrid systems has become an effective way to promote the utilization of clean energy. A reasonable distributed demand response mechanism has research significance for improving the capacity of clean energy consumption. In this study, a multi-microgrid collaborative optimization mechanism and an autonomous bidding strategy of demand response resources that consider the distributed demand response are proposed. First, a microgrid autonomous optimal dispatch model is established to formulate power supply-demand plans and DR strategies by considering the incentive characteristics of demand response contracts. Second, referring to historical transaction information, each microgrid proposes IDR bidding strategies to maximize prospective benefits. Third, to implement an economic and efficient distributed demand response, a two-way auction mechanism is introduced in the day-ahead stage to develop a peer-to-peer matching framework for demand response resources. Finally, numerical example results verify that the proposed mechanism can realize the distributed transactions of demand response resources, improve the economy of multi-microgrid systems, and effectively promote clean energy consumption.

Key words: multi-microgrid system, clean energy, distributed demand response, collaborative optimization, two-way auction mechanism

CLC Number:

TM734

LIU Ren, LIU Yang, XU Lixiong, LI Zhenwei, LI Xueling. Multi-microgrid System Collaborative Optimization Strategy Considering Distributed Demand Response[J]. ELECTRIC POWER CONSTRUCTION, 2023, 44(5): 72-83.

Figures/Tables 19

Fig.1 Multi-microgrid system collaborative optimization architecture

Table 1 Distributed demand response algorithms

Table 2 Comparison of operation indicators in different schemes 元

Fig.2 Comparison of decision results in different schemes

Fig.3 Microgrid 2 of internal supply and demand self-balance results

Fig.4 Microgrid 3 of internal supply and demand self-balance results

Fig.5 Microgrid 4 of internal supply and demand self-balance results

Fig.6 Quotation strategy in DR suppliers

Fig.7 Bidding strategy in DR receiver

Fig.8 t=13 Demand response bidding curve and transaction electricity quantity of each microgrid

Fig.9 The 10th round t=13 demand response matching results of each microgrid

Fig.A1 WPG forecast output in each microgrid

Fig.A2 SPG forecast output in each microgrid

Fig.A3 Load forecast demand in each microgrid

Table A1 Operating parameters of CGs

Table A2 Operating parameters of ESS

Table A3 Time-of-use tariff and on-grid tariff

Table A4 Parameters of IDR contract

Table A5 Demand response peer-to-peer matching schemes of each microgrid

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