A Multi-Agent Game-Based Incremental Distribution Network Source–Load–Storage Collaborative Planning Method Considering Uncertainties

Abstract

How to obtain the optimal decision-making scheme based on the investment behavior of various stakeholders is an important issue that needs to be solved urgently in incremental distribution network planning. To this end, this article introduces the virtual player “Nature” to realize the combination of the game theory and robust optimization and proposes an incremental distribution network source–load–storage collaborate planning method with a multi-agent game. First, the planning and decision-making models of a DG investment operator, a distribution network (DN) company, power consumers, and a distributed energy storage (DES) investment operator are constructed, respectively. Then the static game behaviors between the DG investment operator and distribution network company, as well as the DG investment operator and the DES investment operator, are analyzed based on the transfer relations between these four participants. At the same time, robust optimization is used to deal with the uncertainty of the DG output, and the virtual player “Nature” is introduced to study the dynamic game behavior between the DG investment operator and the distribution company. Finally, a dynamic–static joint game planning model is proposed. The simulation results verify the correctness and effectiveness of the proposed method.

Optimal planning of distribution network with transactive energy: Review and framework

“…The latter emphasises the concept of commercial ownership of energy infrastructures and operation rights/capabilities. The stakeholders include distribution network companies, IDSO, electricity sales companies, prosumers, and user-owned units [24,25]. In the planning problem, multi-stakeholders mainly focus on analysing investment preference, business model, and economic interest.…”

Coordinated planning of integrated electricity–heat–gas energy system considering renewable energy consumption

“…Electricity price and natural gas price are 80$/MWh and 14$/Mbtu which based on [38]. The subsidy of renewable generation is 15$/MWh according to [39,40]. Through k-means method, the curves of time series of electricity demand, heat demand, gas demand, WT output and PV output in typical scenarios can be obtained, as shown in Figure 3.…”

“…Electricity price and natural gas price are 80$/MWh and 14$/Mbtu which based on [38]. The subsidy of renewable generation is 15$/MWh according to [39, 40].…”

Research on comprehensive evaluation method of distribution network based on AHP-entropy weighting method

“…The other kind of evaluation approach examines a specific metric, such as economy, reliability, environmental protection, etc. (Zhang et al, 2015;Dong et al, 2016;Boutaba et al, 2018;Chen et al, 2018;He et al, 2018;Wei et al, 2018;Huang et al, 2019;Yang et al, 2021b;Yang et al, 2021c;Yang et al, 2022a;Yang et al, 2022b).…”

“…In the evaluation of distribution network, literature (Zhang et al, 2015;Dong et al, 2016) builds a comprehensive evaluation index system including economy, sociality and environment. Different from the previous literature that only studied a single user group, the traditional variable weight calculation method in literature (Yang et al, 2022b) is characterized by difficult selection of state variable weight vector and weak operability. As a result, this research provides a shape similarity-based variable weight computation method.…”