Social Cost Optimization for Prosumer Community with Two Price-Package Incentives in Two-Settlement Based Electricity Market
Jianzheng Wang, Guoqiang Hu

TL;DR
This paper develops a stochastic game-based framework for optimizing social costs in prosumer communities with flexible pricing packages in a two-settlement electricity market, enhancing market efficiency.
Contribution
It introduces a novel stochastic Stackelberg game model for social cost optimization considering two-price packages and prosumer behaviors in a two-settlement market.
Findings
The proposed algorithm effectively minimizes social costs.
Analytical strategies for prosumer trading behaviors are derived.
Simulation results demonstrate improved market efficiency.
Abstract
In this paper, we consider a future electricity market consisting of aggregated energy prosumers, who are equipped with local wind power plants (WPPs) to support (part of) their energy demands and can also trade energy with day-ahead market (DAM) and energy balancing market (EBM). In addition, an energy aggregator (EA) is established, who can provide the trading gateways between prosumers and the markets. The EA is responsible for making pricing strategies on the prosumers to influence their trading behaviours such that the social benefit of the prosumer community is improved. Specifically, two price packages are provided by the EA: wholesale price (WP) package and lump-sum (LS) package, which can be flexibly selected by prosumers based on their own preferences. Analytical energy-trading strategies will be derived for WP prosumers and LS prosumers based on non-cooperative games and Nash…
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Taxonomy
TopicsSmart Grid Energy Management · Electric Power System Optimization · Electric Vehicles and Infrastructure
