Optimal bidding of profit-seeking virtual associations of smart prosumers considering peer to peer energy sharing strategy

Abstract

This paper presents a risk-averse stochastic framework for virtual associations (VAs), which are dynamic clusters of prosumers. A VA, as a price taker agent, supports the active participation of prosumers in the day-ahead (DA) electricity market. In this regard, a bi-level optimization model is formulated to optimize the decision-making problem of the VA in the DA market with the main goal of maximizing VA profit and minimizing the total energy costs of prosumers. In this framework, the impacts of peer to peer (P2P) trading among the prosumers and VAs on the offering and bidding strategies of VAs are also considered. In a competition among VAs, the prosumers are able to select the most competitive VA to participate in the DA market. Moreover, due to the uncertainties of market prices, the VA should undertake the risks arising from price volatilities that may cause the VA to suffer from financial loss due to occurrence of some scenarios such as price spikes. To compensate the undesired effects of the occurrence of price spikes, the impacts of demand response (DR) actions and peer to peer (P2P) energy trading among prosumers on the decisions of VA are analyzed. Moreover, an index is defined from which the competitive condition in a retailing layer would be analyzed. Using Nordpool data as a practical test system, the undesired effects of occurrence of price spikes are compensated using demand response (DR) actions and peer to peer (P2P) energy trading among prosumers. Moreover, an index is defined from which the competitive condition in a retailing layer would be analyzed.