Constrained Consumption Shifting Management in the Neighborhood System Scheduling Considering Coalition Formation and Profit Allocation

For enhancing competitiveness of energy district (ED) or distributed energy resources (DER) inside them in market, optimal operation of these has arisen as a relevant topic. With this objective, EDs (or DERs inside them) can collaborate with other EDs in the neighborhood system installed closer or far, forming coalitions for gaining competitiveness in the market. Profit allocation due to coalition between EDs is as an important issue for ensuring DER resources installation in smart grids. In addition, demand fluctuations and energy production based on renewable resources in the neighborhood systems for each ED independently can be accomplished by demand-side management strategies that try to establish mechanisms to allow for a flatter demand curve. In this regard, demand shifting potential can be tapped through the shifting of certain amounts of energy demand from some time periods to other time periods with lower expected demand, typically in response to price values, to help ensure that existing generation will remain available as well as to obtain the maximum profit with the coalition formation. The impact of the consumption shifting in the EDs and existing DERs schedule is also considered during the conduct of both independent and coalition operations. In this paper, a methodology based on artificial bee colony (ABC) is proposed to maximize the profit in a competitive market and allocate profit resulting from a coalition formation between multiple EDs encompassing DERs. The results obtained shown that the disconnection of DERs resulting from pricing decisions allows them to collaborate together with aggregated facilities to achieve higher profits due to excess production and avoid penalties due to shortages in production and demonstrated that significant increase in the profit may persuade the producers for forming a coalition. Eventually, performance of the proposed algorithm is compared with the developed algorithm based on non-linear programming.