Techno-economic optimal operation of the electrical distribution grid considering smart energy consumption by consumers

Energy optimization is one of the major issues for electrical distribution companies to meet demand with minimum generation costs and power losses. In this paper, the optimal operation of the smart electrical distribution grid is modeled by three-stage multi-objective optimization with optimal consumers’ participation and electrical storage systems (ESSs) under electrical price and load demand uncertainties at day ahead. The three strategies of demand response programs (DRPs) such as demand shifting (DS), demand curtailment (DC), and onsite generation (OG) to consumers’ participation are considered with attention to electrical price traffic. In the first and second stages, electrical demand is optimized using DS and DC strategies, respectively. Thus, optimized electrical demand is applied to the third stage optimization for minimization of the multi-objective functions including (1) minimum generation costs and (2) power losses. Also, OG is implemented by ESSs in the third stage optimization as a local resource. All stages of the proposed approach are optimized by the shuffled frog leaping (SFL) algorithm. On the other side, the TOPSIS decision-making method is used to choose the best trade-off solution in the third stage optimization. Eventually, the proposed optimization by the numerical simulation is carried out considering four case studies in IEEE 33-bus test system to demonstrate validation of the strategies. The case studies are implemented based on the participation of the consumers by using DS, DC, and OG strategies. In the first case study, the participation of the consumers is not considered, and this case is assumed as a base case study. The participation of the consumers with the DS strategy is implemented in the second case study. The DS and DC strategies are used by consumers in the third case study, simultaneously. In the fourth case study, OG with DS and DC strategies is considered for optimal participation in energy optimization. The participation of all strategies by consumers leads to minimizing energy generation costs and power loss by 5.52% and 14.68% in comparison with non-participation of the consumers.