Multi-objective performance of smart hybrid energy system with Multi-optimal participation of customers in day-ahead energy market

Abstract

Optimal energy consumption is one of the sustainable development issues in many countries to improve the economic and environmental indices in the energy sector. This paper presents a tri-objective optimal performance of a smart hybrid energy system (SHES) in the presence of customer's participation to optimally reshape the demand profile in the day-ahead energy market. Minimizing the operation costs and the emission pollution as well as maximizing the customer satisfaction level are considered as the objectives of this problem. The three types of demand response (DR) programs consisting of 1) demand curtailment, 2) demand shifting and 3) onsite generation program are considered for optimal scheduling of the electrical and the thermal energy consumption by the customers. The demand curtailment program is considered as the reserve for SHES and the Plug Electric Vehicles (PEVs) are taken into account as the onsite generation program. The uncertainties of energy and reserve prices are modeled using lognormal distribution function. The shuffled frog leaping algorithm (SFLA) is employed to solve the problem from which the non-dominated solutions are generated. Then, the best solution of the non-dominated solutions is selected by the hybrid approach of fuzzy method and the weight sum. To validate the mentioned approach, five case studies are investigated and the results demonstrate optimal scheduling of SHES with acceptable levels of operation costs, emission pollution and customer satisfaction.