Research Info

This paper proposes a multi-objective optimal energy flow problem in the integrated energy distribution systems including electrical, thermal, and natural gas distribution networks. From the mathematical perspective, the electrical network is considered unbalanced and thermal units such as combined heat and power plants and boilers are modeled by their part-load performance. The objectives are minimizing the total operational energy cost of supplying electrical and thermal demands, electrical losses, and unbalances in the power flow in three phases of the grid. A modified teaching-learning based optimization algorithm is applied to solve the optimization problem, considering all constraints of the integrated energy distribution systems. The Pareto optimal front is employed to show the results. The best compromise solution is selected from the Pareto optimal solutions using a fuzzy decision making-based mechanism. The performance of obtained solutions is validated in a typical integrated energy distribution system. In this regard, a practical 19-bus unbalanced electrical network, a practical thermal network with 30-node, and a typical 20-node natural gas network are combined together. The results demonstrate the effectiveness of the proposed multi-objective methodology in finding better operating points for integrated energy distribution systems in comparison with single- and bi-objective problems. In addition, the impacts of the deployment of energy storage systems on the operation of the energy systems are studied in the designated cases.