Solving the Integrated Optimal Power and Gas Flow Problem by Improved Crow Search Algorithm

This paper solves the integrated optimal power and gas flow (IOPGF) problem in a multicarrier energy system (MES), to find the operating variables of electrical and natural gas networks satisfying some practical constraints. The proposed problem models optimal power flow (OPF), optimal gas flow (OGF), and economic heat dispatch (EHD) equations which make it a very complex optimization problem that cannot be easily solved by the classical optimization techniques. In addition, a population-based evolutionary algorithm (PEA), namely the improved crow search algorithm (ICSA) is introduced and applied to solve the OPF and the IOPGF problems. The results are compared with other well-known PEAs to ensure the higher performance of the ICSA. Also, the superior performance of the ICSA is confirmed by applying it to solve five well-known benchmark functions (BFs).

Automated summary

This paper addresses the integrated optimal power and gas flow problem in a multicarrier energy system. It proposes a complex optimization problem and introduces a population-based evolutionary algorithm to solve it. The superior performance of the algorithm is confirmed through comparisons and benchmark function tests.