A combination of heuristic and bacteria foraging-differential evolution algorithm for transmission network expansion planning with security constraints

Article type: Research Article

Authors: Verma, Ashu^{; *} | Bijwe, P.R. | Panigrahi, B.K.

Affiliations: Deparment of Electrical Engineering, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi, Pin -110016, India

Correspondence: [*] Corresponding author. E-mail: [email protected]

Abstract: Transmission network expansion planning (TNEP) is an important component of power system planning. Its task is to determine the optimal set of transmission lines to be constructed such that the cost of expansion plan is minimum and no network constraints are violated during the planning horizon. The problem is very complex due to large number of options to be analysed and the discrete nature of the optimization variables. Hence, more efficient and robust techniques are required to solve this complex problem. This paper presents a new hybrid approach for TNEP with security constraints, where first the solution is obtained very quickly with a new promising heuristic method, which is used as a starting point for the proposed metaheuristic approach known as bacteria foraging differential evolution algorithm (BF-DEA). The heuristic method used for generating the initial solution is based on a DC power flow based compensation approach to simulate single/double line modifications arising out of a candidate line addition and an outage of other line. This method can be used to quickly obtain a suboptimal/optimal transmission network expansion plan. One of the difficulties with metaheuristic methods is the possibility of premature convergence to a nonoptimal solution. The worst part is that in many situations we do not even know as to how close/far the optimal solution obtained is from the global optimum one. The plan obtained with the heuristic method provides an upper bound on the solution obtained with BF-DEA. The hybrid method thus ensures that BF-DEA will provide a solution which is much closer to the global optimum. Results for two sample systems demonstrate the potential of the proposed scheme.

Keywords: Transmission expansion planning, compensation approach, hybrid method

DOI: 10.3233/HIS-2010-0107

Journal: International Journal of Hybrid Intelligent Systems, vol. 7, no. 2, pp. 101-113, 2010