Economics-based transmission expansion planning in restructured power systems using decimal codification genetic algorithm

Transmission expansion planning is an important component of power system planning that affects all aspects of the power system including both generation and demand side in different ways. An inherent problem to today's restructured power markets is the congestion management problem. Since the transmission system is limited by operational and reliability constraints, the participants face significant congestion costs that can be alleviated by investing in transmission capacity. In this paper, an economics-based transmission expansion planning model is proposed. The model minimizes the costs of investment and congestion over a planning horizon that includes multiple load profiles. Decimal Codification Genetic Algorithm (DCGA) is then used to solve the resulting nonlinear mixed-integer problem. The model proposed here will be particularly useful for independent transmission planners who are responsible for making decisions regarding power network operations. The Garver's 6-bus network is examined to show the adequacy of the proposed model. Testing proposed expansion approach on an actual transmission network of northwest of Iran, the Azerbaijan regional electric company, the results reveals effectiveness of the model to handle realistic power networks.