Modeling and planning a transmission network expansion system in a regulated electricity market by considering demand-side management via a developed fuzzy-salp optimization algorithm

Document Type : Original Article


1 Electric Power Research Institute of State Grid Xinjiang Electric Power Co., Ltd., Urumqi, Xinjiang, 830011, China

2 Engineering Research Center of Renewable Energy Power Generation and Grid-connected Control, Ministry of Education, Xinjiang University, Urumqi, Xinjiang, 830017, China


With the daily rise in power demand, the penetration of dispersed generations (DG) such as wind turbines, the operation of series reactive compensator devices and the progress of reconfiguration in power system management, there is a dire need for optimally planning the expansion of transmission network lines. Transmission network expansion planning (TEP) is a major part of power system expansion planning that determines the type, location and time of installing new lines for the adequacy of power supply. Therefore, the TEP problem is a dynamic optimization problem with mixed and integer variables. In traditional systems, consumption management programs were used to overcome some problems of the power system. Meanwhile, demand response (DR) programs were discussed as a part of these programs. However, after the reconfiguration of power systems, these programs were gradually discarded due to incompatibilities with the nature of the market. Soon, due to the problems such as price instability, re-implementation of consumption management programs once again gained momentum. This time, these programs were altered to be compatible with the reconfigured power system management structure. This is widely accepted that increasing the presence and participation of consumers in DR programs in the electricity market will benefit not only individual consumers, but also the whole consumer community. In this paper, a dynamic multi-objective TEP is performed under reliability constraints in the market setting based on demand sales programs and price-dependent bids in the day-ahead market. The proposed algorithm was implemented on an IEEE 24-bus gird to display its benefits, including reduction of investment costs, mitigation of congestion and promotion of reliability.