Calculating the locational marginal price and solving optimal power flow problem based on congestion management using GA-GSF algorithm

An important factor in reviewing the performance of generation units and calculating their profit is the calculation of their locational marginal price (LMP), and this depends on our knowledge on the capacity of transmission lines and optimal power flow (OPF) based on reality by which we aim to minimize the total cost of the generators, solve the congestion of transmission lines, and hence, reduce the price of electricity in the market. Since power flow equations are nonlinear, they should be solved using numerical and repetition-based methods. In this paper, genetic algorithm (GA) has been employed to solve these equations, and in order to improve the performance of GA in its structure, generating scaling factor (GSF) has also been used for simultaneous calculations of power passing through in transmission lines so that by gaining some knowledge on the capacity of transmission lines, in addition to optimal power flow becoming real, we could determine the electricity price by uniform market pricing or LMP methods depending on using the full capacity of lines and generating power of the units, and thus, we can calculate the profit of generators. Finally, the output of the proposed GA-GSF algorithm would include values of buses voltages, lines losses, injected power to buses, power passing through lines, total generation cost, and generators’ profits. Also, the proposed algorithm in this paper has been tested on IEEE 14-BUS, IEEE 30-BUS, IEEE 57-BUS network, and the results show improvements on the OPF problem.