Social welfare maximization in AC-DC power systems based on evolutionary algorithms: a new merit of HVDC links

Abstract

Summary In the current paper, the social welfare maximization for alternating current–direct current (AC–DC) Deregulated Power System (DPS) based on evolutionary algorithms is introduced. The social welfare optimization based on evolutionary algorithms is very simple in comparison with numerical methods for complications of social welfare equations in the presence of high-voltage direct current (HVDC) links, limitations of numerical methods in differentiable convex objective functions, and need of additional mathematical calculations and many variables especially for constraints. Furthermore, as a new merit of HVDC transmission lines besides all well-known privileges, the advantage of the HVDC transmission line presence in a power system for social welfare maximization in comparison with a pure AC power system is shown. To reach this aim, the social welfare maximization is studied in two main steps. First, it is investigated in an AC DPS for four different scenarios. Then one of the most important AC lines transmitting a huge amount of power (operating at its thermal limit) is replaced with a HVDC link with exact the same transmission capacity; and the social welfare is maximized again for four aforementioned scenarios. The optimization process in all cases is performed using Differential Evolution Algorithm (DEA) that is selected among five different evolutionary methods, i.e., Particle Swarm Optimization, Shuffled Frog Leaping Algorithm, Teaching-Learning-Based, and Artificial Bee Colony besides DEA. The results show that the social welfare of the DPS in the presence of the HVDC link is enhanced remarkably during scenarios with high supply, in which congestion of AC transmission line is occurred. Copyright © 2014 John Wiley & Sons, Ltd.