Optimal Reactive Power Planning of Doubly Fed Induction Generators Using Genetic Algorithms P. SANGSARAWUT, A. OONSIVILAI and T. KULWORAWANICHPONG Power System Research Unit, School of Electrical Engineering Suranaree University of Technology 111 University Avenue, Suranaree District, Nakhon Ratchasima THAILAND thanatchai@gmail.com Abstract: - This paper describes optimal reactive power control of a doubly fed induction generator (DFIG), which is widely used in a distributed generating plant. Although its structure is similar to that of an induction motor, its reactive power control is more complicated. In this paper, steady-state power transfer equations are derived and developed for a doubly fed structure of the induction generators. When a distributed power plant equipped with DFIGs is connected to a regional power grid, reactive power injection from the plant results in distribution system performances, e.g. voltage drop, power losses, etc. By using genetic algorithms, optimal reactive power injection can be achieved in order to minimize total power loss in power distribution systems. The 37-node IEEE standard test feeder is used to evaluate its performances. As a result, optimal reactive power control of DFIGs can reduce total power losses and also improve voltage profiles in power distribution systems. Key-Words: - Optimal reactive power planning, doubly fed induction generator, optimization, genetic algorithms 1 Introduction A distributed generator (DG) is a small generator (normally less than 15 MW) [1], scattered throughout an electric power distribution system to serve local loads. It is widely used in a renewable energy plant. The renewable plant has been increasingly installed due to several reasons: i) it can be located closer to customers, ii) high efficiency of modern distributed generating plants is available for a small size capacity of ranging from 10 kW – 15 MW, iii) it is required shorter installation time and cheaper investment cost, iv) it improves distribution reliability, etc [2]. The use of DG in the future requires distribution system engineers to take into account its impact in the system planning. To install a new DG at a particular location, investment and operating costs are very important in power distribution planning. Therefore, one of the planner’s goals is to minimize overall cost [3-5]. When the distribution power network structure is assumed to be invariable during the planning period, changes in load energy demand or the appearance of new loads over short period could require some action from existing reactive power equipment or investments for network upgrade might be necessary. In this circumstance, DG has a built-in function to inject desired reactive power to the grid at the point of connection. This leads to the advantage of reducing power losses and can be a valuable option for the planning engineer to reduce investments for the grid upgrade. However, their installation in non-optimal locations or sizing can result both in an increasing of power losses and in a reducing of reliability levels [6]. Analysis of reactive power control for distributed generators at a given location in order to determine an appropriate range of complex power exchanges indicates optimal sizing of DG installation. In this paper, a doubly fed structure of induction generators [7] is investigated. Determination of optimal DG rating is one of constrained optimization problems that can be solved by nonlinear optimization techniques such as sequential quadratic programming (SQP) or intelligent methods like genetic algorithms (GA) [8]. In this paper, Section 2 provides problem formulation of the reactive power planning problems. Brief of power distribution network and doubly fed induction generator models is also included. Section 3 gives solution methodology described step-by-step, particularly the exploitation of GA and the formulation of penalty function. Simulation results and conclusion are in Section 4 and 5, respectively. RECENT ADVANCES in ENERGY & ENVIRONMENT ISSN: 1790-5095 278 ISBN: 978-960-474-159-5