Reactive power dispatch in wind farms using particle swarm optimization technique and feasible solutions search Marcela Martinez-Rojas a,⇑ , Andreas Sumper a,b,c , Oriol Gomis-Bellmunt a,b,c , Antoni Sudrià-Andreu a,b,c a Centre d’Innovació Tecnològica en Convertidors Estàtics i Accionaments (CITCEA-UPC), Departament d’Enginyeria Elèctrica, Universitat Politècnica de Catalunya, EU d’Enginyeria Tècnica Industrial de Barcelona, C. Comte d’Urgell, 187, Pl. 2, 08036 Barcelona, Spain b Centre d’Innovació Tecnològica en Convertidors Estàtics i Accionaments (CITCEA-UPC), Departament d’Enginyeria Elèctrica, Universitat Politècnica de Catalunya, ETS d’Enginyeria Industrial de Barcelona, Av. Diagonal, 647, Pl. 2, 08028 Barcelona, Spain c IREC, Catalonia Institute for Energy Research, C. Josep Pla, 2, edifici B2, Planta Baixa, 08019 Barcelona, Spain article info Article history: Received 20 October 2010 Received in revised form 2 June 2011 Accepted 4 June 2011 Available online 1 July 2011 Keywords: Wind farm Reactive power compensation Particle swarm optimization abstract In this paper, an optimization method for the reactive power dispatch in wind farms (WF) is presented. Particle swarm optimization (PSO), combined with a feasible solution search (FSSPSO) is applied in order to optimize the reactive power dispatch, taking into consideration the reactive power requirement at point of common coupling (PCC), while active power losses are minimized in a WF. The reactive power requirement at PCC is included as a restriction problem and is dealt with feasible solution search. Finally an individual set point, particular for each wind turbine (WT), is found. The algorithm is tested in a WF with 12 WTs, taking into consideration different control options and different active power output levels. Ó 2011 Elsevier Ltd. All rights reserved. 1. Introduction Nowadays, the amount of wind power has reached important penetration rates in power systems. Due to this growth, power sys- tems have greater control requirements, meaning that wind farms (WF) have to meet such control needs, mainly voltage or reactive power control [1,2] and frequency control [3–5]. Recent technology development has made it possible for WF to participate in power system control and support tasks, similar to conventional power plants [6,7]. Therefore, Transmission System Operators (TSO) in different countries have been working to integrate control requirements for WFs into their grid codes [8–10]. The necessity of control capa- bilities at WF level is an important and determinant characteristic. Active and reactive power controls have to be carried out by the WF with the aim of fulfilling the principal TSO voltage and fre- quency control requirements. In most grid codes, a voltage level in PCC is required and it is defined through a power factor require- ment [11]. In the Irish case, for the automatic voltage regulation, the WF should be capable of receiving a voltage regulation set point at PCC and should act to regulate it, adjusting the reactive power output [12]. Currently, the most common technology used is the doubly fed induction generator (DFIG), which is able to provide reactive power support. A large variety of control strategies can be used in the operation of DFIG [13]. Nevertheless, an internal WF optimization procedure to manage the wind turbines’ (WTs) reactive power sup- port is needed, taking into account WT and WF characteristics [14]. The need to optimize generation has been studied for different purposes and by using several methods [15,16]. In Refs. [17,18] optimization is used in network capacity analysis. An specifically reactive power control problems have been handled with optimiza- tion techniques. A method of finding the optimal reactive power distribution in a power system is presented in Ref. [19]. The method considers transformer taps, generator voltages and switchable VAR sources. The application showed be an useful tool to assist the sys- tem operator to take control decisions to improve the voltage pro- files and minimize the system losses. The problem of locating and sizing capacitors for reactive power compensation in electric radial distribution networks was proposed as a multi-objective program- ming problem presented in Ref. [20]. In Ref. [21] fuzzy adaptive PSO (FAPSO) has been used to solve an optimization problem and deter- mine the reactive power distribution between different available equipments. An optimization algorithm based on a Chaotic Im- proved Honey Bee Mating Optimization (CIHBMO) applied in the daily volt/var control in distribution networks is proposed and tested in Ref. [22]. Since the end of the twentieth century, new optimization tech- niques have been studied, using the analogy of animal swarm behavior. In Ref. [23], an ant colony optimization was developed. Eberhart and Kennedy developed a particle swarm optimization (PSO), based on the swarm behavior of birds or fish [24]. Recently, this new technique has been used in power system controls [25]; 0306-2619/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.apenergy.2011.06.010 ⇑ Corresponding author. Tel.: +34 934137432; fax: +34 934017433. E-mail address: marcela.martinez@citcea.upc.edu (M. Martinez-Rojas). Applied Energy 88 (2011) 4678–4686 Contents lists available at ScienceDirect Applied Energy journal homepage: www.elsevier.com/locate/apenergy