Multi-objective PSO based optimal placement of solar power DG in radial distribution system

Mahesh Kumar1*, Perumal Nallagownden2, Irraivan Elamvazuthi3 J. Electrical Systems 13-2 (2017): 322-331 Regular paper Multi-objective PSO based optimal placement of solar power DG in radial distribution system JES Journal of Electrical Systems Ever increasing trend of electricity demand, fossil fuel depletion and environmental issues request the integration of renewable energy into the distribution system. The optimal planning of renewable distributed generation (DG) is much essential for ensuring maximum benefits. Hence, this paper proposes the optimal placement of probabilistic based solar power DG into the distribution system. The two objective functions such as power loss reduction and voltage stability index improvement are optimized. The power balance and voltage limits are kept as constraints of the problem. The non-sorting pareto-front based multi-objective particle swarm optimization (MOPSO) technique is proposed on standard IEEE 33 radial distribution test system. Keywords: Distributed generation, solar PV module, distribution system, multi-objective PSO. Article history: Received 19 March 2017, Accepted 11 May 2017 1. Introduction Worldwide, the demand for electricity, risk for fossil fuel depletion and environmental issues are increasing. Hence, the renewable based power generation (i.e. wind turbine, solar PV, biomass, micro-turbine etc.) are feasible options in the distribution system. Among the renewable based power generation, there is an increasing trend of power generation from solar based DGs. Because it is non-exhaustible and freely available in nature. It is also noticeable that distribution system is radial in nature, which possesses high resistance to reactance ratio and draws more power loss and decreases the voltage quality of the system [1, 2]. In this case, optimal integration of solar DG advances many benefits, i.e. increase the power losses reduction, improve voltage profile and voltage stability index [3]. It also reduces the greenhouse gas effects and defers the network upgradation. Many positive benefits can be claimed from DG integration. However, the integration of distributed generation in distribution system witnesses to change the operational and control behaviour of the distribution network. Such as non-optimal placement may worsen the situation than existing one. Hence, an efficient optimal placement method is required to overcome these complexities and improve the system performance [4]. In literature, many optimization algorithms are used to overcome these operational complexities and optimally fit the DGs into the distribution system. Among them, analytical, numerical and heuristic based optimization algorithms are most effectively utilized [5]. Author [6, 7] uses the analytical expressions for optimal placement and sizing of distributed generation for power loss reduction and voltage profile improvement in the radial distribution system. The author [8, 9] uses the linear and non-linear programming to optimize the system * Corresponding author: Mahesh Kumar, Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS Bandar Seri Iskandar, Perak Darul Ridzuan, Malaysia. 1 Department of Electrical Engineering, Mehran University of Engineering and Technology Jamshoro, Sindh, Pakistan. E-mail: ; Tel.: +60-149851338. 123 Department of Electrical and Electronics Engineering, Universiti Teknologi PETRONAS Bandar Seri Iskandar, Perak Darul Ridzuan, Malaysia. Copyright © JES 2017 on-line : journal/esrgroups.org/jes J. Electrical Systems 13-2 (2017): 322-331 parameters in the distribution system. The GA, PSO and GA/PSO based multi-objective optimization for power loss reduction and voltage stability improvement are suggested by the author [10]. Flower pollination optimization algorithm [11], big bang crunch based [12], GA and backtracking search optimization algorithm based optimization algorithm [13] for optimal DG integration were proposed in the literature. Among, the author [8, 14] uses the solar based distributed generation in distribution system using non-linear and flower pollinating based optimisation algorithm. However, this paper proposes an advance, paretofront non-dominated sorting based multi-objective PSO optimization for power loss reduction and voltage stability improvement. The proposed model is tested and verified against many literature methods with standard IEEE 33 test system. The reminder of the paper is structured as, Section II presents the problem formulation, section III presents the output power form solar power DG, Section IV presents the multiobjective PSO optimization algorithm, Section IV present the case study, results and discussion and Section V presents the conclusion. 2. Problem formulation The main objective function this study is to optimally allocate the solar power DG into the radial distribution system. The two main objective functions such as power loss reduction and voltage stability index improvement are optimized. Furthermore, the study considers the power balance and minimum and maximum voltage magnitudes as constraints of the problem. 2.1. Power loss reduction It is fact that distribution system consists of about thirteen percent power losses from the total power generation as reported in [15]. Hence, the first objective of this study is to reduce the power losses. A backward forward power flow is utilized to calculate the diffident electrical parameters [16]. The power loss reduction using optimal integration of solar power DG can be formulated as following. i = nb −1 f1 = min( ∑ Pi loss ) (1) i =1 where ܲ௜௟௢௦௦ is the real power loss of branch ݅, ܾ݊ is total number of branches of the system. 2.2. Voltage Stability index The voltage stability index (VSI) is an indicator, which shows the stability of the system or in other terms it can be explained as when the load in the distribution system increases, it reduces the voltage profile of the system. Hence, it is ought to maintain the VSI index in the permissible limit. A lower value of VSI (i.e. lower than the base case) indicates the abnormality in the system, whereas greater values indicate the maximum stability in the system [17]. The voltage stability index for two buses m1 and m2 can be formulated as follows given in Figure 1: 323 M. Kumar et al: M-O PSO based optimal placement of solar power DG in radial dist. Sys.... Figure 1. One-line diagram of the two-bus radial distribution system. 2 VSIm2 = Vm1 4 Pm2 × X i − 2 − 4.0   − 4.0{Pm2 × Ri + Qm2 × X i } Vm1 Qm2 × Ri  (2) Nb f 2 = max ∑(VSImi ) ' (3) mi where ܸܵ‫ܫ‬௠ଶ is the voltage stability index for bus number 2, ܸܵ‫ܫ‬௠௜ is the voltage stability index for all buses that are connecting the system such as (݉݅ = 2, 3, 4 … ܾܰ), Nb is the total number of buses. The voltage stability index is kept as second objective function for this paper. The objective function can be written as:  1  f2 =  '   f 2 (4) 2.3. Network Constraints (...truncated)