A novel power flow analysis in an islanded renewable microgrid Abdolreza Esmaeli a , Mohammad Abedini b , Mohammad H. Moradi c, * a Plasma and Nuclear Fusion Research School, Nuclear Science and Technology Research Institute, Tehran, Iran b Faculty of Engineering, Department of Electrical Engineering, Ayatollah Borujerdi University, Broujerd, Iran c Faculty of Engineering, Department of Electrical Engineering, Bu-Ali Sina University, Hamedan, Iran article info Article history: Received 11 July 2015 Received in revised form 24 March 2016 Accepted 25 April 2016 Keywords: Microgrid Load flow GPSO-GM Wind power Renewable abstract In an islanded microgrid mode the use of conventional power flow analysis is not effective as the voltage of slack bus and the frequency of the microgrid are assumed to be constant. Such assumption fails to consider the real characteristics of the island microgrid as all DGs are involved in providing the demand of active and reactive power as well as in maintaining the frequency of the microgrid. In this paper, a novel algorithm, named GPSO-GM (Guaranteed convergence Particle Swarm Optimization with Gaussian Mutation), for the power flow analysis problem in an islanded microgrid is proposed. The problem is modeled without any slack bus by considering steady state frequency as one of the power flow variables. To model different control modes of DGs, such as droop, PV and PQ, in an islanded microgrid, a new formula for power flow equations is developed. PSO is adopted to minimize the mismatch of total active and reactive power. Two operators, mutation and guaranteed convergence, are added to PSO in order to help in finding an optimal solution and to assist in increasing the speed of the proposed algorithm as well as the accuracy of the results. The performance of proposed load flow based on GPSO-GM is compared with the PSO, Newton-trust and time domain methods. The results provide support for the validity of GPSO-GM. © 2016 Elsevier Ltd. All rights reserved. 1. Introduction A microgrid is seen as an interconnection of distributed gener- ations (DGs) which is integrated with electrical and thermal loads as well as energy storages, and it operates as a single small scale system in low-voltage distribution systems. In microgrids, power quality, reliability and security can be increased by the use of power electronic interfaces and controls [1,2]. A microgrid might operate in grid-connected or islanded modes. In a grid-connected mode, the voltage and frequency of microgrids are dictated by the main grid while in an islanded mode control units of DGs along with managing active and reactive power are responsible for frequency and voltage regulation. A control strategy for microgrids might be designed in different forms such as centralized, decentralized, and distributed; any combination of such forms is also possible. Centralized control strategies require transferring of remarkable data in a reliable communication environment. This is appropriate for small microgrids where DGs are relatively close together [3e5]. Comparing with small microgrids, large microgrids with a large geographic domain might be controlled by decentralized strategies, such as droop control, as considerable communication is not required in large microgrids [2]. Locally measured variables, in droop control schemes, might be used for sharing of load demand among DGs effectively. This is to control the frequency and voltage of microgrids [6]. In practice, as DGs might be connected to microgrids via power electronic devices [7,8] designing an appropriate control strategy for electronic devices is essential [9,10]. To design an effective control strategy, a power flow analysis model, also known as a steady state analysis model, is required, particularly in the case of an islanded microgrid. 2. Literature review Typically, power flow analysis of an electric power system in- volves computing the voltage of nodes and the amount of power flow through lines of a given load profile. A number of studies have proposed different power flow analysis models to address charac- teristics of distribution systems and microgrids, including high R/X * Corresponding author. E-mail addresses: aesmaeli@aeoi.org.ir (A. Esmaeli), m.abedini@abru.ac.ir, m_ abedini_dr@yahoo.com (M. Abedini), mh_moradi@yahoo.co.uk (M.H. Moradi). Contents lists available at ScienceDirect Renewable Energy journal homepage: www.elsevier.com/locate/renene http://dx.doi.org/10.1016/j.renene.2016.04.077 0960-1481/© 2016 Elsevier Ltd. All rights reserved. Renewable Energy 96 (2016) 914e927