Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms.

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A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

An efficient salp swarm-inspired algorithm for parameters identification of photovoltaic cell models

This paper presents results obtained from monitoring a 1.72 kWp photovoltaic system installed on a flat roof of a 12 m high building in Dublin, Ireland (latitude 53.4°N and longitude 6.3°E). The system was monitored between November 2008 and October 2009 and all the electricity generated was fed into the low voltage supply to the building. Monthly average daily and annual performance parameters of the PV system evaluated include: final yield, reference yield, array yield, system losses, array capture losses, cell temperature losses, PV module efficiency, system efficiency, inverter efficiency, performance ratio and capacity factor. The maximum solar radiation, ambient temperature and PV module temperature recorded were 1241 W/m2 in March, 29.5 °C and 46.9 °C in June respectively. The annual total energy generated was 885.1 kW h/kWp while the annual average daily final yield, reference yield and array yield were 2.41 kW h/kWp/day, 2.85 kW h/kWp/day and 2.62 kW h/kWp/day respectively. The annual average daily PV module efficiency, system efficiency and inverter efficiency were 14.9%, 12.6% and 89.2% respectively while the annual average daily performance ratio and capacity factor were 81.5% and 10.1% respectively. The annual average daily system losses, capture losses and cell temperature losses were 0.23 h/day, 0.22 h/day and 0.00 h/day respectively. Comparison of this system with other systems in different locations showed that the system had the highest annual average daily PV module efficiency, system efficiency and performance ratio of 14.9%, 12.6% and 81.5% respectively. The PV system’s annual average daily final yield of 2.4 kW h/kWp/day is higher than those reported in Germany, Poland and Northern Ireland. It is comparable to results from some parts of Spain but it is lower than the reported yields in most parts of Italy and Spain. Despite low insolation levels, high average wind speeds and low ambient temperature improve Ireland’s suitability.

Measured Performance of a 1.72 kW Rooftop Grid Connected Photovoltaic System in Ireland

The coexistence of ac and dc subgrids in a hybrid microgrid is likely given that modern distributed sources can either be ac or dc. Linking these subgrids is a power converter, whose topology should preferably be not too unconventional. This is to avoid unnecessary compromises to reliability, simplicity, and industry relevance of the converter. The desired operating features of the hybrid microgrid can then be added through this interlinking converter. To demonstrate, an appropriate control scheme is now developed for controlling the interlinking converter. The objective is to keep the hybrid microgrid in autonomous operation with active power proportionally shared among its distributed sources. Power sharing here should depend only on the source ratings and not their placements within the hybrid microgrid. The proposed scheme can also be extended to include energy storage within the interlinking converter, as already proven in simulation and experiment. These findings have not been previously discussed in the literature, where existing schemes are mostly for an ac or a dc microgrid, but not both in coexistence.

Autonomous Control of Interlinking Converters with Energy Storages in Hybrid AC-DC Microgrids

Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application in unsupervised, complex multidimensional problems which cannot be solved using traditional deterministic algorithms. The canonical particle swarm optimizer is based on the flocking behavior and social co-operation of birds and fish schools and draws heavily from the evolutionary behavior of these organisms. This paper serves to provide a thorough survey of the PSO algorithm with special emphasis on the development, deployment and improvements of its most basic as well as some of the state-of-the-art implementations. Concepts and directions on choosing the inertia weight, constriction factor, cognition and social weights and perspectives on convergence, parallelization, elitism, niching and discrete optimization as well as neighborhood topologies are outlined. Hybridization attempts with other evolutionary and swarm paradigms in selected applications are covered and an up-to-date review is put forward for the interested reader.

Particle Swarm Optimization: A survey of historical and recent developments with hybridization perspectives

To reduce the frequency variation problem, here a novel controller is projected named as proportional derivative plus fractional order proportional integral (PD plus FOPI) controller. The newly designed controller is realised in a dual control area-based multi-unit model. The desired and suitable value of the parameter of the projected controller is obtained by salp swarm algorithm (SSA) concerning integral time absolute error (ITAE) as fitness or cost function. The designed multi-unit model is inspected with proportional integral derivative (PID), proportional derivative plus proportional integral (PD plus PI) and PD plus FOPI controller, and the dominance of the projected PD plus FOPI controller is established over others concerning different performance indices such as least undershoot, settling time and maximum overshoot. The system response is surveyed under two circumstances, namely (i) an abrupt load deviation of magnitude 0.01 per unit in control area 1 and (ii) abrupt load deviation of magnitude 0.06 per unit in control area 1. The later investigation also reveals that projected controller is robust as it can successfully manage the frequency abnormalities without further tuning the controller gains.

Automatic Generation Control Using Novel PD Plus FOPI Controller Tuned by Salp Swarm Algorithm

To provide an uninterrupted and quality power, isolated microgrids (MGs) are necessary. But, the isolated MGs are highly unstable to the power imbalance occurred between load and generation. In addition to this, intermittent uncertainties of the sources integrated in the MG force the power imbalance in the MG acutely. So, narrowing this power imbalance, the frequency deviation in the MG can be minimized in turn the stability of the system can be preserved. To reap such a response of a MG, an imperative control technique is obligatory. In this paper, an intelligent controller namely fuzzy-proportional-integral-derivative (FPID) is employed. The proposed controller is designed by symbiotic organism search (SOS) algorithm. In the proposed test model, various system parameters are varied and correspondingly, an unchanged stability in the MG has been observed which vows the robustness of FPID-controller. Again, the proposed test system is imposed with a magnified sporadic load which ascertains the potential of the controller to be more robust

Frequency Stability in an Isolated AC Microgrid using an intelligent Fuzzy Logic Based PID controller

Application of a novel metaheuristic algorithm based two-fold hysteresis current controller for a grid connected PV system using real time OPAL-RT based simulator

Binod Kumar Sahu

Papers

Automatic Generation Control Using Novel PD Plus FOPI Controller Tuned by Salp Swarm Algorithm

Frequency Stability in an Isolated AC Microgrid using an intelligent Fuzzy Logic Based PID controller

Application of a novel metaheuristic algorithm based two-fold hysteresis current controller for a grid connected PV system using real time OPAL-RT based simulator