This paper completely introduces an exhaustive and a comprehensive review of the so-called salp swarm algorithm (SSA) and discussions its main characteristics. SSA is one of the efficient recent meta-heuristic optimization algorithms, where it has been successfully utilized in a wide range of optimization problems in different fields, such as machine learning, engineering design, wireless networking, image processing, and power energy. This review shows the available literature on SSA, including its variants, like binary, modifications and multi-objective. Followed by its applications, assessment and evaluation, and finally the conclusions, which focus on the current works on SSA, suggest possible future research directions.

Salp swarm algorithm: a comprehensive survey

The grasshopper optimization algorithm is one of the dominant modern meta-heuristic optimization algorithms. It has been successfully applied to various optimization problems in several fields, including engineering design, wireless networking, machine learning, image processing, control of power systems, and others. We survey the available literature on the grasshopper optimization algorithm, including its modifications, hybridizations, and generalization to the binary, chaotic, and multi-objective cases. We review its applications, evaluate the algorithms, and provide conclusions.

A comprehensive survey of the Grasshopper optimization algorithm: results, variants, and applications

Grasshopper Optimization Algorithm (GOA) is a recent swarm intelligence algorithm inspired by the foraging and swarming behavior of grasshoppers in nature. The GOA algorithm has been successfully applied to solve various optimization problems in several domains and demonstrated its merits in the literature. This paper proposes a comprehensive review of GOA based on more than 120 scientific articles published by leading publishers: IEEE, Springer, Elsevier, IET, Hindawi, and others. It provides the GOA variants, including multi-objective and hybrid variants. It also discusses the main applications of GOA in various fields such as scheduling, economic dispatch, feature selection, load frequency control, distributed generation, wind energy system, and other engineering problems. Finally, the paper provides some possible future research directions in this area.

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Grasshopper Optimization Algorithm: Theory, Variants, and Applications

Salp Swarm Algorithm (SSA) is a recent metaheuristic inspired by the swarming behavior of salps in oceans. SSA has demonstrated its efficiency in various applications since its proposal. In this chapter, the algorithm, its operators, and some of the remarkable works that utilized this algorithm are presented. Moreover, the application of SSA in optimizing the Extreme Learning Machine (ELM) is investigated to improve its accuracy and overcome the shortcomings of its conventional training method. For verification, the algorithm is tested on 10 benchmark datasets and compared to two other well-known training methods. Comparison results show that SSA based training methods outperforms other methods in terms of accuracy and is very competitive in terms of prediction stability.

Salp swarm algorithm: Theory, literature review, and application in extreme learning machines

To accomplish feasible large-scale integration of distributed energy resources (DER) into the existing grid system, microgrid implementation has proven to be the most effective. This article reviews the vital aspects of DER based microgrid and presents simulations to investigate the impacts of DER sources, electric vehicles (EV), and energy storage system (ESS) on practicable architectures’ resilient operation. The focus is primarily on the concept and definition of microgrid, comparison of control strategies (primary, secondary, and tertiary strategies), energy management strategies, power quality (PQ) issues associated with DER based microgrid, and state-of-the-art entities such as ESS and EV's applications toward microgrid reliability. Following discussion on the different attributes of DER sources-based microgrid, simulations are performed to verify the results of the past works on the effects of solar, wind energy sources, ESS, and EVs on the microgrid frequency response. Additional simulations are conducted to assess the influences of DERs, ESS, EVs, and their operational strategies on the microgrid reliability aspects.

Distributed Energy Resources Based Microgrid: Review of Architecture, Control, and Reliability

This work endeavours to propose an approximate mathematical model of a community based renewable microgrid with solar photovoltaic, biogas and biodiesel generators including battery storage for load frequency studies. It becomes a great challenge to coordinate between generation and load demand of the microgrid as the renewable sources are highly unpredictable and nature dependent. To overcome this issue, the responses of the system are studied under different real-world scenarios of renewable source availabilities and load variations with a maiden approach towards optimising the controller gains using a recent grasshopper optimisation algorithm (GOA) for efficient frequency control. The frequency responses of proposed microgrid are compared with different conventional controllers and some popular optimisation algorithms using MATLAB/Simulink. Finally, proportional-integral-derivative controller with GOA is preferred for the case studies under four cases of source variations with step load perturbation and one case of simultaneous source and load variations. The results of all these five scenarios are found satisfactory in terms of frequency responses and reported in the work.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-rpg.2018.5196

Expeditious frequency control of solar photovoltaic/biogas/biodiesel generator based isolated renewable microgrid using grasshopper optimisation algorithm

This is an earliest attempt to study the effective regulation of load-frequency oscillations due to the penetration of renewable generations in bio-renewable cogeneration based hybrid microgrids with demand response (DR) support considering optimal utilisation of resources. The work is a maiden attempt to derive the linearised model of a medium-sized linear-Fresnel-reflector type solar-thermal power unit for load-frequency study in the proposed wind/micro-hydro/biogas/biodiesel generator-based hybrid microgrids, modelling suitable DR strategies for both isolated and interconnected modes. The proposed systems are simulated using MATLAB/Simulink for coordinated source/demand-side management, proposing a novel quasi-oppositional selfish-herd optimisation algorithm in both the modes, incorporating real-time recorded solar/wind data and realistic random loads. Firstly, the oscillations due to renewable-penetrations are reduced efficiently in the isolated microgrid incorporating biodiesel generator and DR supports. Then the study is further extended for interconnected two-unequal hybrid microgrids considering resource availabilities. The system responses are compared in four extreme scenarios of source variations, as well as three variations of DRs without retuning the controllers to study the adaptability of the proposed system. Finally, the system frequency oscillations are regulated satisfactorily by DR support for both the modes.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-gtd.2019.0166

Proficient load-frequency regulation of demand response supported bio-renewable cogeneration based hybrid microgrids with quasi-oppositional selfish-herd optimisation

This study endeavours an effective frequency control of renewable-based isolated two-area interconnected microgrid (ICμG) without battery, incorporating wind power generation in area-1, dish-Stirling solar power generation system in area-2 and other common distributed generation systems such as diesel engine driven generator, plug-in hybrid electric vehicle, heat pump and freezer in both the areas. A recently developed heuristic optimisation technique called water cycle algorithm (WCA) is applied to optimally tune the parameters of the non-integer fractional-order proportional-integral-derivative (FOPID) controllers employed with ICμG. Application of WCA-based FOPID controllers in frequency control two-area ICμG without battery is a novel work. The comparative performance analysis of proportional-integral-derivative (PID), PID with filter and non-integer order-based FOPID controller with their gains tuned by particle swarm optimisation (PSO), improved PSO, firefly algorithm and WCA algorithms indicates the superiority of WCA-based FOPID controller's under different case studies (considering different load disturbances, wind speed variation with real data, and solar irradiance) in terms of frequency deviation, tie-line power, and objective function. Furthermore, the sensitivity analysis contemplates that WCA-optimised FOPID controller can withstand ±25% change in synchronising coefficient, +20% change in loading condition and ±25% change in frequency bias constant without resetting the gain values.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-rpg.2018.5419

Comparative performance evaluation of WCA‐optimised non‐integer controller employed with WPG–DSPG–PHEV based isolated two‐area interconnected microgrid system

Coordinated regulation of voltage and load frequency in demand response supported biorenewable cogeneration‐based isolated hybrid microgrid with quasi‐oppositional selfish herd optimisation

The world energy requirement has skyrocketed radically in the past two decades raising concern over energy security and adequacy. Energy resource planning plays a substantial role in the global eco...

Amar Kumar Barik

Papers

Expeditious frequency control of solar photovoltaic/biogas/biodiesel generator based isolated renewable microgrid using grasshopper optimisation algorithm

Proficient load-frequency regulation of demand response supported bio-renewable cogeneration based hybrid microgrids with quasi-oppositional selfish-herd optimisation

Comparative performance evaluation of WCA‐optimised non‐integer controller employed with WPG–DSPG–PHEV based isolated two‐area interconnected microgrid system

Coordinated regulation of voltage and load frequency in demand response supported biorenewable cogeneration‐based isolated hybrid microgrid with quasi‐oppositional selfish herd optimisation

Recent trends and development in hybrid microgrid: a review on energy resource planning and control