Expeditious frequency control of solar photovoltaic/biogas/biodiesel generator based isolated renewable microgrid using grasshopper optimisation algorithm
01 Oct 2018-Iet Renewable Power Generation (The Institution of Engineering and Technology)-Vol. 12, Iss: 14, pp 1659-1667
TL;DR: An approximate mathematical model of a community based renewable microgrid with solar photovoltaic, biogas and biodiesel generators including battery storage for load frequency studies is proposed and proportional-integral-derivative controller with GOA is preferred for the case studies.
Abstract: 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.
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TL;DR: This work surveys the available literature on the grasshopper optimization algorithm, including its modifications, hybridizations, and generalization to the binary, chaotic, and multi-objective cases.
Abstract: 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.
157 citations
TL;DR: A comprehensive review of GOA based on more than 120 scientific articles published by leading publishers: IEEE, Springer, Elsevier, IET, Hindawi, and others is presented in this article.
Abstract: 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.
98 citations
TL;DR: A review of different controllers utilized in traditional as well as renewable energy-based power system for LFM such as; classical controllers, fractional order controllers, cascaded controllers, sliding mode controller (SMC), tilt-integral-derivative controllers, H-infinity controller and other recently developed controllers are provided.
84 citations
TL;DR: This 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.
Abstract: 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.
68 citations
61 citations
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TL;DR: A literature review on biodiesel production, combustion, performance and emissions is presented in this article, where a vast majority of the scientists reported that short-term engine tests using vegetable oils as fuels were very promising but the longterm test results showed higher carbon built up and lubricating oil contamination resulting in engine failure.
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