Optimal Sizing of Stand Alone Hybrid Renewable Energy System with Load Shifting

Kumar, Sanjay; Kaur, Tarlochan; Upadhyay, Subho; Sharma, Vivek; Vatsal, Deven

doi:10.1080/15567036.2020.1831107

Cited by 30 publications

(12 citation statements)

References 40 publications

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“…e HES, which consists of SPV, microhydro (MHP), and storage batteries, is thought to meet the needs of distant populations in India's western Himalayas. e accuracy and utility of the proposed method were demonstrated by testing the outcomes of these algorithms with HOMER [27].…”

Section: Introductionmentioning

confidence: 99%

Optimal Sizing of Hybrid Energy System Using Random Exploratory Search-Centred Harris Hawks Optimizer with Improved Exploitation Capability

Anand

Kamboj

Alaraj

et al. 2022

Mathematical Problems in Engineering

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Due to the depletion of traditional energy resources, emissions of greenhouse gases, climate change, etc., renewable energy resources (RER) based power generation is becoming the main source of the present and future power sector. The major RERs, including solar, wind, and small hydro, may provide reliable and sustainable solutions in the smart grid environment. Solar and wind energy-based power generation is more prevalent but varies in nature and is not even very predictable very efficiently. Therefore, it has become necessary to integrate two or more RER and develop a hybrid energy system (HES). The HESs provide a cost-effective and reliable power supply with reduced and/or almost negligible greenhouse gas emissions as well. Due to economic and power reliability concerns, the optimal sizing of components is necessary for the development of an optimum HES. In recent years, metaheuristic evolutionary algorithms have been widely used for optimal sizing of HES. Harris hawk’s optimizer (HHO) is a recently devised metaheuristics search method that has the ability to discover global minima and maxima. However, due to its weak exploitation capacity, the basic HHO algorithm’s local search is pretty slow and has a slow rate of convergence. Thus, to boost the exploitation phase of HHO, a new approach, random exploratory search centered Harris hawk’s optimizer (hHHO-ES), has been developed in the present work for optimal sizing of HES. The suggested approach is validated and compared to existing optimization approaches for a variety of well-known benchmark functions, including unimodal, multimodal, and fixed dimensions. Following this, it is used to develop HES, which will be capable of providing power to remote areas where grid supply is scarce. The objective function is formulated using net present cost (NPC) as a prime function under a set of constraints such as bounds of system components and reliability. The obtained results are compared with those from harmony search (HS) and particle swarm optimization (PSO) and found to be better.

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Section: Introductionmentioning

confidence: 99%

Optimal Sizing of Hybrid Energy System Using Random Exploratory Search-Centred Harris Hawks Optimizer with Improved Exploitation Capability

Anand

Kamboj

Alaraj

et al. 2022

Mathematical Problems in Engineering

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“…In this work, optimal switching intervals of several appliances were found, and the size of the HES was optimized after this. In a study [25], a model is proposed for the sizing optimization of the small HES based on a local resource assessment and demand side management. The load shifting process was performed by shifting the water pump load to the night hours.…”

Section: Introductionmentioning

confidence: 99%

Optimizing the Size of Autonomous Hybrid Microgrids with Regard to Load Shifting

2021

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The article proposes a method of multipurpose optimization of the size of an autonomous hybrid energy system consisting of photovoltaic, wind, diesel, and battery energy storage systems, and including a load-shifting system. The classical iterative Gauss–Seidel method was applied to optimize the size of a hybrid energy system in a remote settlement on Sakhalin Island. As a result of the optimization according to the minimum net present value criterion, several optimal configurations corresponding to different component combinations were obtained. Several optimal configurations were also found, subject to a payback period constraint of 5, 6, and 7 years. Optimizing the size of the hybrid power system with electric load shifting showed that the share of the load not covered by renewable energy sources decreases by 1.25% and 2.1%, depending on the parameters of the load shifting model. Net present cost and payback period also decreased, other technical and economic indicators improved; however, CO2 emissions increased due to the reduction in the energy storage system.

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“…Even though the integration of DGs provides numerous advantages, it leads to an indisputable problem called islanding. The process of DG units energizing the loads with the system detached from the grid is represented as islanding 1‐4 . The islanding has to be detected within a time of delay of 2 seconds as specified in IEEE 1547‐2018.…”

Section: Introductionmentioning

confidence: 99%

“…Because the voltage, current, and frequency are measured in distribution side itself, the passive methods are considered to ensure the quality of power and reduced NDZ. In passive method, the threshold limits are fixed to identify the islanding event 1‐7 . The passives methods, such as over‐voltage, over‐current, over‐frequency, under‐voltage, under‐current, and under‐frequency, intelligent‐based methods, and artificial neural network (ANN) are used for the detection of islanding.…”

Section: Introductionmentioning

confidence: 99%

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Islanding‐based reliability enhancement and power loss minimization by network reconfiguration using PSO with multiple DGs

Ramachandradurai

Kumarappan

2021

Int Trans Electr Energ Syst

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The distributed generation (DG) units are used more in the electrical networks to reduce the energy demand along with reducing the system losses and increasing the voltage profile of the load points. This paper presents an unintentional islanding detection, reliability enhancement, and power loss minimization of the restored system after an islanding event. The detection of islanding is performed by passive detection method of simultaneous measurement of voltage and frequency (vf)-based technique. The reliability of the system is increased along with the power loss minimization through reconfiguration by Particle Swarm Optimization (PSO) technique. The network reconfiguration is performed by identifying the most vulnerable buses, and reliability indices of the system are evaluated after the islanding event. The reliability indices act as a marker for validating the proposed reconfiguration strategy. The proposed method for islanding detection, reliability enhancement, and power loss minimization is compared with the existing methods available in the literature. The proposed method is tested on two different radial distribution system such as IEEE-69 and 118 bus systems, and the results obtained after the validation are promising.

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Optimal Sizing of Stand Alone Hybrid Renewable Energy System with Load Shifting

Cited by 30 publications

References 40 publications

Optimal Sizing of Hybrid Energy System Using Random Exploratory Search-Centred Harris Hawks Optimizer with Improved Exploitation Capability

Optimal Sizing of Hybrid Energy System Using Random Exploratory Search-Centred Harris Hawks Optimizer with Improved Exploitation Capability

Optimizing the Size of Autonomous Hybrid Microgrids with Regard to Load Shifting

Islanding‐based reliability enhancement and power loss minimization by network reconfiguration using PSO with multiple DGs

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