Optimal sizing of a wind/solar/battery/diesel hybrid microgrid based on typical scenarios considering meteorological variability

Yang, Duo; Jiang, Chao; Cai, Guowei; Huang, Nantian

doi:10.1049/iet-rpg.2018.5944

Cited by 41 publications

(20 citation statements)

References 33 publications

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“…The aerodynamic power coefficient of a wind turbine is a performance indicator, which is influenced by the blade pitch angle (β) and the tip-speed ratio (λ). A generic equation of C p based on the turbine characteristics is given by (2) [20][21][22][23][24][25][26][27][28][29]:…”

Section: Wind Turbine Characteristicsmentioning

confidence: 99%

Modelling, Design and Control of a Standalone Hybrid PV-Wind Micro-Grid System

Al-Quraan

Al-Qaisi

2021

Energies

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The problem of electrical power delivery is a common problem, especially in remote areas where electrical networks are difficult to reach. One of the ways that is used to overcome this problem is the use of networks separated from the electrical system through which it is possible to supply electrical energy to remote areas. These networks are called standalone microgrid systems. In this paper, a standalone micro-grid system consisting of a Photovoltaic (PV) and Wind Energy Conversion System (WECS) based Permanent Magnet Synchronous Generator (PMSG) is being designed and controlled. Fuzzy logic-based Maximum Power Point Tracking (MPPT) is being applied to a boost converter to control and extract the maximum power available for the PV system. The control system is designed to deliver the required energy to a specific load, in all scenarios. The excess energy generated by the PV panel is used to charge the batteries when the energy generated by the PV panel exceeds the energy required by the load. When the electricity generated by the PV panels is insufficient to meet the load’s demands, the extra power is extracted from the charged batteries. In addition, the controller protects the battery banks in all conditions, including normal, overcharging, and overdischarging conditions. The controller should handle each case correctly. Under normal operation conditions (20% < State of Charge (SOC) < 80%), the controller functions as expected, regardless of the battery’s state of charge. When the SOC reaches 80%, a specific command is delivered, which shuts off the PV panel and the wind turbine. The PV panel and wind turbine cannot be connected until the SOC falls below a safe margin value of 75% in this controller. When the SOC goes below 20%, other commands are sent out to turn off the inverter and disconnect the loads. The electricity to the inverter is turned off until the batteries are charged again to a suitable value.

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Section: Wind Turbine Characteristicsmentioning

confidence: 99%

Modelling, Design and Control of a Standalone Hybrid PV-Wind Micro-Grid System

Al-Quraan

Al-Qaisi

2021

Energies

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“…However, the total system cost was the only performance index to be optimised. Yang et al [23] proposed generation method including a wind-irradiation-load. This is to optimally size renewable energy resources in case of a microgrid.…”

Section: Literature Survey and Contributionsmentioning

confidence: 99%

“…The candidate solutions are competed based on a fitness function that is related to the HSI. A habitat H can be represented as in(23) [37]…”

mentioning

confidence: 99%

Hybrid energy system design using greedy particle swarm and biogeography‐based optimisation

Abuelrub

Khamees

Ababneh

et al. 2020

IET Renewable Power Generation

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Renewable energy systems (RESs) are affordable, clean and sustainable. However, their output power is intermittent. Therefore, RESs are usually combined with an energy storage system or conventional sources to make the overall operation uninterruptable. Optimal sizing of hybrid energy system components is imperative to be financially and technically feasible. In this study, a multi-objective optimisation based on a hybrid optimisation procedure, which combines the exploitation ability of the biogeography-based optimisation (BBO) with the exploration ability of the particle swarm optimisation (PSO), is used to handle the system design. This algorithm is known as greedy particle swarm and BBO algorithm (GPSBBO). Weighted sum method is added to the GPSBBO to handle the multi-objective nature of the design problem. A case study for a hybrid wind-PV energy system design in the standalone and grid-connected configurations is presented to illustrate the proposed method. Coverage of two sets, hypervolume and diversity performance indices are used to compare results of the proposed method to nondominated sorting genetic algorithm and the multi-objective PSO. These indices show an improved performance of the suggested method in finding the optimal system design.

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“…For the optimal sizing of renewable energy resources in microgrids, a method for generating wind speed, irradiation, and load scenarios was proposed in this study, which the researchers examined an energy management system to select the optimal configuration of the microgrid system using a teaching and learning based optimization (TLBO) method in [10].…”

Section: Introductionmentioning

confidence: 99%

Energy Management System for Hybrid Microgrids

Attou¹,

Zidi²,

Khatir³

et al. 2021

EEA

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Energy management in grid-connected Micro-grids (MG) has undergone rapid evolution in recent times due to several factors such as environmental issues, increasing energy demand and the opening of the electricity market. The Energy Management System (EMS) allows the optimal scheduling of energy resources and energy storage systems in MG in order to maintain the balance between supply and demand at low cost. The aim is to minimize peaks and fluctuations in the load and production profile on the one hand, and, on the other hand, to make the most of renewable energy sources and energy exchanges with the utility grid. In this paper, our attention has been focused on a Rule-based energy management system (RB EMS) applied to a residential multi-source grid-connected MG. A Microgrid model has been implemented that combines distributed energy sources (PV, WT, BESS), a number of EVs equipped with the Vehicle to Grid technology (V2G) and variable load. Different operational scenarios were developed to see the behaviour of the implemented management system during the day, including the random demand profile of EV users, the variation in load and production, grid electricity price variation. The simulation results presented in this paper demonstrate the efficacy of the suggested EMS and confirm the strategy's feasibility as well as its ability to properly share power among different sources, loads and vehicles by obeying constraints on each element.

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Optimal sizing of a wind/solar/battery/diesel hybrid microgrid based on typical scenarios considering meteorological variability

Cited by 41 publications

References 33 publications

Modelling, Design and Control of a Standalone Hybrid PV-Wind Micro-Grid System

Modelling, Design and Control of a Standalone Hybrid PV-Wind Micro-Grid System

Hybrid energy system design using greedy particle swarm and biogeography‐based optimisation

Energy Management System for Hybrid Microgrids

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