Design and energy management optimization for hybrid renewable energy system- case study: Laayoune region

Mellouk, Lamyae; Ghazi, Mohamed; Aaroud, Abdessadek; Boulmalf, Mohammed; Benhaddou, Driss; Zine-Dine, Khalid

doi:10.1016/j.renene.2019.02.066

Cited by 57 publications

(16 citation statements)

References 38 publications

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“…The hybrid system is scheduled under a novel parallel hybrid genetic algorithm-particle swarm optimization algorithm (P-GA-PSO) to minimize energy cost and energy losses and maximizing renewable energy production. Indeed, the results improve that the obtained energy cost does not surpass 0.17 US$/kWh, which is close to the fossil fuel energy cost, and the applied strategy has good performance in terms of simulation time and solution quality [17]. In [18], the study proposes a novel technique for HGT PV/WT/battery system to minimize the purchased energy from the grid as well as maximize the profit from RE and battery sales.…”

Section: Introductionmentioning

confidence: 93%

Optimum Energy Flow Management of a Grid-Tied Photovoltaic-Wind-Battery System considering Cost, Reliability, and CO2 Emission

Azaroual

Ouassaid

Maâroufi

2021

International Journal of Photoenergy

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The main goal of this paper is to explore the performance of a residential grid-tied hybrid (GTH) system which relies on economic and environmental aspects. A photovoltaic- (PV-) wind turbine- (WT-) battery storage system with maximizing self-consumption and time-of-use (ToU) pricing is conducted to examine the system efficiency. In so doing, technical optimization criteria with taking into consideration renewable energy benefits including feed-in-tariff (FIT) and greenhouse gas emission (GHG) reduction are analyzed. As the battery has a substantial effect on the operational cost of the system, the energy management strategy (EMS) will incorporate the daily operating cost of the battery and the effect of the degradation. The model can give the opportunity to the network to sell or purchase energy from the system. The simulation results demonstrate the effectiveness of the proposed approach in which the new objective function achieves the maximum cost-saving (99.81%) and income (5.16 $/day) compared to other existing strategies as well as the lowest GHG emission. Furthermore, the battery enhances the best daily self-consumption and load cover ratio. Then, as the model is nonlinear, a comparison with other existing algorithms is performed to select the feasible, robust, and reliable model for the residential application. A hybrid algorithm (HGAFMINCON) is developed to demonstrate the superiority of the algorithm over FMINCON and GA shown in terms of cost savings and income.

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Section: Introductionmentioning

confidence: 93%

Optimum Energy Flow Management of a Grid-Tied Photovoltaic-Wind-Battery System considering Cost, Reliability, and CO2 Emission

Azaroual

Ouassaid

Maâroufi

2021

International Journal of Photoenergy

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“…Mazzola et al [33] proposed a framework to determine the optimal energy scheduling of isolated rural MGs considering forecast-based dispatch in the MGs operation using a normalized root-mean-square error approach. Mellouk et al [34] formulated an optimization technique based on a genetic algorithm-particle swarm optimization algorithm to determine the optimal energy management of a grid-connected MG in Laayoune region. Ramli et al [35] formulated a multi-objective self-adaptive differential evolution algorithm to design and manage the energy of a grid-connected MG.…”

Section: Grid−tmentioning

confidence: 99%

“…The output power of the MT, FC, PV, and WT should be within their specified limits as given in (31)- (34).…”

Section: ) Dg's Power Limitsmentioning

confidence: 99%

Robust Energy Management and Economic Analysis of Microgrids Considering Different Battery Characteristics

et al. 2020

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This paper presents the economic analysis and optimal energy management of a grid-connected MG that comprises renewable energy resources and different battery storage technologies with different characteristics such as initial charge, depth of discharge, and the number of charging/discharging cycles to minimize the total operating cost of the system by maximizing the benefits of BSS, minimizing the investment and replacement cost of BSS, and minimizing the operation and maintenance cost of DGs. Several constraints are considered, such as the output power limits of the distributed generators, the limits of power imported from or exported to the grid, load balance, and other sets of battery storage constraints. The general algebraic modeling system (GAMS) is used to solve the deterministic optimization problem. Second, stochastic optimization is used to solve the deterministic problem with market price uncertainty. Third, robust optimization using the information gap decision theory is presented to model the electric load uncertainty. The validity and effectiveness of the proposed solution are explained by comparing the results obtained by GAMS to the results obtained by other optimization techniques presented in the literature.

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“…The considered smaller scale grid is made for four diverse RE innovations and energy stockpiling framework. The destinations of both enhancement issues are to fulfill regular burden request, to limit energy creation cost, to amplify RE combination, to maintain a strategic distance from energy misfortunes and over-burden [27].…”

Section: Modeling and Optimization Techniques Used For Ressmentioning

confidence: 99%

Energy Management System for Hybrid Energy System: Renewable Integration, Modeling and Optimization, Control Aspects and Conceptual Framework

Kumari

Sharma

Singh

et al. 2020

Metaheuristic and Evolutionary Computation: Algorithms and Applications

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In developing Countries like India, the interest of energy has been expanding surprisingly because of the speculation of the agricultural, modern just as residence exercises. The rising an Earth-wide temperature boost marvels and an expansion in the consumption of petroleum derivatives has been the most crucial main thrust towards the thoughtfulness regarding misuse of Renewable Energy Sources. Alongside different favorable circumstances of these sources, there comes a heap of complexities connected to them because of their irregular and variable nature. Consequently, to maintain a strategic distance from these vulnerabilities it is important to give these assets appropriate planning and proper energy management. This work here a detailed study of different optimization techniques which can be applied to the renewable energy resources including the multi-agent solution as well as the Artificial Intelligence and Micro-grid controller which can offer a clear vision for the researchers in this field. Certain recommendations considering the challenges in renewable energy (RE) development are also been provided. In the proposed framework, the smart grid is optimized by the use of different optimization methods.

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Design and energy management optimization for hybrid renewable energy system- case study: Laayoune region

Cited by 57 publications

References 38 publications

Optimum Energy Flow Management of a Grid-Tied Photovoltaic-Wind-Battery System considering Cost, Reliability, and CO2 Emission

Optimum Energy Flow Management of a Grid-Tied Photovoltaic-Wind-Battery System considering Cost, Reliability, and CO2 Emission

Robust Energy Management and Economic Analysis of Microgrids Considering Different Battery Characteristics

Energy Management System for Hybrid Energy System: Renewable Integration, Modeling and Optimization, Control Aspects and Conceptual Framework

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