Modeling and multi-objective optimization of a stand-alone photovoltaic-wind turbine-hydrogen-battery hybrid energy system based on hysteresis band

Li, Zhe; Liu, Yuhan; Du, Mingpu; Cheng, Yonghong; Shi, Le

doi:10.1016/j.ijhydene.2022.11.196

Cited by 30 publications

(7 citation statements)

References 91 publications

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“…Li et al proposed a modelling and MOO method for an independent photovoltaic wind turbine hydrogen battery hybrid energy system based on hysteresis bands. It combines the net annual value of the system and the remaining electricity to construct an objective optimisation function, and uses the non dominated sorting genetic algorithm (GA) to solve the objective function, which can reduce the probability of power loss to 0.92% [13]. Sun et al reviewed the latest research on power system network security and proposed solutions to enhance grid security, including smart grid technology surveys, power industry practices and standards, solutions to network security issues, and unresolved issues [14].…”

Section: Related Workmentioning

confidence: 99%

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Modelling and Optimisation of Green Energy Systems Based on Complementary Integration of Renewable Energy, 1-9.

Mao,

Yang,

Gao

2024

International Journal of Power and Energy Systems

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This paper proposes a green energy system modelling and optimisation based on complementary integration of renewable energy, constructing an energy system model using solar energy, air energy, biomass energy, and distributed functional systems. And the objective optimisation function is constructed based on environmental friendliness, profitability, and energy utilisation efficiency as indicators. The results show that in mixed mode, the average annual environmental evaluation indicators of F before optimisation were 75.91%, while the average annual environmental evaluation indicators of M1, M2, and M3 after optimisation were 81.77%, 81.82%, and 82.53%, respectively. Research has shown that green energy system modelling and optimisation methods based on complementary integration of renewable energy can effectively solve energy and environmental problems, improve energy utilisation efficiency and environmental friendliness, and provide strong support for comprehensive decision-making of all parties in the power supply system.

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Section: Related Workmentioning

confidence: 99%

“…The amount of biogas required by the internal combustion engine and users at t is B t ice and B t user . The material balance of anaerobic digestion is (13).…”

Section: Moo Design Of Gesmentioning

confidence: 99%

Modelling and Optimisation of Green Energy Systems Based on Complementary Integration of Renewable Energy, 1-9.

Mao,

Yang,

Gao

2024

International Journal of Power and Energy Systems

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“…Foreign scholars have proposed various approaches to optimize power systems [5] . Among these, an energy management system employing time domain rolling optimization has been introduced [6] . While this method achieves economic efficiency in power system operation and management, it suffers from limitations related to continuous optimization, leading to suboptimal solutions [7] .…”

Section: Introductionmentioning

confidence: 99%

Power optimization and peak shaving strategies for offshore wind power and hydrogen production systems

Li,

Hu,

Yuan

et al. 2024

Ninth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2023)

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The capacity optimization configuration of offshore wind power and hydrogen production systems has traditionally focused on initial investment and cost-benefit analysis during the project construction lifecycle, neglecting considerations of scheduling economy in the system's actual operation. This article presents a novel approach to optimize the allocation mechanism of grid power and hydrogen production power in offshore wind farms with the aim of maximizing net income. The study employs simulations to assess the hydrogen production scenario for a 1000 MW Sheyang offshore wind power facility under various offshore distance scenarios across different seasons. Results indicate that peak shaving through electrolysis is most effective during autumn, yielding substantial benefits. Electrolysis cells can achieve peak shaving operation ranging from 6 MW to 300 MW, constituting 26.5% of the total electricity generated for hydrogen production.

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“…Throughout the most recent year, there has been a surge of diverse approaches dedicated to the optimization of HRES. These innovative methods and strategies have been documented in a range of references, including [39], [40], [41], [42], [43], [44], and [45]. This dynamic landscape of research reflects the ongoing efforts to enhance the efficiency and performance of HRES.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Hybrid Renewable Energy Systems:Novel Models and Heuristic Algorithms

Hosseini,

Al-Ghaili,

Deveci

et al. 2024

Preprint

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In practical applications, real-world challenges ofteninvolve the integration of multiple renewable energy sources,including solar, wind, hydro, biomass, geothermal, and energystorage solutions like batteries. The primary objective ofthese integrated systems is to optimize energy production,enhance system reliability, and simultaneously minimize costssuch as those associated with fossil fuels and greenhouse gasemissions. Therefore, it is crucial to model these complexproblems as all objectives are covered. In this paper, wepropose multi-objective and multi-level mathematical modelsfor Hybrid Renewable Energy Systems (HRESs). These modelsallow us to simultaneously address various objectives andlevels of decision-making in the context of renewable energyintegration. Then, to effectively tackle these complex models,the paper introduces two efficient hybrid algorithms for bothmulti-level and multi-objective models. First algorithm is acombined smoothing approach to address multi-level problem.The algorithm uses Karush-Kuhn-Tucker (KKT) conditions,some mathematical principles and proofs, and a heuristicfunction to smooth the multi-level model. Finally, the algorithmemploys Taylor approximation to further refine the smoothedproblem. The second algorithm, focuses on multi-objective model,which involves two phases: first, a heuristic algorithm simplifiesobjective functions through interpolation; second, the populationis enhanced using the Laying Chicken Algorithm (LCA); and aneural network refines the best LCA generation to identify thePareto front in multi-objective problems.

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Modeling and multi-objective optimization of a stand-alone photovoltaic-wind turbine-hydrogen-battery hybrid energy system based on hysteresis band

Cited by 30 publications

References 91 publications

Modelling and Optimisation of Green Energy Systems Based on Complementary Integration of Renewable Energy, 1-9.

Modelling and Optimisation of Green Energy Systems Based on Complementary Integration of Renewable Energy, 1-9.

Power optimization and peak shaving strategies for offshore wind power and hydrogen production systems

Optimizing Hybrid Renewable Energy Systems:Novel Models and Heuristic Algorithms

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