Multi-objective optimization of solar thermal photovoltaic hybrid power generation system based on NSGA-II algorithm

Meng, Liang; Zhou, Weiqing; Li, Yang; Liu, Zhibin; Liu, Yajing

doi:10.1051/matecconf/202133602022

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…The NSGA-II algorithm finds extensive use across various fields, particularly in power electronics, where it effectively tackles multi-objective optimization problems in solar photovoltaic power generation [9]. This algorithm employs the elite strategy to rank and compete parent and offspring solutions, yielding improved genes for generating the next population.…”

Section: Three-phase Optimization Methods Considering Voltage Over-li...mentioning

confidence: 99%

Advances in stability control methods of distribution network for distributed photovoltaic systems

Zhang

2024

J. Phys.: Conf. Ser.

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In the current global energy crisis, distributed photovoltaic power generation represents an innovative approach to integrated power generation and energy utilization, offering significant prospects for development. However, the distribution network’s stability may be impacted by the connection to the grid of distributed solar power generation, which will significantly affect consumers’ demand for electricity. Therefore, this paper explores several control methods for grid stability in distributed photovoltaic systems, including a multi-objective optimization method of three-phase load imbalance with distributed photovoltaic distribution network considering voltage over-limit risk, three-phase voltage imbalance compensation control method based on parallel inverters of photovoltaic micro-grid in dq coordinate system and distributed cooperative control method based on dynamic event-triggered robust average consensus algorithm (DET-RACA) and barrier Lyapunov function (BLF). The paper evaluates these control methods, discussing their respective advantages, limitations, and impact on grid stability. Additionally, the latest research trends in these areas are reviewed, providing valuable insights for future studies focused on enhancing distribution network stability in the context of distributed photovoltaic power generation.

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Section: Three-phase Optimization Methods Considering Voltage Over-li...mentioning

confidence: 99%

Advances in stability control methods of distribution network for distributed photovoltaic systems

Zhang

2024

J. Phys.: Conf. Ser.

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“…The system is composed of photovoltaic array [6,7], fuel cell, electrolytic cell, short-term energy storage unit and energy control unit, etc., which can mainly convert solar radiation into electric energy and convert it into DC or AC electricity for human use through multiple links, so as to ensure the stability and safety of power supply.…”

Section: Design Of Optimization Scheduling Methods Of Solar Photovolt...mentioning

confidence: 99%

Optimization Scheduling Method of Solar Photovoltaic and Fuel Cell Combined Power Generation System

Xue

Zheng

Duan³

2022

SPEE

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The performance of the battery used in the traditional solar photovoltaic power generation system is poor, and the solar energy has a certain volatility, which makes the performance of the solar photovoltaic power generation system decline significantly. In order to improve the performance of the solar photovoltaic power generation system, a solar photovoltaic fuel cell combined power generation system has been developed. However, there are some problems in the process of traditional combined generation system optimal scheduling, such as high investment cost and total cost, and short generation time of optimal scheduling scheme. This paper takes solving the problems of traditional system optimal scheduling as the research goal, a new optimization scheduling method of solar photovoltaic and fuel cell combined power generation system was designed. The composition and topological structure of the solar photovoltaic fuel cell combined power generation system are analyzed. The system is composed of photovoltaic array, fuel cell, electrolytic cell, short-term energy storage unit and energy control unit. It can mainly convert sunlight radiation into electric energy, and convert it into DC or AC used by people through multiple links, so as to ensure the stability and security of power supply in our country. A scheduling model is established according to the photovoltaic cell power generation model, the fuel cell power generation model, the electrolytic hydrogen production model, the battery model, the power conversion model and the combined power generation system model. And the multi-objective cuckoo algorithm is used to solve the model, the optimization scheduling results of solar photovoltaic fuel cell combined power generation system are obtained. The experimental results show that the total investment cost of this method is reduced by 123678.4 yuan and 175858.7 yuan compared with the experimental comparison method, and the total cost is reduced by 301195.5 yuan and 414991.8 yuan compared with the experimental comparison method. It shows that compared with the experimental comparison method, the total investment cost and total cost of this method are lower, and the generation time of the optimal scheduling scheme is between 0.19s and 0.25s, and the practical application effect is good. It fully solves the problems existing in the traditional methods and has certain application significance.

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“…This paper focuses on the multi-objective optimization configuration of the cold, heat, and power supply systems with landscape storage. A model is developed for optimal allocation of multiple objectives, considering economic and environmental protection objectives [11] .The Enhanced NSGA-II algorithm is employed to solve the multi-objective challenge, and validation is conducted through integration with the operational system in western Liaoning to demonstrate the effectiveness of the proposed approach.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective optimization of an integrated energy system based on enhanced NSGA-II

Zhao,

Xiao,

Yang

et al. 2024

J. Phys.: Conf. Ser.

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To solve the energy crisis, China has made great efforts to develop an integrated energy system to achieve multi-energy coordination, mutual aid, energy conservation, and carbon reduction. This article mainly studies the multi-objective optimization scheduling problem of a combined cooling, heating, and power system considering wind and solar energy storage. Firstly, from two different perspectives of economy and carbon emissions, an economic objective function and an environmental objective function are established, and a multi-objective optimization configuration model and corresponding constraint conditions for the combined cooling, heating, and power system considering wind and solar energy storage are constructed. Then, an enhanced non-dominated sorting genetic algorithm II (NSGA-II) is proposed, which enhances the efficiency and accuracy of the algorithm by introducing dominance strength and variance factors. Finally, a simulation analysis was conducted on a running cogeneration system in a certain area of western Liaoning to attest to the validity of the model and method proposed in this paper.

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Multi-objective optimization of solar thermal photovoltaic hybrid power generation system based on NSGA-II algorithm

Cited by 3 publications

References 8 publications

Advances in stability control methods of distribution network for distributed photovoltaic systems

Advances in stability control methods of distribution network for distributed photovoltaic systems

Optimization Scheduling Method of Solar Photovoltaic and Fuel Cell Combined Power Generation System

Multi-objective optimization of an integrated energy system based on enhanced NSGA-II

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