Type-II Fuzzy Credibility Constraints Programming Based Distribution Network Planning Including Photovoltaic Power Generation

Renewable energy generation is an important way for human society to achieve sustainable energy and economic development. However, renewable energy with high uncertainty brings a huge challenge to the stable operation of power systems when it is connected to the grid. Accurate and effective modeling...

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Veröffentlicht in:2024 4th International Conference on Energy Engineering and Power Systems (EEPS) S. 545 - 554
Hauptverfasser: He, Yingjing, Shen, Shuyi, Lou, Jing, Lu, Xinyi, Sun, Xinyu, Zheng, Lingwei
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 09.08.2024
Schlagworte:
Distribution network planning
Distribution networks
fuzzy credibility constrained programming
Load modeling
Optimization models
Particle swarm optimization
Photovoltaic systems
photovoltaic uncertainty
Planning
Power system stability
Programming
Renewable energy sources
type-II fuzzy sets
Uncertainty
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Zusammenfassung:Renewable energy generation is an important way for human society to achieve sustainable energy and economic development. However, renewable energy with high uncertainty brings a huge challenge to the stable operation of power systems when it is connected to the grid. Accurate and effective modeling of uncertainty in renewable energy is an important guarantee for achieving optimal planning and stable operation of distribution networks with high renewable energy penetration. Most existing research on uncertainty in distribution networks focuses on analyzing multiple uncertainties such as source and load, but most studies only provide a simple description of each type of uncertainty. Based on this, this article first introduces type-II fuzzy sets to better describe the uncertainty of photovoltaic (PV) under the influence of various external factors, constructs a substation location planning model based on type-II fuzzy Credibility Constrained Programming (T2FCCP). On this basis, a distribution network planning model based on type-II fuzzy Credibility Chance Constrained Programming (T2F3CP) is established. To solve the two models, Particle Swarm Optimization (PSO) and Discrete Particle Swarm Optimization (DPSO) are adopted respectively. Finally, a regional distribution network with 6 microgrids and 50 load points is used to validate the proposed model. The research results show that the T2FCCP and T2F3CP optimization models can effectively describe the uncertainty of PV in distribution network planning under high PV penetration, reduce the impact of uncertainty, and ensure the stable operation of distribution networks under high renewable energy penetration.
DOI:10.1109/EEPS63402.2024.10804536