scholarly journals Exploring the Regulation Reliability of a Pumped Storage Power Plant in a Wind–Solar Hybrid Power Generation System

Water ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 2548
Author(s):  
Beibei Xu ◽  
Jingjing Zhang ◽  
Mònica Egusquiza ◽  
Junzhi Zhang ◽  
Diyi Chen ◽  
...  

In the coming decades, the proportion of wind–solar energy in power system significantly increases, resulting to uncertainties of power fluctuation in abundant wind–solar energy regions. The flexibility operation of Pumped Storage Power Plants (PSPPs) has already been widely recognized to regulate wind–solar power fluctuations; however, less is known about the regulation reliability of the PSPP affected by them. It is a challenge, since various uncertainties exist during this regulation process. Here, a mathematical model with a solar–wind–hydro hybrid power generation system is adopted to investigate the regulation reliability of PSPP. The uncertainties and limitations of model parameters are considered during this process. Five regulation indexes, i.e., rise time, settling time, peak value, peak time and overshoot of the reactive power generator terminal voltage, guide vane opening and angular velocity, are extracted to evaluate the PSSP’s regulation quality. Finally, the PSPP reliability probability affected by parametric uncertainties is presented. The obtained results show that the inertia coefficient is the most sensitivity parameters for the settling time, peak value and peak time with sensitivity index 33.7%, 72.55% and 71.59%, respectively. The corresponding total contribution rate of the top 10 sensitive parameters are 74.45%, 93.45% and 87.15%, respectively. Despite some types of uncertainties not being considered, the results of this research are important for the regulation reliability evaluation of PSPPs in suppressing power fluctuations of wind and solar generation.

2020 ◽  
pp. 014459872095974
Author(s):  
Ahmed N Abdalla ◽  
Muhammad Shahzad Nazir ◽  
MingXin Jiang ◽  
Athraa Ali Kadhem ◽  
Noor Izzri Abdul Wahab ◽  
...  

Generating systems are known as adequately reliable when satisfying the load demand. Meanwhile, the efficiency of electrical systems is currently being more influenced by the growing adoption of the Wind/Solar energy in power systems compared to other conventional power sources. This paper proposed a new optimization approach called Metaheuristic Scanning Genetic Algorithm (MSGA) for the evaluation of the efficiency of power generating systems. The MSGA is based on a combination of metaheuristic scanning and Genetic Algorithm. The MSGA technique is used for evaluating the reliability and adequacy of generation systems integrated with wind/Solar energy is developed. The usefulness of the proposed algorithm was tested using Reliability Test System ‘IEEE-RTS-79’ which include both of wind power and solar power generation. The result approve the effectiveness of the proposed algorithm in improving the computation time by 85% and 2% in comparison with the particle swarm optimization (PSO) and differential evolution optimization algorithm (DEOA) respectively. In addition, the proposed model can be used to test the power capacity forecasting scheme of the hybrid power generation system with the wind, solar and storage.


2016 ◽  
Vol 40 (6) ◽  
pp. 717-725 ◽  
Author(s):  
Yuzheng Lu ◽  
Bin Zhu ◽  
Jun Wang ◽  
Yaoming Zhang ◽  
Junjiao Li

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2809 ◽  
Author(s):  
Yumin Xu ◽  
Yansheng Lang ◽  
Boying Wen ◽  
Xiaonan Yang

In recent years, wind and photovoltaic power (PV) have been the renewable energy sources (RESs) with the greatest growth, and both are commonly recognized as the major driving forces of energy system revolution. However, they are characterized by intermittency, volatility and randomness. Therefore, their stable and efficient implementation is one of the most significant topics in the field of renewable energy research. In order to improve the stability of RESs and reduce the curtailment of wind and solar energy, this paper proposes an innovative planning method for optimal capacity allocation. On one hand, a new power generation system is introduced which combines a pumped storage power station with a wind farm and PV; on the other hand, the sequential Monte Carlo method is utilized to analyze the economy and reliability of the system under different capacity configurations considering investment cost, operating characteristics and influence factors of wind and solar energy. Then, optimal capacity allocation can be achieved. In summary, this proposed scheme provides an effective solution for the planning and construction of a new power generation system with RESs.


2005 ◽  
Vol 151 (3) ◽  
pp. 8-18 ◽  
Author(s):  
Shigehiro Yamamoto ◽  
Kazuyoshi Sumi ◽  
Eiichi Nishikawa ◽  
Takeshi Hashimoto

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