Modeling the output power of PV farms for power system adequacy assessment

Author(s):  
Samer Sulaeman ◽  
Mohammed Benidris ◽  
Joydeep Mitra
2013 ◽  
Vol 448-453 ◽  
pp. 1727-1731
Author(s):  
Xi Yun Yang ◽  
Li Xia Li ◽  
Ya Min Zhang

The DC bus voltage is key variable for the operation of converter system in a wind power system. When grid voltage drops, a control of the DC bus voltage is needed to keep the smoothness of DC bus voltage for avoiding generator cutting off grid. A combined control method based on the grid voltage information feedforward with a crowbar circuit is proposed for a direct-drive wind power system in the paper. The unbalanced energy of the DC bus can be unleashed by the crowbar circuit during the dropping of grid voltage. At the same time, the output power of motor-side converter can be controlled to decrease according to the grid-side voltage information, and the mechanical speed of wind turbine and generator can be suppressed by the pitch angle regulation when the output power reduces. Thus, the DC-bus voltage can keep smooth. Results based on Matlab/Simulink simulation shows that this method not only improves dynamic response performance of DC bus voltages control, but also reduces the action time of crowbar circuit. It is benefit to the ability of the wind power system riding through the grid fault.


2013 ◽  
Vol 860-863 ◽  
pp. 2083-2087
Author(s):  
Xian Jun Qi ◽  
Jia Yi Shi ◽  
Xiang Tian Peng

Probability box (P-box) and interval probability (IP) were used to express both variability and imprecision of wind speed and output power of WTGs. The p-box of WTG's output power was constructed by empirical cumulative distribution function and K.S. confidence limits. The discrete IP distribution of WTG's output power was elicited from the p-box. The optimization model of imprecise generating capacity adequacy assessment incorporating wind power was established and solved by genetic algorithm (GA). Case study on RBTSW system shows the rationality of presented method.


2020 ◽  
Vol 8 (6) ◽  
pp. 4447-4452

Today’s power systems era is speedily going towards natural sources of power. The power system is also in the mode of decentralization. Decentralize means to split a large power system into small, safe and smart power grid or to create microgrid. This decentralization required separate control of each part of the power system. It can reduce the complexity of the large power system; provide efficient and economical installation and easy operation. To keep our globe healthy; green sources of electrical energy like solar, wind tidal, biomass are the best option for the power sector. Integrating green power sources in a decentralized power system needs better planning and upgraded technology. To deal with uncertainties of Green power sources, the first step is to estimate output power. In this paper output power with the uncertain nature of sources is estimated and analyzed to integrating green power sources. For it, the statistic model of solar and wind power generation has been discussed. Probable distribution of wind speed and solar irradiation is found using available mean data. Output power Generation of wind and solar sources are estimated based on the probability distribution curve and power equation. It has analyzed for different value of shape parameter Here mean wind speed and mean solar irradiation data of one town of Gujarat state, India has been collected for the planning of microgrid.


2021 ◽  
Vol 11 (23) ◽  
pp. 11332
Author(s):  
Imran Haseeb ◽  
Ammar Armghan ◽  
Wakeel Khan ◽  
Fayadh Alenezi ◽  
Norah Alnaim ◽  
...  

The load pressure on electrical power system is increased during last decade. The installation of new power generators (PGs) take huge time and cost. Therefore, to manage current power demands, the solar plants are considered a fruitful solution. However, critical caring and balance output power in solar plants are the highlighted issues. Which needs a proper procedure in order to minimize balance output power and caring issues in solar plants. This paper investigates artificial neural network (ANN) and hybrid boost converter (HBC) based MPPT for improving the output power of solar plants. The proposed model is analyzed in two steps, the offline step and the online step. Where the offline status is used for training various terms of ANNs in terms of structure and algorithm while in the online step, the online procedure is applied with optimum ANN for maximum power point tracking (MPPT) using traditional converter and hybrid converter in solar plants. Moreover, a detail analytical framework is studied for both proposed steps. The mathematical and simulation approaches show that the presented model efficiently regulate the output of solar plants. This technique is applicable for current installed solar plants which reduces the cost per generation.


2020 ◽  
Author(s):  
Aulia Indana ◽  
Dharu Arseno ◽  
Edwar ◽  
Adilla Safira

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