Output Power Of Photovoltaic Plant Research Articles

A Bi-Level Control Strategy for PV-BES System Aiming at the Minimum Operation Cost of BES

With the increased penetration of the photovoltaic (PV) energy, the power system stability problem becomes an issue, as the output power of PV plants has unpredictable fluctuations. To maintain the power stability of the PV plants, battery energy storages (BESs) play an important role due to their fast and accurate response speed. However, it is challenging that the BES with multiple sub-modules responds well to the PV power fluctuations resulting from the various influence factors, such as defects, faults, and partial shading. Therefore, a bi-level control strategy is proposed in this paper, aiming at minimizing the operation cost of BES in maintaining power stability. The control strategy consists of the PV power fluctuations identification block and the mitigation block. In specific, the identification block can output the power fluctuation of a PV system by the PV power fluctuation identification technique. The technique is developed based on the characteristics of PV-string current under electrical faults and partial shading conditions. Meanwhile, the mitigation block can manage the multiple battery sub-modules with different regulation characteristics to meet the power fluctuations. At last, the promising results are obtained by MATLAB\Simulink with the coordinated operation of those two blocks, including the precise condition of the PV system and the optimal power output of each battery sub-module. Therefore, a comprehensive bi-level control strategy is developed to regulate the operation of battery sub-modules for PV-BES systems.

On-Line Diagnosis and Fault State Classification Method of Photovoltaic Plant

This paper presents an on-line diagnosis method for large photovoltaic (PV) power plants by using a machine learning algorithm. Most renewable energy output power is decreased due to the lack of management tools and the skills of maintenance engineers. Additionally, many photovoltaic power plants have a long down-time due to the absence of a monitoring system and their distance from the city. The IEC 61724-1 standard is a Performance Ratio (PR) index that evaluates the PV power plant performance and reliability. However, the PR index has a low recognition rate of the fault state in conditions of low irradiation and bad weather. This paper presents a weather-corrected index, linear regression method, temperature correction equation, estimation error matrix, clearness index and proposed variable index, as well as a one-class Support Vector Machine (SVM) method and a kernel technique to classify the fault state and anomaly output power of PV plants.

Structured, physically inspired (gray box) models versus black box modeling for forecasting the output power of photovoltaic plants

Two advanced models for forecasting the output power of photovoltaic plants are discussed in details: a black-box Takagi-Sugeno fuzzy model and a physically inspired, semiparametric statistical model (Generalized Additive Model, GAM) based on smoothing splines. The structure of the two models, their strengths and weaknesses, are presented. The models performance is thoroughly compared with the performance of a simple linear model tested under the frame of the European Cooperation in Science and Technology (COST) Action “Weather Intelligence for Renewable Energies”, as a benchmark used also in the forecasting exercise reported in Sperati et al. Energies 8 (2015) 9594. The models are used to forecasting the output power at time horizons of 1–72 h ahead. The data used during the COST competition are used here as input. The present study extends beyond the traditional evaluation of overall model accuracy. Detailed influences of seasonal effects, sun elevation angle and solar irradiance level upon the models performance are assessed. While the accuracy of the simple linear model is not entirely bad, it differs in important details from the two advanced forecasting models. The results show that a moderate, carefully chosen increase in model structure complexity can improve the predictive performance. Suitable penalty on model complexity can help both to enforce parsimony and improve practical forecasting abilities, to a certain extent. The physically inspired GAM comes out as the best performing model.

Optimal configuration of energy storage system based on frequency hierarchical control in ship power system with solar photovoltaic plant

This study presents the results of hybrid energy storage system (HESS) and improved maximum power point tracking (MPPT) algorithm simulation analysis undertaken to improve the smoothing performance of solar photovoltaic (PV) plant installed in the ship power system. Frequency hierarchical control algorithm is used to assign high-frequency oscillation part to the supercapacitor and low-frequency oscillation part to the battery. Meanwhile, improved MPPT algorithm is also used to limit the maximum output power of PV plant, which can reduce the necessary installed capacity of HESS further. The effectiveness of the proposed method was verified under a typical ship power system model.

Impact of large‐scale photovoltaic generation integration structure on static voltage stability in China's Qinghai province network

Large-scale photovoltaic (PV) generations are integrated into China's Qinghai province network and challenging the system stability. This study focuses on static voltage stability analysis of Qinghai grid in consideration of high-penetration PV generation. The test system is based on the practical network structure of Qinghai grid. Different practical PV integration structures are, respectively, studied by discussing the influences of transmission line length, output power of PV plant and reactive power compensation capacity on system static voltage stability. The authors also compared different PV integration structures to study the effect of topology on static voltage stability. Simulation results are performed in the practical network structure of Qinghai grid. The analysis results can be used to provide guidance for system modification and thereby improve the system operation stability.