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Enhanced state estimation and bad data identification in active power distribution networks using photovoltaic power forecasting
摘要： In view of the problems of insu?cient real-time measurements in active distribution networks, a state estimation method for active distribution networks is proposed based on the forecasting of photovoltaic (PV) power generation. First, the extreme learning machine (ELM) enhanced by the genetic algorithm (GA) is used to forecast the PV power generation. Second, the Gaussian mixture model (GMM) is used to model the forecasting error. The weighted mean of the forecasting error is used to correct the forecasting value of the PV power generation, and the weighted variance of the forecasting error is used as the basis for setting the pseudo measurement weight. Finally, the real-time measurements collected by the supervisory control and data acquisition (SCADA) system, the forecasted pseudo measurements, and the virtual measurements are used to estimate the state of the active distribution network using the weighted least square (WLS) algorithm. Through simulations in the IEEE 33-bus system, it is shown that the proposed model provides accurate and reliable pseudo measurements for the active distribution network, improves the redundancy of the system, and thus further improves the accuracy of the state estimation and the capability of detecting and identifying bad data in active distribution systems without adding measurement devices.
关键词： Gaussian mixture model,Bad data,Forecasting of photovoltaic power generation,Active distribution system,State estimation,Pseudo measurement
更新于2025-09-16 10:30:52
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Community energy business model evolution: A review of solar photovoltaic developments in England
摘要： The ongoing energy system transformation process is placing citizens and communities at the heart of future energy systems. To date, their participation has focused on the ownership and control of renewable energy installations facilitated by supportive national policies. Yet across many European countries, policies that have previously supported the deployment of small-scale renewable projects are being withdrawn. Social innovation and the evolution of business models are needed if citizen participation is to continue and succeed in this new policy landscape. At the same time, few business models stand still. This paper reviews the evolution of community energy business models in England to provide insights into the potential of community participation in the energy system post subsidies. Concentrating on community solar photovoltaic projects as the cornerstone technology, this review identifies and critique three archetypal business models as sequentially dominating English community renewable energy to date. Using insights from both Science and Technology Studies and Transaction Cost Economics, it explores the drivers and origin of these models as well as resulting community benefits. Looking forwards and by reviewing current activity, this paper identifies new intermediary actors as playing a key role in facilitating and brokering new, increasingly complicated and commercial community energy business models. We argue that this marks a significant break from the past and may, in time, offer more opportunities for community participation in energy system transformation. Moreover, it offers some communities the possibility of staying small and retaining their more radical potential.
关键词： Solar photovoltaic,Power purchase agreements,Intermediaries,Transaction costs,Community energy,Business models
更新于2025-09-16 10:30:52
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Fixed- and variable-frequency sliding mode controller–maximum power point tracking converter for two-stage grid-integrated photovoltaic system employing nonlinear loads with power quality improvement features
摘要： This article presents a reliable and efficient photovoltaic sliding mode voltage-controlled maximum power point tracking DC-DC converter–active power filter integration system to supply real power to grid. This integrated active power filter system performs power quality enhancement features to compensate current harmonics to make distortion-free grid supply current and reactive power employing nonlinear loads. The proposed proportional–integral–derivative–based sliding mode controller is designed with fixed-frequency pulse-width modulation based on equivalent control approach. The main objective of this paper is to design a photovoltaic system with a new sliding surface to force the photovoltaic voltage to follow the reference maximum power point voltage with the alleviation of slow transient response and disadvantages of chattering effects of variable-frequency hysteresis modulation sliding mode controller–maximum power point tracking. The perturbations caused by the uncertainties in climatic conditions and converter output bulk oscillations during grid integration are also mitigated. The features of the proposed photovoltaic–active power filter integration system are confirmed at different operating conditions through PSIM simulation software, and its performance is also compared with a conventional variable-frequency sliding mode-controlled maximum power point tracking. The obtained simulation and experimental results give good dynamic response under various operating conditions of environmental and local load conditions.
关键词： sliding mode controller,pulse-width modulation,photovoltaic,power quality,active power filter,Maximum power point tracking,high step-up DC-DC converter
更新于2025-09-12 10:27:22
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Probabilistic small signal stability analysis of power system with wind power and photovoltaic power based on probability collocation method
摘要： Recently, with increasing improvements in the penetration of wind power and photovoltaic power in the world, probabilistic small signal stability analysis (PSSSA) of a power system consisting of multiple types of renewable energy has become a key problem. To address this problem, this study proposes a probabilistic collocation method (PCM)-based PSSSA for a power system consisting of wind farms and photovoltaic farms. Compared with the conventional Monte Carlo method, the proposed method meets the accuracy and precision requirements and greatly reduces the computation; therefore, it is suitable for the PSSSA of this power system. Case studies are conducted based on a 4-machine 2-area and New England systems, respectively. The simulation results show that, by reducing synchronous generator output to improve the penetration of renewable energy, the probabilistic small signal stability (PSSS) of the system is enhanced. Conversely, by removing part of the synchronous generators to improve the penetration of renewable energy, the PSSS of the system may be either enhanced or deteriorated.
关键词： Probabilistic small signal stability,Renewable energy,Wind power,Photovoltaic power,Probabilistic collocation method
更新于2025-09-12 10:27:22
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[IEEE 2019 Chinese Control And Decision Conference (CCDC) - Nanchang, China (2019.6.3-2019.6.5)] 2019 Chinese Control And Decision Conference (CCDC) - Tracking the Maximum Power Point of Photovoltaic Power Generation Based on Self-coding Neural Network
摘要： The current and voltage of photovoltaic power generation system constantly are changed by the external temperature and radiation, which can lead to the constant change in the maximum power point of photovoltaic power generation. To resolve this problem, we propose a novel method based on the self-encoding neural network technology which is applied to the maximum power point tracking of photovoltaic power generation. The method is based on the deep learning network training of stacking encoders and fine-tuning the self-coding neural network which utilizes the reverse propagation method with supervised learning. Finally the model analysis of photovoltaic power generation system is carried out by MATLAB/simulink environment. The results show that this method can track the maximum power point of photovoltaic power more quickly and accurately than the conventional conductance increment method and improve the efficiency of photovoltaic power generation.
关键词： Photovoltaic Power Generation,Maximum Power Point Tracking,Self-encoding Neural Network
更新于2025-09-12 10:27:22
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[IEEE 2019 IEEE Energy Conversion Congress and Exposition (ECCE) - Baltimore, MD, USA (2019.9.29-2019.10.3)] 2019 IEEE Energy Conversion Congress and Exposition (ECCE) - Synchronous Frequency Support of Photovoltaic Power Plants with Inertia Emulation
摘要： Grid stability is one of the main concerns in renewable energies. The lack of inertia and their low capability to provide frequency support has created the need for implementing new control strategies to solve this problem. In current networks, frequency and voltage support are performed through synchronous generators, which provide an inherent grid support due to the inertia presented in their mechanical rotors. Based on the same concept, renewable energies based on power converters have introduced synchronous controllers to emulate the dynamic behavior of synchronous generators and provide voltage and frequency support. However, most synchronous control strategies integrate their controllers as an add-on firmware embedded in each power converter, without presenting a coordinated synchronous performance when several converters operate in a PV power plant. The aggregation of several power converters operating with a coordinated synchronous response would be advantageous in these cases, since they can provide a harmonic response with an automatic power distribution when grid support is required. This paper presents a synchronous control strategy for photovoltaic power plants, which manages several power converters as an aggregated synchronous system.
关键词： Grid frequency support,Photovoltaic Power Plants,Synchronous Power Control
更新于2025-09-12 10:27:22
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Diffusion charge compensation strategy for power balancing in capacitor-less photovoltaic modules during partial shading
摘要： Photovoltaic arrays are highly susceptible to the partial shading that drastically reduces the power output by forming multiple peaks in the characteristics curves complicating the operation of maximum power point trackers (MPPTs). In this paper, a new diffusion charge compensation strategy for power enhancement in the arrays during partial shading has been proposed. The strategy eliminates the requirement of bypass diodes and passive energy storage components and uses the inherent diffusion capacitance of the module for power balancing during shading reducing cost and complexity. The strategy has been tested in MATLAB/Simulink environment and validated experimentally under various partial shading scenarios. The proposed strategy increases the power output and improves the tracking efficiency of the MPPTs by forming single maxima in the characteristics curves of the array during partial shading as compared to the conventional arrays with and without bypass diodes. Also, the proposed strategy excels in performance by increasing the power output of arrays during partial shading with a conversion efficiency of nearly 98%.
关键词： Photovoltaic,Power generation,Partial shading,Diffusion capacitance,Maximum power point tracker,Charge compensation
更新于2025-09-12 10:27:22
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[IEEE 2019 4th International Conference on Intelligent Green Building and Smart Grid (IGBSG) - Hubei, Yi-chang, China (2019.9.6-2019.9.9)] 2019 4th International Conference on Intelligent Green Building and Smart Grid (IGBSG) - Research on Efficiency Improvement Strategy of A New Type of Photovoltaic Power Generation Conversion System
摘要： With the increasingly prominent environmental problems, the proportion of photovoltaic in distributed power supply is increasing. In this paper, a new tracking method of solar maximum power point is proposed, which can keep the system in the position of maximum power point, and build on Matlab/Simulink simulation model to proposed method is verified.
关键词： Power generation conversion,Photovoltaic power generation,MPPT control
更新于2025-09-12 10:27:22
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Improvement of maximum power point tracking (MPPT) efficiency using grey wolf optimization (GWO) algorithm in photovoltaic (PV) system
摘要： Photovoltaics are becoming very popular, because the system does not produce pollution and can be installed anywhere, including in remote areas. However, in the use of photovoltaic found some common problems, it is difficult to get maximum and stable power. Therefore, to overcome these problems using Maximum Power Point Tracking method. On a photovoltaic system it is necessary to determine which converter will be used to increase the power output of the photovoltaic. The design of MPPT using gray wolf optimization algorithm that can track the output power quickly and reduce the oscillation in photovoltaic system. The result of the maximum power tracker using the gray wolf optimization algorithm is better than the incremental conductance algorithm of up to 0,4 s. Converters are used using soft-switching buck converter method to overcome the power losses that often arise in PV systems. The result of power output using soft-switching buck converter is greater than using buck converter. When comparing the efficiency of photovoltaic systems using the gray wolf optimization algorithm increases from using the incremental conductance algorithm.
关键词： photovoltaic,power,converter,MPPT
更新于2025-09-12 10:27:22
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Prediction of Photovoltaic Power Generation Based on General Regression and Back Propagation Neural Network
摘要： Based on the general regression (GR) and back propagation (BP) neural network prediction method, this work forecasts the generated power of photovoltaic (PV) power station. First, the Pearson correlation coefficient method was used to analyze the meteorological factors. The degree of correlation between complex weather factors and PV power output was differentiated and the irradiance and battery temperature were selected as the important influencing variables. Second, the weather was classified according to the certain classification criteria. Then, we established the model by using GR and BP neural network prediction methods. The relative errors were within acceptable limits. The former model is more convenient while the latter model has better nonlinear fitting capacity. The results of the two models are compared and analyzed. We find out that the BP neural prediction method have better prediction results than GR method on PV power generation. Our findings can not only provide valuable information for the optimal dispatching of micro-grid and photovoltaic power, but also be of great significance in energy management and hierarchical control of micro-grid.
关键词： back propagation neural network,photovoltaic power generation,general regression neural network,Pearson correlation coefficient
更新于2025-09-12 10:27:22