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A spatiotemporal probabilistic model-based temperature-augmented probabilistic load flow considering PV generations
摘要： The probabilistic steady‐state forecasting of a PV‐integrated power system requires a suitable forecasting model capable of accurately characterizing the uncertainties and correlations among multivariate inputs. The critical and foremost difficulties in the development of such a model include the accurate representation of the characterizing features such as complex nonstationary pattern, non‐Gaussianity, and spatial and temporal correlations. This paper aims at developing an improved high‐dimensional multivariate spatiotemporal model through enhanced preprocessing, transformation techniques, principal component analysis, and a suitable time series model that is capable of accurately modeling the trend in the variance of uncertain inputs. The proposed model is applied to the probabilistic load flow carried out on the modified Indian utility 62‐bus transmission system using temperature‐augmented system model for an operational planning study. A detailed discussion of various results has indicated the effectiveness of the proposed model in capturing the aforesaid characterizing features of uncertain inputs.
关键词： PV generation,probabilistic load flow,operational planning,spatiotemporal correlation,steady‐state forecasting
更新于2025-09-23 15:22:29
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Data-driven uncertainty analysis of distribution networks including photovoltaic generation
摘要： This paper investigates residential distribution networks with uncertain loads and photovoltaic distributed generation. An original probabilistic modeling of consumer demand and photovoltaic generation is presented that is based on the analysis of large set of data measurements. It is shown how photovoltaic generation is described by complex non-standard distributions that can be described only numerically. Probabilistic analysis is performed using an enhanced version of the Polynomial Chaos technique that exploits a proper set of polynomial basis functions. It is described how such functions can be generated from the numerically available data. Compared to other approximate methods for probabilistic analysis, the novel technique has the advantages of modeling accurately truly nonlinear problems and of directly providing the detailed Probability Density Function of relevant observable quantities affecting the quality of service. Compared to standard Monte Carlo method, the proposed technique introduces a simulation speedup that depends on the number of random parameters. Numerical applications to radial and weakly meshed networks are presented where the method is employed to explore overvoltage, unbalance factor and power loss, as a function of photovoltaic penetration and/or network configuration.
关键词： Photovoltaic generation,Data-driven models,Polynomial chaos,Unbalanced distribution networks,Probabilistic load flow,Uncertainty Analysis
更新于2025-09-23 15:21:01
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[IEEE 2018 China International Conference on Electricity Distribution (CICED) - Tianjin (2018.9.17-2018.9.19)] 2018 China International Conference on Electricity Distribution (CICED) - A Probabilistic Load Flow Method of Village-level Photovoltaicload Station Scaled Access to the Distribution Network
摘要： With the vigorous implementation of the PV Poverty Alleviation Policy, a large number of PV power plants have access to the rural distribution network, in order to accurately and comprehensively assess the influence of the uncertain and correlative factors of distributed photovoltaic for rural distribution networks, probabilistic load flow calculations are applied for rural distribution networks that consider the relevance of photovoltaic output. Based on the characteristics of PV output correlation, a probability distribution model with correlated probabilistic input variables was constructed using in hybrid Copula theory, and a cumulant probabilistic load flow calculation method based on Copula theory was proposed to consider the correlation of input variables. Through the IEEE-33 bus system and an actual distribution network simulation in Gansu Province, the simulation results show that the model can display the probability characteristics of photovoltaic power generation well, and the hybrid Copula function is more accurate than the single Copula function in dealing with correlation problems. The results are compared with the Monte Carlo method to verify the rapidity and accuracy of the proposed method.
关键词： Copula theory,photovoltaic,rural distribution network,cumulant method,probabilistic load flow
更新于2025-09-16 10:30:52
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Maximum Power Photovoltaic Units Penetration under Voltage Constraints Criteria in Distribution Network Using Probabilistic Load Flow
摘要： Nowadays, the connections of Renewable Energy Sources to Distribution Networks are increasing in large number. In order to assess the performance of Distribution Network under normal operating conditions Probabilistic Load Flow analysis is necessary in order to take into consideration the stochastic behavior of Load Demands and Renewable Energy Sources (for example the Photovoltaics Generation Units). Generally, Deterministic Load Flow calculations are typically needed to assess the allowed Distributed Generation penetration level for a given network in order to ensure, for example, that Voltage limits are not exceeded. The present paper deals with the Probabilistic Load Flow using Monte Carlo techniques. The developed program allows probabilistic predictions of Voltages profiles at all buses or nodes of a Distribution Networks. A practical case is also discussed to show the application of the study in order to assess the maximum Photovoltaic power penetration that can be installed into a Distribution Network without violating Voltage Constraints.
关键词： Distribution Network,Distributed Generation,Probabilistic Load Flow,Photovoltaic Units,Renewable Energy Sources
更新于2025-09-12 10:27:22