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Ren, Zhouyang,Yan, Wei,Zhao, Xia,Zhao, Xueqian,Yu, Juan The Korean Institute of Electrical Engineers 2014 Journal of Electrical Engineering & Technology Vol.9 No.2
This paper presents a probabilistic power flow (PPF) analysis method for distribution network incorporating the randomness and correlation of photovoltaic (PV) generation. Based on the multivariate kernel density estimation theory, the probabilistic model of PV generation is proposed without any assumption of theoretical parametric distribution, which can accurately capture not only the randomness but also the correlation of PV resources at adjacent locations. The PPF method is developed by combining the proposed PV model and Monte Carlo technique to evaluate the influence of the randomness and correlation of PV generation on the performance of distribution networks. The historical power output data of three neighboring PV generators in Oregon, USA, and 34-bus/69-bus radial distribution networks are used to demonstrate the correctness, effectiveness, and application of the proposed PV model and PPF method.
Zhouyang Ren,Wei Yan,Xia Zhao,Xueqian Zhao,Juan Yu 대한전기학회 2014 Journal of Electrical Engineering & Technology Vol.9 No.2
This paper presents a probabilistic power flow (PPF) analysis method for distribution network incorporating the randomness and correlation of photovoltaic (PV) generation. Based on the multivariate kernel density estimation theory, the probabilistic model of PV generation is proposed without any assumption of theoretical parametric distribution, which can accurately capture not only the randomness but also the correlation of PV resources at adjacent locations. The PPF method is developed by combining the proposed PV model and Monte Carlo technique to evaluate the influence of the randomness and correlation of PV generation on the performance of distribution networks. The historical power output data of three neighboring PV generators in Oregon, USA, and 34-bus/69-bus radial distribution networks are used to demonstrate the correctness, effectiveness, and application of the proposed PV model and PPF method.
A Correlation Evaluation Method of PV Power Output Based on ITOPSIS
Xia Weiyi,Ren Zhouyang,Li Hui,Song Yue,Hu Xiuqiong,Hu Bo 대한전기학회 2022 Journal of Electrical Engineering & Technology Vol.17 No.4
Based on the Improved Technique for Order Preference by Similarity to an Ideal Solution (ITOPSIS), an evaluation method is proposed to quantify the contribution of each photovoltaic (PV) plant on the randomness and sequential characteristics of regional PV power. It can provide valuable information for the operators and planners of power systems, as well as the dealers in electricity market. First, a correlation index system is constructed to evaluate the correlation between the power outputs of individual PV plants and the regional PV power. Next, ITOPSIS is proposed to synthesize the proposed indices. Group standardization and theoretical optimal value avert the decrease of diff erence between plants and make the results applicable for comparing correlations in diff erent cluster. The historical data collected from 16 PV plants were used to verify the eff ectiveness and correctness of the proposed method
Cui, Wei,Yan, Wei,Lee, Wei-Jen,Zhao, Xia,Ren, Zhouyang,Wang, Cong The Korean Institute of Electrical Engineers 2017 Journal of Electrical Engineering & Technology Vol.12 No.1
The increasing of wind power penetration level presents challenges in classical optimal reactive power dispatch (ORPD) which is usually formulated as a deterministic optimization problem. This paper proposes a two-stage stochastic programming model for ORPD by considering the uncertainties of wind speed and load in a specified time interval. To avoid the excessive operation, the schedule of compensators will be determined in the first-stage while accounting for the costs of adjusting the compensators (CACs). Under uncertainty effects, on-load tap changer (OLTC) and generator in the second-stage will compensate the mismatch caused by the first-stage decision. The objective of the proposed model is to minimize the sum of CACs and the expected energy loss. The stochastic behavior is formulated by three-point estimate method (TPEM) to convert the stochastic programming into equivalent deterministic problem. A hybrid Genetic Algorithm-Interior Point Method is utilized to solve this large-scale mixed-integer nonlinear stochastic problem. Two case studies on IEEE 14-bus and IEEE 118-bus system are provided to illustrate the effectiveness of the proposed method.
Wei Cui,Wei Yan,Wei-Jen Lee,Xia Zhao,Zhouyang Ren,Cong Wang 대한전기학회 2017 Journal of Electrical Engineering & Technology Vol.12 No.1
The increasing of wind power penetration level presents challenges in classical optimal reactive power dispatch (ORPD) which is usually formulated as a deterministic optimization problem. This paper proposes a two-stage stochastic programming model for ORPD by considering the uncertainties of wind speed and load in a specified time interval. To avoid the excessive operation, the schedule of compensators will be determined in the first-stage while accounting for the costs of adjusting the compensators (CACs). Under uncertainty effects, on-load tap changer (OLTC) and generator in the second-stage will compensate the mismatch caused by the first-stage decision. The objective of the proposed model is to minimize the sum of CACs and the expected energy loss. The stochastic behavior is formulated by three-point estimate method (TPEM) to convert the stochastic programming into equivalent deterministic problem. A hybrid Genetic Algorithm-Interior Point Method is utilized to solve this large-scale mixed-integer nonlinear stochastic problem. Two case studies on IEEE 14-bus and IEEE 118-bus system are provided to illustrate the effectiveness of the proposed method.