Expectation-maximisation model for stochastic distribution network planning considering network loss and voltage deviation

作者：Qi, Baoxia; Chen, Jiajia^*; Zhao, Yanlei; Jiao, Pihua

来源：IET Generation Transmission & Distribution, 2019, 13(2): 248-257.

DOI：10.1049/iet-gtd.2018.5813

• particle swarm optimisation
• power distribution planning
• sampling methods
• wind turbines
• stochastic processes
• investment
• simulated annealing
• wind power plants
• continuously increasing demand
• forecasting error
• forecasting approach
• mean-variance-skewness based expectation maximisation model
• uncertain wind power
• MVSbEM model
• network loss
• voltage deviation
• power factors
• different forecasting wind
• sample uncertain wind speed
• wind power penetration
• expectation-maximisation model

The penetration of wind power is increasing in distribution network for reducing reliance on fossil fuels and covering continuously increasing demand for energy. However, it is argued that the forecasting error of wind power cannot be avoided even using the best forecasting approach. Therefore, in this study, a mean-variance-skewness based expectation maximisation (MVSbEM) model has been proposed by maximisation of the mean and skewness while simultaneously minimisation of the variance to obtain the optimal trade-off relationship between the profit and risk of distribution network planning (DNP) considering uncertain wind power integrated. In the MVSbEM model, the indexes of network loss, voltage deviation, and investment cost are concurrently taken into account under several kinds of actual operation constraints. In addition, the authors have made a full investigation on the MVSbEM by considering different forecasting errors, power factors of wind power, the different forecasting wind speeds, the number of wind turbines as well as the lines and substations upgrading. Furthermore, in order to reduce the computational burden, the Latin hypercube sampling method is used to sample uncertain wind speed. The feasibility and effectiveness of the MVSbEM model have been comprehensively evaluated on a modified IEEE 33-bus system.

• 出版日期2019-1-22
• 单位山东理工大学