NDLI: Expectation–maximisation model for stochastic distribution network planning considering network loss and voltage deviation

Content Provider	IET Digital Library
Author	Qi, Baoxia Chen, Jiajia Zhao, Yanlei Jiao, Pihua
Abstract	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.
Starting Page	248
Ending Page	257
Page Count	10
ISSN	17518687
Volume Number	13
e-ISSN	17518695
Issue Number	Issue 2, Jan (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-gtd/13/2
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2018.5813
Journal	IET Generation, Transmission & Distribution
Publisher Date	2018-10-30
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Continuously Increasing Demand Different Forecasting Wind Distribution Network Expectation–maximisation Model Forecasting Approach Forecasting Error Investment Latin Hypercube Sampling Method Mean-variance-skewness Based Expectation Maximisation Model MVSbEM Model Network Loss Optimisation Technique Particle Swarm Optimisation Power Distribution Planning Power Factors Power System Economics Power System Managemen Power System Operation Power System Planning And Layout Sample Uncertain Wind Speed Sampling Method Simulated Annealing Simulated Annealing Particle Swarm Optimisation Algorithm Statistics Stochastic Distribution Network Planning Stochastic DNP Stochastic Linearised SCUC Substations Upgrading Uncertain Wind Power Voltage Deviation Wind Power Penetration Wind Power Plant Wind Turbine
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering

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