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Energies 2017, 10(9), 1291; doi:10.3390/en10091291

Day-Ahead Active Power Scheduling in Active Distribution Network Considering Renewable Energy Generation Forecast Errors

College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
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Received: 25 July 2017 / Revised: 21 August 2017 / Accepted: 25 August 2017 / Published: 29 August 2017
(This article belongs to the Section Electrical Power and Energy System)
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Abstract

With large-scale integration of distributed energy resources (DERs), distribution networks have turned into active distribution networks (ADNs). However, management risks and obstacles are caused by this in due to renewable energy generation (REG) forecasting errors. In this paper, a day-ahead active power scheduling method considering REG forecast errors is proposed to eliminate the risks, minimize the costs of distribution companies and achieve optimal power flow. A hierarchical coordination optimization model based on chance constrained programming is established to realize day-ahead optimal scheduling of active power in ADNs coordinated with network reconfiguration, achieving an optimal solution of network topologies and DER outputs. The hierarchical method includes three levels: the first level provides initial values, and multiple iterations between the second and third level are used to solve the multi-period mixed integer nonlinear optimization problem. The randomness due to REG forecast errors is tackled with chance constrained programming in the scheduling procedure. The hybrid particle swarm optimization algorithm is employed to solve the proposed model. Simulation results verify the validity of the proposed method with an improved 33 nodes distribution network. View Full-Text
Keywords: active distribution network (ADN); active power scheduling; network reconfiguration; hierarchical coordination optimization; forecast errors active distribution network (ADN); active power scheduling; network reconfiguration; hierarchical coordination optimization; forecast errors
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Cong, P.; Tang, W.; Zhang, L.; Zhang, B.; Cai, Y. Day-Ahead Active Power Scheduling in Active Distribution Network Considering Renewable Energy Generation Forecast Errors. Energies 2017, 10, 1291.

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