Journal article
A new Risk-Managed planning of electric distribution network incorporating customer engagement and temporary solutions
IEEE Transactions on Sustainable Energy, Vol.7(4), pp.1646-1661
2016
Abstract
The connection of renewable-based distributed generation (DG) in distribution networks has been increasing over the last few decades, which would result in increased network capacity to handle their uncertainties along with uncertainties associated with demand forecast. Temporary non-network solutions (NNSs) such as demand response (DR) and temporary energy storage system/DG are considered as promising options for handling these uncertainties at a lower cost than network alternatives. In order to manage and treat the risk associated with these uncertainties using NNSs, this paper presents a new risk-managed approach for multi-stage distribution expansion planning (MSDEP) at a lower cost. In this approach, the uncertainty of available DR is also taken into account. The philosophy of the proposed approach is to find the “optimal level of demand” for each year at which the network should be upgraded using network solutions while procuring temporary NNSs to supply the excess demand above this level. A recently developed forward-backward approach is fitted to solve the risk-managed MSDEP model presented here for real sized networks with a manageable computational cost. Simulation results of two case studies, IEEE 13-bus and a realistic 747-bus distribution network, illustrate the effectiveness of the proposed approach.
Details
- Title
- A new Risk-Managed planning of electric distribution network incorporating customer engagement and temporary solutions
- Authors/Creators
- A. Arefi (Author/Creator) - Murdoch UniversityA. Abeygunawardana (Author/Creator) - Queensland University of TechnologyG. Ledwich (Author/Creator) - Queensland University of Technology
- Publication Details
- IEEE Transactions on Sustainable Energy, Vol.7(4), pp.1646-1661
- Publisher
- IEEE
- Identifiers
- 991005540771307891
- Copyright
- © 2016 IEEE
- Murdoch Affiliation
- School of Engineering and Information Technology
- Language
- English
- Resource Type
- Journal article
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- Citation topics
- 4 Electrical Engineering, Electronics & Computer Science
- 4.18 Power Systems & Electric Vehicles
- 4.18.204 Smart Grid Optimization
- Web Of Science research areas
- Energy & Fuels
- Engineering, Electrical & Electronic
- Green & Sustainable Science & Technology
- ESI research areas
- Engineering