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Energies 2017, 10(7), 1036; doi:10.3390/en10071036

Flexible Multi-Objective Transmission Expansion Planning with Adjustable Risk Aversion

1
Energy Flagship, The Commonwealth Scientific and Industrial Research Organization (CSIRO), Mayfield West, NSW 2304, Australia
2
School of Science and Engineering, Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China
3
Center for Intelligent Electricity Networks, The University of Newcastle, Callaghan, NSW 2308, Australia
*
Author to whom correspondence should be addressed.
Received: 8 May 2017 / Revised: 27 June 2017 / Accepted: 13 July 2017 / Published: 20 July 2017
(This article belongs to the Section Electrical Power and Energy System)
View Full-Text   |   Download PDF [2486 KB, uploaded 20 July 2017]   |  

Abstract

This paper presents a multi-objective transmission expansion planning (TEP) framework. Rather than using the conventional deterministic reliability criterion, a risk component based on the probabilistic reliability criterion is incorporated into the TEP objectives. This risk component can capture the stochastic nature of power systems, such as load and wind power output variations, component availability, and incentive-based demand response (IBDR) costs. Specifically, the formulation of risk value after risk aversion is explicitly given, and it aims to provide network planners with the flexibility to conduct risk analysis. Thus, a final expansion plan can be selected according to individual risk preferences. Moreover, the economic value of IBDR is modeled and integrated into the cost objective. In addition, a relatively new multi-objective evolutionary algorithm called the MOEA/D is introduced and employed to find Pareto optimal solutions, and tradeoffs between overall cost and risk are provided. The proposed approach is numerically verified on the Garver’s six-bus, IEEE 24-bus RTS and Polish 2383-bus systems. Case study results demonstrate that the proposed approach can effectively reduce cost and hedge risk in relation to increasing wind power integration. View Full-Text
Keywords: risk management; stochastic programming; multi-objective optimization; and power-system planning risk management; stochastic programming; multi-objective optimization; and power-system planning
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Qiu, J.; Zhao, J.; Wang, D. Flexible Multi-Objective Transmission Expansion Planning with Adjustable Risk Aversion. Energies 2017, 10, 1036.

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