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.
Highlights
Due to growing concern on climate change and energy sustainability, as one of the renewable resources, wind power is considered a promising alternative to conventional fossil-fuel power generators [1,2]
This paper mainly focuses on incentive-based DR, such as the emergency demand response program, direct load control and interruptible service
This paper presents a probabilistic multi-objective transmission expansion planning (TEP) model for power systems with increasing wind power integration
Summary
Due to growing concern on climate change and energy sustainability, as one of the renewable resources, wind power is considered a promising alternative to conventional fossil-fuel power generators [1,2]. The conventional least-cost reliability constrained transmission expansion planning (TEP) cannot fully capture the stochastic nature of emerging uncertainties and handle the conflicting objectives in a deregulated modern power industry [14]. Reference [9] presents a probabilistic TEP model considering large-scale wind farms integration and incentive-based DR. Reference [18] proposes an optimal transmission network planning model in order to integrate 50% wind power into the system. In [20], a multi-objective TEP model is proposed for incorporating large-scale wind power. In [21], a multi-objective TEP model is proposed to address the conflicting interests of investment cost, absorption of private investment, and reliability.
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