Abstract
This paper proposes an optimal allocation of a Wind-Storage Unit (WSU). Since transmission lines congestion varies according to the size, the location, and the operation of a generation unit in power systems, we assess the optimal location of a unit as a function of its variable operating condition. An independently operated wind-storage unit is assumed as a price-maker that seeks to maximize its market payoff without any prior information on optimally locating the wind and storage units. The main problem is provided as a tri-level optimization problem in which the first level is the WSU profit maximization, the second level is the power system operation cost minimization from the perspective of the independent system operator (ISO), and the third level is the maximization of the robustness of the system by using an appropriate transmission switching interval robust based chance constrained (TSIRC) method in order to minimize the operation cost of the system and transmission lines congestion problem. The tri-level model is converted to a bi-level optimization model by using Karush-Kuhn-Tucker (KKT) conditions provided as a Mathematical Programming with Equilibrium Constraint (MPEC). An effective binary particle swarm optimization algorithm (BPSO) is used in order to find the optimal location of the wind and storage units. Unscented Transform (UT) as a key element is suggested to model the uncertainties associated with the output power of the wind turbines. The proposed method is tested on an IEEE 24-bus test system and the results reveal the validity of this work.
Highlights
The development and deployment of distributed energy resources (DERs) have attracted much attention to power system oper ations
This paper proposes an optimal allocation of a Wind-Storage Unit (WSU)
The main problem is provided as a tri-level optimization problem in which the first level is the WSU profit maximization, the second level is the power system operation cost minimization from the perspective of the independent system operator (ISO), and the third level is the maximization of the robustness of the system by using an appropriate transmission switching interval robust based chance constrained (TSIRC) method in order to minimize the operation cost of the system and transmission lines congestion problem
Summary
The development and deployment of distributed energy resources (DERs) have attracted much attention to power system oper ations. The authors in [3] investigated the ESS allocation along with load shedding in order to improve the power system reliability in contin gencies They stated that such procedures could reduce the annual planning and operation costs including those of resource installation, interruption, and maintenance. In [20], both the correction effect among WTs and the allocation of ESS in WT integrated power systems are concerned and a new hybrid opti mization algorithm is represented to allocate the price-taker ESSs. In [21], authors went through two major steps to allocate the renewable energy sources including WTs and ESS in partitioned transmission network. To the best of authors’ knowledge, none of the previous works have provided an effective model for optimal congestion based price-maker wind-storage unit as a market participant.
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