Potential and Efficient Computation of Corrective Power Flow Control in Cost vs. Risk Trade-Off

Abstract

Increased levels of variable renewable generation lead to increased variations in power flows. If the required transmission capacity is provided by a grid with no or little controllability as in today's power system, the consequence is a significant under-utilization of the transmission assets most of the time. In this paper, corrective power flow control is used to improve the utilization of the existing transmission capabilities and adjust the grid to the varying needs of generation and demand. In lieu of the traditional N-1 security formulation, a risk based approach is employed. The resulting risk constrained economic dispatch is solved efficiently by decomposing it into a two stage process by using newly defined locational security impact factors (LSIF). In addition, these LSIFs provide information on the most effective, location-dependent measures to reduce system risk. Simulations provide insights into the effectiveness of the proposed approach and the potential of corrective power flow control to reduce cost of dispatched generation and to decrease system risk.Index Terms-Corrective power flow control, risk minimization, security constrained optimal power flow.

Decomposed algorithm for risk-constrained AC OPF with corrective control by series FACTS devices

“…The probability of element p to fail and create contingency q, shown in Fig. 1b, is chosen based on [15] to have two components. The first is constant and represents the outage probability obtained from historical records, and the second is a quadratic function of the element's loading before the outage.…”

“…Risk-based security indices can be used for both increasing operators' awareness of the system state [8,9] and optimizing power system performance [10,11,12], e.g. by formulating the Risk-Constrained OPF (RCOPF) problem [13,14,15,16,17,18].…”

“…This paper focuses on the RCOPF problem, which has the objective of minimizing the total supply cost in the system while keeping the risk below a given value and, due to its size, becomes difficult to solve in a centralized fashion for real-world grids. Existing approaches for decoupling this problem include using Benders decomposition [14] or so-called locational security impact factors (LSIFs) [15,28,29]. However, studies [14,15,28] are based on a DC approximation of a power system, and the problem formulation in [29] does not include corrective control.…”

“…Existing approaches for decoupling this problem include using Benders decomposition [14] or so-called locational security impact factors (LSIFs) [15,28,29]. However, studies [14,15,28] are based on a DC approximation of a power system, and the problem formulation in [29] does not include corrective control. In addition, only single-element outages are considered in these studies and communication overhead between parallel processors is not taken into account when analyzing the potential acceleration of the algorithm with parallelized computations.…”

Day-Ahead Corrective Adjustment of FACTS Reactance: A Linear Programming Approach

“…For instance, [34]- [36] propose various methods to include FACTS adjustment for a variety of applications. However, the formulation developed in [34]- [37] is computationally expensive and will not be applicable to large-scale power systems. A regression-based model is proposed in [38] to provide suggestions to the operator regarding the operation of FACTS devices and improve the usage of transmission capacity; this prior work aims at addressing the computational complexity challenge by employing an offline statistical method.…”