A CVaR-constrained optimal power flow model for wind integrated power systems considering Transmission-side flexibility

Abstract

The integration of renewable power can pose uncertainty to power system operation, causing operational risk like power imbalance or line congestion. To improve the operational security and economy of the system under uncertainties, this paper considers two potential directions. The first is to enhance the system capability for safely accommodating uncertainties using various network resources. Such capability is often termed as the operational flexibility. The second direction is to employ appropriate risk management methods. With these two directions, a conditional value-at-risk (CVaR)-constrained optimal power flow (OPF) model is developed in this paper for wind-integrated power systems. In this model, dynamic line rating (DLR) and flexible AC transmission system (FACTS) technologies are exploited to unlock transfer capacities of transmission lines and enable line reactance control. As a result, power system has capability to allow more flexible and cost-efficient power flow distributions. That is, additional operational flexibility is provided by the transmission-side DLR and FACTS technologies. Such flexibility is termed as the transmission-side flexibility. Meanwhile, CVaR is employed as the risk management tool to control the security level of each operational constraint. To address the non-linearity of CVaR and solve the proposed model, a novel solution method is developed by combining Gaussian mixture model for uncertainty modelling with cutting-planes for CVaR reformulation. Numerical experiments in MATLAB reveal the economic benefit of the proposed model: the inclusion of transmission-side flexibility in formula can reduce the operational cost by 6.10% on a 14-bus system. The simulation results also show that the proposed solution method overcomes the poor system security associated with the traditional Gaussian method and is more economical than the previous robust method (3.79% reduction in operational cost on a 14-bus system).