Abstract
Power systems are susceptible to disturbances due to their nature. These disturbances can cause overloads or even contingencies of greater impact. In case of an extreme situation, load curtailment is considered the last resort for reducing the contingency impact, its activation being necessary to avoid the collapse of the system. However, load shedding systems seldom work optimally and cause either excessive or insufficient reduction of the load. To resolve this issue, the present paper proposes a methodology to enhance the load curtailment management in medium voltage distribution systems using Particle Swarm Optimization (PSO). This optimization seeks to minimize the amount of load to be cut off. Restrictions on the optimization problem consist of the security operation margins of both loading and voltage of the system elements. Heuristic optimization algorithms were chosen, since they are considered an online basis (allowing a short processing time) to solve the formulated load curtailment optimization problem. Best performances regarding optimal value and processing time were obtained using a PSO algorithm, qualifying the technique as the most appropriate for this study. To assess the methodology, the CIGRE MV distribution network benchmark was used, assuming dynamic load profiles during an entire week. Results show that it is possible to determine the optimal unattended power of the system. This way, improvements in the minimization of the expected energy not supplied (ENS) as well as the System Average Interruption Frequency Index (SAIDI) at specific hours of the day were made.
Highlights
The energy dependence of modern societies requires power grids to fulfill high levels of reliability, availability, quality, security, among others
The paper consists of the following sections: Section 2 presents the background on load curtailment optimization methods; Section 3 addresses the proposed procedure based on the Particle Swarm Optimization (PSO) method; Section 4 presents the assessment of the procedure with the CIGRE MV distribution network benchmark; Section 5 presents the conclusions
≤ xk ≤ 1 where i, k are the buses of the system; g = 0 are the balance equations; N is the number of buses with loads; xk is the load shedding factor at bus k, being 0 total disconnection and 1 no power cut off; Dk is the load required at bus k; Trak is the loading of transformer connected at bus k; Lini,k is the loading of line between i, k buses; and Uk is the set of bus voltages
Summary
The energy dependence of modern societies requires power grids to fulfill high levels of reliability, availability, quality, security, among others. The common scheme to operate conventional distribution networks during contingencies is the centralized control of load curtailment For this reason, the entire system should be prepared to follow a procedure to minimize the impact of the interruption in any possible scenario of contingency, given a load forecast demand. In view of the above concerns, this article presents a practical methodology to optimize load curtailment during a contingency through load forecasting applied to conventional distribution networks This seeks to reduce the contingency impact on both the SAIDI index and the expected energy not supplied by using a centralized control. The optimization is performed trough the Particle Swarm Optimization algorithm (PSO) This procedure is suitable for real-time operation during contingencies as well as for long-term planning of conventional distribution networks, providing an optimal load shedding strategy and identifying contingencies of high impact on the reliability indexes. The paper consists of the following sections: Section 2 presents the background on load curtailment optimization methods; Section 3 addresses the proposed procedure based on the PSO method; Section 4 presents the assessment of the procedure with the CIGRE MV distribution network benchmark; Section 5 presents the conclusions
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