Abstract
The blackout risks of cascading failures in power systems are notably associated with the failures of transmission lines. Line capacity temporary expansion can reduce blackout risk by decreasing the line failures due to the overloads during the cascading failures. To efficiently quantify the impact of line capacity temporary expansion on blackout risks, we propose a data based state-failure–network method in this paper. The state-failure network, which is formed by the cascading failure data generated by cascading failure simulations, contains the empirical probabilities that correspond to the failure probabilities of lines. Since implementing line capacity temporary expansion to the system can change the failure probabilities of lines and reduce the blackout risk, the empirical probabilities offer the link between line capacity temporary expansion and state-failure network. By updating the values in the state-failure network with changed empirical probabilities, the blackout risk after line capacity temporary expansion is implemented can be efficiently worked out by state-failure network. Thus, the impact of line capacity temporary expansion on blackout risk is quantified by comparing the newly calculated blackout risk with the risk before the line capacity temporary expansion is implemented. The advantage of the proposed method lies in the high accuracy and efficiency of quantifying the impacts of any line capacity temporary expansion schemes once the state-failure network is formed. Case studies verify the accuracy and efficiency of the proposed method.
Highlights
Cascading failures in power systems often give rise to large blackouts and cause severe losses to modern society [1], [2]
To address the issue of efficiently quantifying the impact of line capacity temporary expansion on blackout risks, this paper proposes an algorithm based on the state-failure– network method illustrated in [24]
Besides their distributions, it still calls for the detailed analyses of losses caused by the failures to account for the nonlinearity between line capacity temporary expansion and blackout risks from 0-300MW, which will be pursued in our future work
Summary
Cascading failures in power systems often give rise to large blackouts and cause severe losses to modern society [1], [2]. To improve the efficiency for obtaining the blackout risks after line capacity temporary expansion is implemented, another way using cascading failures data to form data based models has been proposed in the literature [22]–[24]. Since the models in [22], [23] do not take load losses into account, they cannot quantify the impact of line capacity temporary expansion on blackout risks. To address the issue of efficiently quantifying the impact of line capacity temporary expansion on blackout risks, this paper proposes an algorithm based on the state-failure– network method illustrated in [24]. State-failure network is able to obtain accurate blackout risk estimations after the line capacity temporary expansion is implemented. Due to the complexity of cascading failure dynamics and strong nonlinearity, optimizing the line capacity temporary expansion schemes can hardly be achieved by an analytical way This method offers a reliable tool to efficiently achieve the analyses based on heuristic optimization algorithms. 3) Hybrid state: the state with both failures and f0. cascading failures can either terminate at these states or propagate to subsequent stages
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