Operating Reliability Evaluation of Power Systems With Demand-Side Resources Considering Cyber Malfunctions
Authors:
Open Access
- 1 January 2020
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Access
- Vol. 8, 87354-87366
Abstract
Demand-side resources (DSRs) have been shown to be valuable for providing reserve capacity and enhancing the reliability of power systems with high wind power penetration. The successful utilization of DSRs relies heavily upon the infrastructure of advanced information and communication technologies (ICTs). Notably, ICT systems may suffer from cyber attacks and communication latency, which could result in the malfunctions of DSRs and consequently bring adverse impacts on the reliability of power systems. In this paper, a novel operating reliability evaluation framework for multi-state power systems with DSRs and wind power considering malfunctions of cyber systems is proposed. For avoiding increasing complexity caused by multiple system states, an analytic method based on Lz transform technique is proposed to achieve dynamic system reliability. The reliability model for a typical hierarchical decentralized control infrastructure in demand side considering cyber attacks and communication latency is first proposed. Then, reserve capacity from DSRs considering stochastic behavior under the cyber infrastructure is modelled. Moreover, multi-state models for power generation systems with stochastic wind power and conventional generation are developed considering cyber malfunctions. Reliability indices based on load curtailment by conducting optimal power flow for various system states are utilized for reliability assessment. A modified IEEE RTS with four cases is adopted to validate the proposed model and method, which denotes that reserve capacity from DSRs can definitely enhance system operating reliability and affected by proportions of DSRs, consideration of cyber malfunctions, actual committed time for DSRs and initial system conditions.Keywords
Funding Information
- China Postdoctoral Science Foundation (2019TQ0090)
- National Social Science Foundation of China (19ZDA081)
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