Short-Term Reliability Assessment of Generating Systems Considering Demand Response Reliability

Abstract

Demand response (DR), one kind of flexible resources, can decrease the operating costs of power systems and improve their reliability. However, DR is not absolutely reliable due to its inherent uncertainty, so its function of improving system reliability is restricted. In order to estimate the risk of generating systems during the period of DR events, the short-term reliability assessment of generating systems considering DR reliability is studied in this paper. Firstly, a multi-state continuous-time Markov chain (CTMC) model of DR response capacity is established and the state division of response capacity is performed by the method of mean-standard deviation (MSD) classification. Secondly, the transition matrix of DR response capacity is estimated according to the sequence of DR response capacity. Thirdly, the CTMCs of demand response providers' (DRP) response capacity and those of generating units' (GU) output capacity are converted into universal generating functions (UGF) by Lz-transform. Finally, the transient distribution of DR response capacity and GU output capacity are derived, and the short-term reliability assessment method for generating systems considering DR reliability is proposed. A case study on a revised IEEE-RTS79 system shows the application of the presented method. The method proposed in this paper can assist system operators to evaluate the reliability of generating systems during the period of DR events.

Keywords

• Demand response reliability
• Markov chain
• mean-standard deviation classification
• short-term reliability assessment of generating systems
• universal generating function