Modified interval‐based generator scheduling for PFR adequacy under uncertain PV generation. Issue 16 (26th July 2019)

• Record Type: Journal Article
• Authors: Prakash, Vivek; Sharma, Kailash Chand; Bhakar, Rohit; Tiwari, Harpal
• Is Part Of: IET generation, transmission & distribution. Volume 13:Issue 16(2019)
• Page Start: 3725
• Page End: 3733
• Publication Date: 2019-07-26
• Subjects: scheduling -- power generation scheduling -- frequency response -- stochastic programming -- photovoltaic power systems -- power generation dispatch -- stochastic processes -- power grids; modified interval‐based generator scheduling -- uncertain PV generation -- photovoltaic generation -- adequate PFR -- rapid frequency stability -- generation outage -- PFR estimation -- acceptable operational time frames -- system operator -- PV uncertainty characterisation -- computationally fast modified interval scheduling approach -- interval forecasting -- stochastic scheduling approach -- PFR performance -- computational time -- PV curtailment; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2018.6391
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : Large quantum of photovoltaic (PV) generation into the grid would reduce system's primary frequency response (PFR) capability. Adequate PFR is critical to provide rapid frequency stability after contingencies such as large generation outage. PFR estimation and its scheduling within acceptable operational time frames is a challenging task for system operator. Uncertain PV generation makes this problem critical. Existing models for PV uncertainty characterisation with stochastic scheduling are computationally demanding. This study proposes a computationally fast modified interval scheduling approach for operation and PFR cost minimisation. Uncertainty is modelled through interval forecasting, while hourly ramp needs are based on net load scenario. The proposed model is compared with stochastic scheduling approach for PFR performance, overall cost performance, computational time and PV curtailment. Numerical results show that the proposed model drastically reduces simulation time for similar cost performance.