Abstract
The paper presents a method developed for detecting rough errors in the measurements related to batteries in the part of electric power system that is characterised by low data redundancy. Since batteries either produce or consume power, not all methods of bad data detection can be used to detect erroneous measurements of the active power of the battery in the case of low measurement redundancy. Because of different values of the active power that a battery may produce or consume at several snapshots in row, dynamic algorithms cannot be used. In this study, a new method of bad data detection is developed. The method is based on the battery control strategy analysis.
Highlights
The main objectives in managing an electric power system (EPS) with renewable energy sources are to mitigate fluctuations in the system and to accept as much solar and wind power as possible
In electric power system control, validity and completeness of data are provided by the state estimation procedure [3], [4], which calculates steady-state variables on the basis of a measurement snapshot
A method of bad data detection is based on the battery control strategy analysis according to which the battery is discharged when there is a shortage of power generated at the wind farm, and it is charged when there is too much power generated at the wind- farm
Summary
The main objectives in managing an electric power system (EPS) with renewable energy sources are to mitigate fluctuations in the system and to accept as much solar and wind power as possible. These objectives can be met by using energy storage devices. There are several technologies of Pumped hydro energy storage (PHES) in Russia. Energy is stored using energy storage technologies, which allow smoothing energy consumption over time, shave peak loads and, thereby, reduce the required operating power of the main equipment of the system. The second section presents a description of the problem. The sixth section several case studies are presented.
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