Computation of Ancillary Service Requirement Assessment Indices for Load Frequency Control in a Restructured Power System using SMES Unit and SCES Unit


Bacterial Foraging Optimization
Superconducting Magnetic Energy Storage
Super Capacitor Energy Storage
Proportional plus Integral Controller
Ancillary Service
Power System Ancillary Service Requirement Assessment Indices.

How to Cite

I.A. Chidambaramand, N.D. Sridhar. Computation of Ancillary Service Requirement Assessment Indices for Load Frequency Control in a Restructured Power System using SMES Unit and SCES Unit. Glob. J. Energ. Technol. Res. Updat. [Internet]. 2014 Sep. 29 [cited 2022 May 23];1(1):25-39. Available from:


To ensure a quality power supply the power system should not only match the total generation with total load and the associated system losses but also should emphasis better Ancillary Services. Even small disturbances to the power system can result in wide deviation in system frequency and quick restoration process are of prime importance not only based on the time of restoration and also should ensure stability limits. This paper proposes various design procedures for computing Power System Ancillary Service Requirement Assessment Indices (PSASRAI) for a Two-Area Thermal Reheat Interconnected Power System (TATRIPS) in a restructured environment. As simple conventional Proportional plus Integral (PI) controllers are still popular in power industry for frequency regulation as in case of any change in system operating conditions new gain values can be computed easily even for multi-area power systems, this paper focus on the computation of various PSASRAI for Two Area Thermal Reheat Interconnected Power System in restructured environment based on the settling time and peak undershoot concepts of control input deviations of each area. Energy storage is an attractive option to augment demand side management implementation, so storage devices like Super Capacitor Energy Storage (SCES) and Superconducting Magnetic Energy Storage (SMES) unit can be efficiently utilized to meet the peak demand. So the design of the Proportional plus Integral (PI) controller gains for the restructured power system without and with the storage units are carried out using Bacterial Foraging Optimization (BFO) algorithm. These controllers are implemented to achieve a faster restoration time in the output responses of the system when the system experiences with various step load perturbations. In this paper the PSASRAI are calculated for different types of possible transactions and the necessary remedial measures to be adopted are also suggested. If PSARAI based on settling time lies between 1 to 1.5 and if PSARAI based on peak undershoot is less than 0.2 distributed generation has to be incorporated and if the limit exceeds then the system becomes vulnerable and may result to black outs.


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