Improved load frequency control with superconducting magnetic energy storage in interconnected power systems

Abstract

This paper presents adaptive neural control of a superconducting magnetic energy storage system (SMES) in a power system for improved load frequency control (LFC). The proposed scheme for SMES control is a new one, tackles the deficiencies in the existing SMES control schemes and is clear about its implementation aspects. The power conversion system (PCS) of SMES used in this paper comprises of a voltage source converter (VSC) and a two-quadrant chopper. The control in each control area is implemented through a neural estimator and a neural controller with both of them operating online. The neural estimator extracts the control area dynamics around an operating point, and the neural controller then generates the power command for the corresponding SMES unit on the basis of a newly introduced variable which is a function of area control error and the change in stored energy in the SMES coil. This feature leads to a suitable and pure adaptive control of SMES. Moreover, in this paper the supplementary controller associated with the automatic generation control (AGC) is made to act on the area control error, with a modified gain setting, which is obtained by the integral square error (ISE) criterion. Simulation studies based on MATLAB are presented on a two-area power system after carrying out the necessary modeling exercise. 

Multi-Area Frequency and Tie-Line Power Flow Control by Fuzzy Gain Scheduled SMES

“…Figure 5 shows the proposed configuration of SMES units in a two-area power system [Mufti et al, 2007]. Two areas are connected by a weak tie-line.…”

“…As a result, fluctuations in terminal voltage can be corrected by the excitation system very quickly, but fluctuations in generated power or frequency are corrected slowly. Since load frequency control is primarily concerned with the real power/frequency behavior, the excitation system model will not be required in the approximated analysis [Mufti et al, 2007& Sheikh et al, 2008. This important simplification paves the way for constructing the simulation model shown in Fig.…”

“…But fixed gain controllers based on classical control theories are presently used. These are insufficient because of changes in operating points during a daily cycle [Benjamin et al, 1978;Nanda et al, 1988;Das et al, 1990;Mufti et al, 2007;Nanda et al, 2006& Oysal et al, 2004 and are not suitable for all operating conditions. Therefore, variable structure controller [Benjamin et al, 1982;Sivaramaksishana et al, 1984;Tripathy et al, 1997& Shayeghi et al, 2004 has been proposed for AGC.…”

Robust Stabilizing Controllers to Automatic Generation Control for Load Frequency Control Application

“…Basically, the governor-turbine system is slow reacting compared with the excitation system, which is fast reacting. As a result, fluctuations in terminal voltage can be corrected by the excitation system very quickly [3]. Fluctuations in generated power or frequency are corrected slowly.…”

“…However, as the LFC is fundamentally for the problem of an instantaneous mismatch between the generation and demand of active power, the incorporation of a fast-acting energy storage device in the power system can improve the performance under such conditions. To achieve a better performance, many control strategies are proposed in literature [1][2][3]. But fixed gain controllers based on classical control theories are presently used.…”