Control design for interconnected power systems with OLTCs via robust decentralized control

This paper addresses the problem of designing a decentralized control of interconnected power systems, with OLTC and SVCs, under large changes in real and reactive loads that cause large structural changes in the system model. In addition to this, small changes in load are regulated by small disturbance controllers whose gains are adjusted for variations in power system model due to large changes in loads. The only feedback needed by subsystem controllers is the state of the subsystem itself. The design is carried out within a large-scale Markov jump parameter systems framework. In this paper, unlike other control schemes, OLTC transformers are used to damp power-angle oscillations. Simulation results are presented to demonstrate the performance of the designed controller. © 2006 IEEE

Design of switching damping controllers for power systems based on a Markov jump parameter system approach

The application of a new technique, based on the theory of Markov Jump Parameter Systems (MJPS), to the problem of designing controllers to damp power system oscillations is presented in this paper. This problem is very difficult to address, mainly because these controllers are required to have an output feedback decentralized structure. The technique relies on the statistical knowledge about the system operating conditions to provide less conservative controllers than other modern robust control approaches. The influence of the system interconnections over its modes of oscillation is reduced by means of a proper control design formulation involving Integral Quadratic Constraints. The discrete nature of some typical events in power systems (such as line tripping or load switching) is adequately modeled by the MJPS approach, therefore allowing the controller to withstand such abrupt changes in the operating conditions of the system, as shown in the results. © 2006 IEEE

Evolution of microgrids with converter-interfaced generations: Challenges and opportunities

© 2019 Elsevier Ltd Although microgrids facilitate the increased penetration of distributed generations (DGs) and improve the security of power supplies, they have some issues that need to be better understood and addressed before realising the full potential of microgrids. This paper presents a comprehensive list of challenges and opportunities supported by a literature review on the evolution of converter-based microgrids. The discussion in this paper presented with a view to establishing microgrids as distinct from the existing distribution systems. This is accomplished by, firstly, describing the challenges and benefits of using DG units in a distribution network and then those of microgrid ones. Also, the definitions, classifications and characteristics of microgrids are summarised to provide a sound basis for novice researchers to undertake ongoing research on microgrids

Overview of AC microgrid controls with inverter-interfaced generations

Distributed generation (DG) is one of the key components of the emerging microgrid concept that enables renewable energy integration in a distribution network. In DG unit operation, inverters play a vital role in interfacing energy sources with the grid utility. An effective interfacing can successfully be accomplished by operating inverters with effective control techniques. This paper reviews and categorises different control methods (voltage and primary) for improving microgrid power quality, stability and power sharing approaches. In addition, the specific characteristics of microgrids are summarised to distinguish from distribution network control. Moreover, various control approaches including inner-loop controls and primary controls are compared according to their relative advantages and disadvantages. Finally, future research trends for microgrid control are discussed pointing out the research opportunities. This review paper will be a good basis for researchers working in microgrids and for industry to implement the ongoing research improvement in real systems