System dynamics and control of EV incorporated deregulated power system using MBO‐optimized cascaded ID‐PD controller

Abstract

Summary A two‐area hybrid deregulated power system is proposed with a multi‐source combination of generating units with reference to the modern power and energy scenario. The proposed system is incorporated with solar‐thermal, conventional‐thermal, wind, and electric vehicle (EV) and is provided with appropriate system nonlinearities for a realistic approach. In addition to renewables, the inclusion of EVs helps to reduce CO2 emissions and dependence on fossil fuels, resulting in a cleaner environment. Such a class system requires a robust controller. In this regard, the transient and steady‐state dynamics with respect to various classical and cascaded secondary controllers have been evaluated. The response comparison among different secondary controllers reports the cascaded ID‐PD controller as the optimal one. Magnetotactic bacteria optimization (MBO) technique is used for parallely optimizing the secondary controller gains. A new study is explored to inspect the impact of EVs in regulating the system stability for the proposed system. The analysis confirms the inclusion of EVs in both the control area for better system dynamics. Sensitivity analysis is done to reflect the robustness of MBO‐optimized cascaded ID‐PD controller gains. It shows that optimized gains do not need to be rearranged for variations in system parameters. A separate study is carried out for any alterations in DISCO participation matrix (DPM), which is inevitable in a practical deregulated power system. It is found that the optimal controller gains attained at nominal DPM are also resilient to changes in DPM.

Power generation control of restructured hybrid power system with FACTS and energy storage devices using optimal cascaded fractional‐order controller

“…As per the literature, 25,28,29,34,36,50 following conditions must be met in order to develop an effective secondary controller for a modern restructured power system: Effective in dealing with load fluctuations. Effective at dealing with the challenges that come with energy storage systems. Robust in face of the RES uncertainties. Conformable in tuning as per working conditions. …”

“…Meta-heuristic optimization techniques find their ways successfully in optimizing the controller gains. Several optimization techniques genetic algorithm (GA), 8 Hooke-Jeev's optimization, 9 teaching learning algorithm, 10 firefly algorithm, 14 bio-geography based optimization (BBO), 18,21 Bacterial foraging OPTIMIZATION (BFO), 25 hybrid particle swarm optimization (HPSO), 26 magnetotactic bacteria optimization, 28 flower pollination optimization, 29 cuckoo search optimization, 33 sine-cosine algorithm, 36 stochastic fractal search optimization, 37 fruit fly optimization, 38 whale optimization algorithm 40,44 are reported in literature for power system studies. Such optimizing techniques have been very successful in LFC operation.…”

“…As per the literature, 25,28,29,34,36,50 following conditions must be met in order to develop an effective secondary controller for a modern restructured power system:…”

“…The area output power depends on the area control error (ACE), however the rise in power generation hinges on the area involvement factor (aif) 26 . The authors in References 27 and 28 presented a report on restructured power system comprising appropriate system nonlinearities.…”

Disturbance rejection based fractional order PID controller for system performance improvement of hybrid power system

“…Encouraging from the widespread use of RES, a thorough inspection of RES based smart grid is illustrated in Reference 9. Frequency and tie‐line power control of HPS incorporated with solar–thermal is discussed in References 10 and 11. The importance of wind and solar energy for modern power system is reported in References 12 and 13.…”