Dynamic and Stability Analysis of Wind-Diesel-Generator System With Intelligent Computation Algorithm: Computation Algorithms Applied to WDG System

Dynamic and Stability Analysis of Wind-Diesel-Generator System With Intelligent Computation Algorithm: Computation Algorithms Applied to WDG System

Dipayan Guha (Motilal Neheru National Institute of Technology Allahabad, India), Provas Kumar Roy (Kalyani Government Engineering College, India) and Subrata Banerjee (National Institute of Technology Durgapur, India)
Copyright: © 2019 |Pages: 40
DOI: 10.4018/978-1-5225-8030-0.ch003
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In this chapter, the dynamic performance of a wind-diesel-generator system has been studied against wind and load perturbations. The wind perturbation is modeled by simulating base, ramp, gust, and random wind. An optimized cascade tilt-integral-derivative (CC-TID) controller is provided to the test system for producing desired control signal to regulate the blade pitch angle of wind turbine. To confirm the efficacy of CC-TID controller, the output results are compared to that of PI- and PID-controller. The optimum gains of the proposed controllers are explored employing Levy-embedded grey wolf optimization, whale optimization algorithm, drone squadron optimization, and search group algorithm. To show the effectiveness, the output results are compared to the results of genetic algorithm and particle swarm optimization tuned controllers. A thyristor control series compensator (TCSC) is provided to WDG model for increasing the damping of system oscillations. Analysis of the presented results confirm the supremacy of CC-TID-TCSC controller over other controllers provided in this chapter.
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Electrical energy is environmentally the most favorable form of energy, the generation routed through the burning of fossil fuels or through nuclear reaction or use of hydro resources. However, with the swift fall of natural resources and degradation of environmental conditions, generation of power through renewable energy resources (RER) has gained ample attention from the researchers over the worldwide (Das et al., 1999). RER comprises solar power, wind power, geothermal power, wave power, tidal power, hydropower, biomass power etc. Wind and photovoltaic (PV) power generation are two of the most prevalent renewable sources used in the hybrid power system (HPS) due to their clean, abundant, inexpensive, and eco-friendly features. However, PV power generation is costly, has poor conversion efficiency, and lower power density as compared to wind power generation (WPG). Since the power generated from the WTG changes abruptly, hence to balance the intermittent characteristic, a diesel generator (DG) is coordinated with WTG to fulfill the required of load profile. The proposed wind-diesel-generator (WDG) system is trustworthy since the diesel set behaves as a cushion to overlook the variation of load demand and wind speed and meet the deficit demand (Das et al., 1999; Gampa and Das, 2015). Due to an intermittent characteristic of WTG, the unbalance power generation and load demand causes frequency fluctuation that may lead to the problem of instability. Thus the control of frequency and power is emergent for the successful operation of the coordinated WDG system.

In the state-of-art, numerous control methods have been reported for betterment of the dynamic performance of an isolated and/or interconnected WDG system following wind and load fluctuations. A comprehensive review of the challenges and opportunities in frequency control of the power system are presented in (Alhelou, 2018a). A load frequency control (LFC) of HPS with non-scheduled wind plant has been discussed in (Aziz et al., 2018). Uhlen et al. presented a robust control algorithm for WDG system using multivariable frequency domain techniques (Uhlen et al., 1994). A coordinated control of fuel cell (FC) and aqua-electrolyzer (AE) to solve the frequency and power fluctuation problem in micro-grid (MG) is discussed in (Ngamroo, 2012; Nadweh, 2018; Njenda, 2018; Zamani, 2018). The usefulness of electric vehicle control on primary frequency response of smart grid is discussed in (Alhelou et al., 2015; Alhelou et al., 2016). A model based fault detection scheme for measurement of variables in frequency control of power system with unknown input observer is discussed in (Alhelou et al., 2018b; Alhelou 2018c).

Key Terms in this Chapter

Optimization Techniques: Optimization is the process of making something better. Optimization is the selection of the best choice from among available options.

Thyristor Control Series Capacitor (TCSC): TCSC is a capacitive reactance compensator that comprises a series capacitor bank shunted with a thyristor-controlled reactor (TCR) to offer smoother variable capacitive reactance. In TCSC no high voltage interfacing transformer is required, thereby making it more economical than other FACTS devices. TCSC is usually connected in series with tie-line with an aim to improve rapid and continuous control of the transmission-line series-compensation level.

Cascade Controller: Cascade controller includes secondary measurement and secondary feedback arrangement that makes it more compatible to provide good set-point tracking and better disturbance rejection ability. In a cascade controller, two feedback loops are employed, and the inner loop responds much faster than the outer loop.

Frequency Control: Frequency control is a process of maintaining the stability of a power system. In the power system, the frequency of the loop gets deviate from the steady-state value under the action of load perturbation. Load frequency controller is employed to regulate the power generation level to match the load profile to keep the area frequency at its nominal value (±2.5Hz of nominal value).

Hybrid Power System: This hybrid energy system provides centralized electrical power generation in a local area by combining renewable energy resources with some slack systems and energy storage devices. The storage system helps to avoid the energy crisis issue and provides fast active compensation to power system oscillations.

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