Application of Artificial Intelligence-Based Techniques in Controlling the STATCOM Used for Compensation for Voltage Dip
Severe voltage sag in weak power systems connected to DFIG-based wind farms may lead to voltage instability. In such cases, FACTS devices like static synchronous compensator (STATCOM) can provide voltage support at the point of common coupling (PCC) by dy
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Abstract Severe voltage sag in weak power systems connected to DFIG-based wind farms may lead to voltage instability. In such cases, FACTS devices like static synchronous compensator (STATCOM) can provide voltage support at the point of common coupling (PCC) by dynamic injection of reactive power. In this research attempt, three artificial intelligence-based techniques have been used to control the STATCOM—fuzzy logic, particle swarm optimization (PSO) and a combination of fuzzy logic and PSO. The STATCOM, controlled by the three proposed techniques— fuzzy-PI, PSO-PI and fuzzy PSO-PI, provides voltage compensation in the DFIG-based grid-connected wind power system in five test cases, namely simultaneous occurrence of step change (drop) in wind speed and dip in grid voltage, single-line-to-ground (SLG) fault, line-to-line (LL) fault, double-line-to-ground (DLG) fault and sudden increase in load by more than a thousand times. A performance comparison regarding the amount of voltage compensation offered is done among all the three artificial intelligence-based STATCOM control techniques in all the five test cases.
Keywords Static synchronous compensator (STATCOM) Fuzzy logic Particle swarm optimization (PSO) Grid-connected Point of common coupling (PCC) Doubly fed induction generator (DFIG)
B. Mukhopadhyay (&) R.K. Mandal National Institute of Technology, Patna, India e-mail: [email protected] R.K. Mandal e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2018 S. SenGupta et al. (eds.), Advances in Smart Grid and Renewable Energy, Lecture Notes in Electrical Engineering 435, https://doi.org/10.1007/978-981-10-4286-7_18
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B. Mukhopadhyay and R.K. Mandal
1 Introduction DFIG is considered to be highly suitable for grid-connected wind power plants owing to its advantages which include independent supervision of active and reactive power, better voltage regulation, maximum power extraction at low wind speeds and the ability to ride-through faults [1]. Voltage instability may occur due to severe faults in weak power systems associated with grid-connected wind farms. Under such circumstances, FACTS devices like the STATCOM may be harnessed to provide dynamic reactive power support at the PCC, thus enabling enhanced transient and steady-state voltage stability [2, 3]. In this work, the STATCOM employed for voltage compensation is controlled using three artificial intelligence-based techniques—fuzzy logic, PSO and a combination of fuzzy logic and PSO. In terms of voltage compensation offered at the PCC, a performance comparison is done among the three techniques used to control the STATCOM, namely fuzzy-PI, PSO-PI and fuzzy PSO-PI, in five test cases—simultaneous occurrence of step change (drop) in wind speed and grid voltage dip, SLG, LL, DLG faults and sudden load change.
2 Fuzzy-PI Controller for STATCOM The voltage, current and frequency regulators in the STATCOM control system shown in Fig. 1 are equipped with fuzzy logic controllers. Mamdani fuzzy inference system and Center of
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