Application Firefly Algorithm for Improvement STATCOM Controller to Enhance the Stability in a Grid Connected to Wind Power

Huu Vinh Nguyen1, Hung Nguyen2, Kim Hung Le3, Minh Tien Cao4, Qui-Thoi Le4, Ngoc-Tuan Tran4
1Ho Chi Minh City Power Corporation(EVNHCMC), Ho Chi Minh City, Viet Nam
2HUTECH Institute of Engineering Ho Chi Minh City University of Technology (HUTECH), Ho Chi Minh City, Viet Nam
3The University of Danang, University of Science and Technology, Da Nang Province, Viet Nam
4Faculty of Telecommunications Engineering, Telecommunications University, Nha Trang City, Viet Nam

Tóm tắt

STATCOM is a FACTS device installed in power systems for damping stability and increasing power transmission capacity. The algorithms used to control the STATCOM often use a PID controller. However, the PID controller is not robust for its stability control in highly nonlinear and complex systems. This paper presents the application firefly algorithm for improving the STATCOM controller to enhance the stability in a network connected to a wind energy system. The wind energy system is represented as a Doubly Fed Induction Generator (DFIG) driven by a Wind Turbine (WT). The power grid is simulated by an IEEE standard 14-bus system encompassing 14 nodes, 5 sources, and 11 loads. The studied wind power system is one of 5 sources that supply power to the network. Simulation results are performed with different disturbance conditions for testing the stability of the studied system. It can be concluded from simulation results that the proposed STATCOM controller helps improve the studied system's stability.

Từ khóa

#Static Synchronous Compensator (STATCOM) #Firefly algorithm #Adaptive Neuro-Fuzzy Inference System (ANFIS) #Wind energy #Stability

Tài liệu tham khảo

huu, 0, Using an intelligent ANFIS-Online controller for STATCOM in improving dynamic voltage stability, Facta Universitatis Series Electronics and Energetics, 33, 395

10.1109/ICICES.2013.6508175

ph?, 2013, Quy ??nh v? l? trình, các ?i?u ki?n và c? c?u ngành ?i?n ?? hình thành và phát tri?n các c?p ?? th? tr??ng ?i?n l?c t?i Vi?t Nam, Th? t??ng Chính ph? 63/2013/Q?-TTG

th??ng, 2014, Phê duy?t thi?t k? t?ng th? th? tr??ng bán buôn ?i?n c?nh tranh Vi?t Nam, 6463/Q?-BCT

higorani, 2000, Understanding FACTS: Concepts and Technology of Flexible AC Transmission Systems

fardanesh, 1998, Convertible static compensator: Application to the New York transmission system, CIGRE Paris Session, 14

bergen, 1999, Power System Analysis

10.2172/607488

10.1016/S1665-6423(13)71523-2

10.1016/j.matcom.2020.04.033

10.48084/etasr.3032

10.1007/978-3-642-04441-0_8

fattahi, 2017, Prediction of slope stability using adaptive neuro-fuzzy inference system based on clustering methods, Mining and the Environment, 8, 163

e, 2011, Improvement of fault ride through capability of wind farms using DFIG considering SDBR, Proc 14th European Conference on Power Electronics and Applications

jang, 1997, Neuro-Fuzzy and Soft Computing

10.1109/TSTE.2011.2142406

joskow, 2006, Electricity Market Reform

10.14445/22312803/IJCTT-V32P105

10.1109/ICRERA.2016.7884381

lai, 2001, Power System Restructuring and Deregulation: Trading, Performance and Information Deregulation

sioshansi, 2008, Competitive Electricity Markets

10.1109/PESS.2002.1043417

shahidehpour, 2001, Restructured Electrical Power Systems: Operation, Trading, and Volatility

farhoodnea, 2012, A Comprehensive Review of Optimization Techniques Applied for Placement and Sizing of Custom Power Devices in Distribution Networks, Przegl?d Elektrotechniczny, 88, 261

fister, 2012, Memetic firefly algorithm for combinatorial optimization

10.1109/ICGCE.2013.6823480

10.1016/j.amc.2015.04.065

10.1016/j.asoc.2015.12.036

10.1109/AEEICB.2017.7972401

yang, 2014, Nature-Inspired Optimization Algorithms

10.1016/j.eswa.2015.04.072