In this paper, an adaptive fuzzy logic-based differential evolution (DE) algorithm is proposed to optimize the gain of proportional–integral–derivative (PID) controllers. Using the proposed controller, the speed regulation parameters are tuned. Here, fuzzy logic is used to generate the controlled range of population set to DE algorithm. So that most favourable offspring population is created and the drawback of conventional DE algorithm is reduced. Using the proposed controller, the approximation errors and the external disturbance effects are minimized. The proposed method is implemented in MATLAB/Simulink working platform and the effectiveness is verified by multi-source two-area power generation system with renewable energy source. Three test cases are used to evaluate the simulation behaviour of proposed method. Simulation results of the tested power systems prove the effectiveness of the proposed load frequency control and proved its superiority over traditional PID controller, DE-tuned PID controller and fuzzy logic—DE algorithm-based PID controller. Comparison results show that proposed method has less overshoot, undershoot and fast settling time.
Multi-area system Deregulation PID tuning Adaptive fuzzy logic DE algorithm
This is a preview of subscription content, log in to check access.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
Informed consent was obtained from all individual participants included in the study.
Alajmi BN, Ahmed KH, Finney SJ, Williams BW (2011) Fuzzy logic control approach of a modified hill-climbing method for maximum power point in microgrid standalone photovoltaic system. IEEE Trans Power Electron 26(4):1022–1030CrossRefGoogle Scholar
Alam MN, Das B, Pant V (2015) A comparative study of metaheuristic optimization approaches for directional overcurrent relays coordination. Electr Power Syst Res 128:39–52CrossRefGoogle Scholar
Apostolopoulou D, Dominguez-Garcia AD, Sauer PW (2015) An assessment of the impact of uncertainty on automatic generation control systems. IEEE Trans Power Syst 31(4):2657–2665CrossRefGoogle Scholar
Arqub OA, Abo-Hammour Z (2014) Numerical solution of systems of second-order boundary value problems using continuous genetic algorithm. Inf Sci 279:396–415MathSciNetCrossRefzbMATHGoogle Scholar
Arqub OA, Mohammed AS, Momani S, Hayat T (2016) Numerical solutions of fuzzy differential equations using reproducing kernel Hilbert space method. Soft Comput 20(8):3283–3302CrossRefzbMATHGoogle Scholar
Arqub OA, Al-Smadi M, Momani S, Hayat T (2017) Application of reproducing kernel algorithm for solving second-order, two-point fuzzy boundary value problems. Soft Comput 21(23):7191–7206CrossRefzbMATHGoogle Scholar
Arya Y, Kumar N (2016) AGC of a multi-area multi-source hydrothermal power system interconnected via AC/DC parallel links under deregulated environment. Electr Power Energy Syst 75:127–138CrossRefzbMATHGoogle Scholar
Bhateshvar YK, Mathur HD, Siguerdidjane H, Bhanot S (2015) Frequency stabilization for multi-area thermal–hydro power system using genetic algorithm-optimized fuzzy logic controller in deregulated environment. Electr Power Compon Syst 43(2):146–156CrossRefGoogle Scholar
Cheng Y, Tabrizi M, Sahni M, Povedano A, Nichols D (2014) Dynamic available AGC based approach for enhancing utility scale energy storage performance. Electr Power Energy Syst 5(2):1070–1078Google Scholar
Dash P, Saikia LC, Sinha N (2015) Comparison of performances of several FACTS devices using Cuckoo search algorithm optimized 2DOF controllers in multi-area AGC. Int J Electr Power Energy Syst 65:316–324CrossRefGoogle Scholar
Dhillon SS, Lather JS, Marwaha S (2016) Multi objective load frequency control using hybrid bacterial foraging and particle swarm optimized PI controller. Electr Power Energy Syst 79:196–209CrossRefGoogle Scholar
Elsisi M, Soliman M, Aboelela MAS, Mansour W (2016) Bat inspired algorithm based optimal design of model predictive load frequency control. Electr Power Energy Syst 83:426–433CrossRefGoogle Scholar
Fahmi A, Abdullah S, Amin F, Siddque N, Ali A (2017) Aggregation operators on triangular cubic fuzzy numbers and its application to multi-criteria decision making problems. J Intell Fuzzy Syst 33:3323–3337CrossRefGoogle Scholar
Fahmi A, Abdullah S, Amin F, Ali A (2018a) Weighted average rating (war) method for solving group decision making problem using triangular cubic fuzzy hybrid aggregation (Tcfha). Punjab Univ J Math 50(1):23–34MathSciNetGoogle Scholar
Fahmi A, Abdullah S, Amin F, Ali A, Khan WA (2018b) Some geometric operators with triangular cubic linguistic hesitant fuzzy number and their application in group decision-making. J Intell Fuzzy Syst. https://doi.org/10.3233/jifs-18125Google Scholar
Fahmi A, Amin F, Smarandache F, Khan M, Hassan N (2018d) Triangular cubic hesitant fuzzy einstein hybrid weighted averaging operator and its application todecision making. Symmetry 10(11):658CrossRefGoogle Scholar
Hota PK, Mohanty B (2016) Automatic generation control of multi source power generation under deregulated environment. Electr Power Energy Syst 75:205–214CrossRefGoogle Scholar
Mohanty B, Hota PK (2015) Comparative performance analysis of fruit fly optimisation algorithm for multi-area multisource automatic generation control under deregulated environment. IET Gener Transm Distrib 9(14):1845–1855CrossRefGoogle Scholar
Naidu K, Mokhlis H, Bakar AHA, Terzija V, Illias HA (2014) Application of firefly algorithm with online wavelet filter in automatic generation control of an interconnected reheat thermal power system. Electr Power Energy Syst 63:401–413CrossRefGoogle Scholar
Omar Abu Arqub (2017) Adaptation of reproducing kernel algorithm for solving fuzzy Fredholm-Volterra integrodifferential equations. Neural Comput Appl 28(7):1591–1610CrossRefGoogle Scholar
Sahu RK, Panda S, Sekhar GC (2015) A novel hybrid PSO-PS optimized fuzzy PI controller for AGC in multi area interconnected power systems. Electr Power Energy Syst 64:880–893CrossRefGoogle Scholar
Sekhar GC, Sahu RK, Baliarsingh AK, Panda S (2016) Load frequency control of power system under deregulated environment using optimal firefly algorithm. Electr Power Energy Syst 74:195–211CrossRefGoogle Scholar
Sharma G, Nasiruddin I, Niazi KR, Bansal RC (2016) Optimal AGC of a multi-area power system with parallel AC/DC tie lines using output vector feedback control strategy. Electr Power Energy Syst 81:22–31CrossRefGoogle Scholar
Shiva CK, Mukherjee V (2015) Automatic generation control of multi-unit multi-area deregulated power system using a novel quasi-oppositional harmony search algorithm. IET Gener, Transm Distrib 9(15):2398–2408CrossRefGoogle Scholar
Singh S, Parmar KP, Majhi S, Kothari DP (2012) Load frequency control of a realistic power system with multi-source power generation. Electr Power Energy Syst 42:426–433CrossRefGoogle Scholar
Sundararaj V (2016) An efficient threshold prediction scheme for wavelet based ECG signal noise reduction using variable step size firefly algorithm. Int J Intell Eng Syst 9(3):117–126Google Scholar
Sundararaj V, Muthukumar S, Kumar RS (2018) An optimal cluster formation based energy efficient dynamic scheduling hybrid MAC protocol for heavy traffic load in wireless sensor networks. Comput Secur 77:277−288CrossRefGoogle Scholar
Xie P, Li Y, Zhu L, Shi D, Duan X (2016) Supplementary automatic generation control using controllable energy storage in electric vehicle battery swapping stations. IET Gener Transm Distrib 10(4):1107–1116CrossRefGoogle Scholar
Yousef H (2015) Adaptive fuzzy logic load frequency control of multi-area power system. Electr Power Energy Syst 68:384–395CrossRefGoogle Scholar