The Economic Dispatch of Wind Integrated Power System based on an Improved Differential Evolution Algorithm

Author(s): Haiqing Liu, Jinmeng Qu, Yuancheng Li*

Journal Name: Recent Advances in Electrical & Electronic Engineering
Formerly Recent Patents on Electrical & Electronic Engineering

Volume 13 , Issue 3 , 2020

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Graphical Abstract:


Background: As more and more renewable energy such as wind energy is connected to the power grid, the static economic dispatch in the past cannot meet its needs, so the dynamic economic dispatch of the power grid is imperative.

Methods: Hence, in this paper, we proposed an Improved Differential Evolution algorithm (IDE) based on Differential Evolution algorithm (DE) and Artificial Bee Colony algorithm (ABC). Firstly, establish the dynamic economic dispatch model of wind integrated power system, in which we consider the power balance constraints as well as the generation limits of thermal units and wind farm. The minimum power generation costs are taken as the objectives of the model and the wind speed is considered to obey the Weibull distribution. After sampling from the probability distribution, the wind speed sample is converted into wind power. Secondly, we proposed the IDE algorithm which adds the local search and global search thoughts of ABC algorithm. The algorithm provides more local search opportunities for individuals with better evolution performance according to the thought of artificial bee colony algorithm to reduce the population size and improve the search performance.

Results: Finally, simulations are performed by the IEEE-30 bus example containing 6 generations. By comparing the IDE with the other optimization model like ABC, DE, Particle Swarm Optimization (PSO), the experimental results show that obtained optimal objective function value and power loss are smaller than the other algorithms while the time-consuming difference is minor. The validity of the proposed method and model is also demonstrated.

Conclusion: The validity of the proposed method and the proposed dispatch model is also demonstrated. The paper also provides a reference for economic dispatch integrated with wind power at the same time.

Keywords: Dynamic economic dispatch, wind farm, weibull distribution, improved differential evolution, artificial bee colony, integrated power system.

A.W. Bizuayehu, A.A. Sánchez de la Nieta, J. Contreras, and J.P.S. Catalão, "Impacts of stochastic wind power and storage participation on economic dispatch in distribution systems", IEEE Transact. Sustain. Energ., vol. 7, no. 3, pp. 1336-1345, 2016.
T. Xu, W. Wu, W. Zheng, H. Sun, and L. Wang, "Fully distributed Quasi-Newton multi-area dynamic economic dispatch method for active distribution networks", IEEE Trans. Power Syst., vol. 33, no. 4, pp. 4253-4263, 2017.
J. Li, Interactive energy-saving dispatch considering generation and demand side uncertainties: A chinese studyIEEE Transact. Smart Grid, PP, no. 99, pp. 1-1. 2016
M-R. Andervazh, and S. Javadi, "Emission-economic dispatch of thermal power generation units in the presence of hybrid electric vehicles and correlated wind power plants", IET Gener. Transm. Distrib., vol. 11, no. 9, pp. 2232-2249, 2017.
Y.Z. Li, Multi-objective optimal dispatch of microgrid under uncer-tainties via interval optimizationEEE Transactions on Smart Grid, PP, no. 99, pp. 1-1. 2017
M. Di Somma, G. Graditi, E. Heydarian-Forushani, M. Shafie-khah, and P. Siano, Stochastic optimal scheduling of distributed energy resources with renewable sconsidering economic and environmental aspectsRenew. Energ, vol. 116. no. A, pp. 272-287. 2018
H. Chen, R. Zhang, G. Li, L. Bai, and F. Li, "Economic dispatch of wind integrate power systems with energy storage considering composite operating costs", IET Gener. Transm. Distrib., vol. 10, no. 5, pp. 1294-1303, 2016.
B. Wang, S. Wang, X-Z. Zhou, and J. Watada, "Two-stage multi-objective unit commitment optimization under hybrid uncertainties", IEEE Trans. Power Syst., vol. 31, no. 3, pp. 2266-2277, 2016.
S-D. Lu, and M-C. Tsou, "Considering carbon emissions in economic dispatch planning for isolated power systems-a case study of the taiwan power system", IEEE Trans. Ind. Appl., vol. 54, no. 2, pp. 987-997, 2018.
A. Cherukuri, and J. Cortés, "distributed coordination of DERS with storage for dynamic economic dispatch", IEEE Trans. Automat. Contr., vol. 63, no. 3, pp. 835-842, 2018.
W. Liu, P. Zhuang, H. Liang, J. Peng, and Z. Huang, Distributed economic dispatch in microgrids based on co-operative reinforcement learningIEEE Transact. Neur. Netw. Learn. Syst., vol. 29. no. 6, . 2018
Y. Arya, "AGC of restructured multi-area multi-source hydrothermal power systems incorporating energy storage units via optimal fractional order fuzzy PID controller", Neural Comput. Appl., vol. 31, pp. 851-872, 2017.
Y. Arya, "Automatic generation control of two-area electrical power systems via optimal fuzzy classical controller", J. Franklin Inst., vol. 355, no. 5, pp. 2662-2688, 2018.
Y. Arya, "Improvement in automatic generation control of two-area electric power systems via a new fuzzy aided optimal PIDN-FOI controller", ISA Trans., vol. 80, pp. 475-490, 2018.
[] [PMID: 30122501]
B. Gjorgiev, and M.Č. Epin, "A multi-objective optimization based solution for the combined economic-environmental power dispatch problem", Eng. Appl. Artif. Intell., vol. 26, no. 1, pp. 417-429, 2013.
Y. Arya, and N. Kumar, "Fuzzy gain scheduling controllers for AGC of two-area interconnected electrical power systems", Electr. Power Compon. Syst., vol. 44, no. 7, pp. 737-751, 2016.
A. Shukla, and S.N. Singh, "Multi-objective unit commitment with renewable energy using hybrid approach", IET Renew. Power Gener., vol. 10, no. 3, pp. 327-338, 2016.
C. Duan, L. Jiang, W. Fang, J. Liu, and S. Liu, "Data-driven distributionally robust energy-reserve-storage dispatch", IEEE Trans. Industr. Inform., vol. 14, no. 7, pp. 2826-2836, 2018.
H. Gangammanavar, S. Sen, and V.M. Zavala, "Stochastic optimization of sub-hourly economic dispatch with wind energy", IEEE Trans. Power Syst., vol. 31, no. 2, pp. 949-959, 2016.
M.G.M. Abdolrasol, M.A. Hannan, A. Mohamed, U.A.U. Amiruldin, and I.Z. Abidin, "An optimal scheduling controller for virtual power plant and microgrid integration using binary backtracking search algorithm", IEEE Trans. Ind. Appl., vol. 54, no. 3, pp. 2834-2844, 2018.
G. Chen, J. Ren, and E.N. Feng, "Distributed finite-time economic dispatch of a network of energy resources", IEEE Trans. Smart Grid, vol. 8, no. 2, pp. 822-832, 2017.
T. Luz, P. Moura, and A. de Almeida, "Multi-objective power generation expansion planning with high penetration of renewables", Renew. Sustain. Energy Rev., vol. 81, no. 2, pp. 2637-2643, 2018.
H.F. Zhang, F. Gao, J. Wu, and K. Liu, "A dynamic economic dispatching model for power grid containing wind power generation system", Power System Technology, vol. 37, no. 5, pp. 1298-1303, 2013.
A.P. Piotrowski, "Differential evolution algorithms applied to neural network training suffer from stagnation", Appl. Soft Comput., vol. 21, no. 5, pp. 382-406, 2014.
P. Lu, J. Zhou, H. Zhang, R. Zhang, and C. Wang, "Chaotic differential bee colony optimization algorithm for dynamic economic dispatch problem with valve-point effects", Int. J. Electr. Power Energy Syst., vol. 62, no. 11, pp. 130-143, 2014.

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Article Details

Year: 2020
Published on: 17 May, 2020
Page: [384 - 395]
Pages: 12
DOI: 10.2174/2213111607666181226150448
Price: $25

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