A MOPSO method for Direct Load Control in Smart Grid

作者: Jose Evora , Jose Juan Hernandez , Mario Hernandez

DOI: 10.1016/J.ESWA.2015.05.056

关键词:

摘要: We model electricity demand of a city in complex way including appliances and users.We propose scalable real time method for managing the demand.We implement this using multi-objective criteria optimisation algorithm.A solution loads is found within requirements.Demand can be reduced up to 20% by controlling three types appliances. In recent years, power grids have been evolving decentralised production control. Direct Load Control (DLC) methods are oriented manage on side. A DLC based Multi-Objective Particle Swarm Optimisation (MOPSO) algorithm described. This sets operation when restriction must accomplished. Since operate real-time, calculations distributed. The obtained dividing among neighbourhoods calculating multiple local optimisations. has experimentally evaluated through simulations.

参考文章(26)
Margarita Reyes Sierra, Carlos A. Coello Coello, Improving PSO-Based multi-objective optimization using crowding, mutation and ∈-dominance international conference on evolutionary multi criterion optimization. pp. 505- 519 ,(2005) , 10.1007/978-3-540-31880-4_35
M. Negnevitsky, D. T. Nguyen, M. de Groot, C. Wang, Demand response in the retail market: Benefits and challenges australasian universities power engineering conference. pp. 1- 6 ,(2009)
Carlos A. Coello Coello, A Comprehensive Survey of Evolutionary-Based Multiobjective Optimization Techniques Knowledge and Information Systems. ,vol. 1, pp. 269- 308 ,(1999) , 10.1007/BF03325101
Steven D. Silver, Phillip Cowans, Small world network model of personal consumption: Demand-side management in an expert system Expert Systems With Applications. ,vol. 35, pp. 632- 644 ,(2008) , 10.1016/J.ESWA.2007.07.058
R.T. Marler, J.S. Arora, Survey of multi-objective optimization methods for engineering Structural and Multidisciplinary Optimization. ,vol. 26, pp. 369- 395 ,(2004) , 10.1007/S00158-003-0368-6
Martin Lukasiewycz, Michael Glaß, Felix Reimann, Jürgen Teich, Opt4J Proceedings of the 13th annual conference on Genetic and evolutionary computation - GECCO '11. pp. 1723- 1730 ,(2011) , 10.1145/2001576.2001808
Aimin Zhou, Bo-Yang Qu, Hui Li, Shi-Zheng Zhao, Ponnuthurai Nagaratnam Suganthan, Qingfu Zhang, None, Multiobjective evolutionary algorithms: A survey of the state of the art Swarm and evolutionary computation. ,vol. 1, pp. 32- 49 ,(2011) , 10.1016/J.SWEVO.2011.03.001
Carlos A. Coello Coello, Margarita Reyes-Sierra, Multi-Objective Particle Swarm Optimizers: A Survey of the State-of-the-Art International Journal of Computational Intelligence Research. ,vol. 2, pp. 287- 308 ,(2006) , 10.5019/J.IJCIR.2006.68
Joshua D. Knowles, David W. Corne, Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy Evolutionary Computation. ,vol. 8, pp. 149- 172 ,(2000) , 10.1162/106365600568167