Title : 
Distributed multi-agent algorithm for residential energy management in smart grids
         
        
            Author : 
Mets, Kevin ; Strobbe, Matthias ; Verschueren, Tom ; Roelens, Thomas ; De Turck, Filip ; Develder, Chris
         
        
            Author_Institution : 
Dept. of Inf. Technol., Ghent Univ. - IBBT, Ghent, Belgium
         
        
        
        
        
        
            Abstract : 
Distributed renewable power generators, such as solar cells and wind turbines are difficult to predict, making the demand-supply problem more complex than in the traditional energy production scenario. They also introduce bidirectional energy flows in the low-voltage power grid, possibly causing voltage violations and grid instabilities. In this article we describe a distributed algorithm for residential energy management in smart power grids. This algorithm consists of a market-oriented multi-agent system using virtual energy prices, levels of renewable energy in the real-time production mix, and historical price information, to achieve a shifting of loads to periods with a high production of renewable energy. Evaluations in our smart grid simulator for three scenarios show that the designed algorithm is capable of improving the self consumption of renewable energy in a residential area and reducing the average and peak loads for externally supplied power.
         
        
            Keywords : 
distributed power generation; energy management systems; multi-agent systems; power engineering computing; smart power grids; bidirectional energy flows; demand-supply problem; distributed multiagent algorithm; distributed renewable power generators; energy production scenario; grid instabilities; historical price information; low-voltage power grid; market-oriented multiagent system; production mix; renewable energy production; renewable energy self consumption; residential energy management; smart grid simulator; smart power grids; solar cells; voltage violations; wind turbines; Green products; Prediction algorithms; Production; Renewable energy resources; Smart grids; Wind turbines; Multi-Agent System; Renewable Energy; Residential Energy Management; Smart Power Grids;
         
        
        
        
            Conference_Titel : 
Network Operations and Management Symposium (NOMS), 2012 IEEE
         
        
            Conference_Location : 
Maui, HI
         
        
        
            Print_ISBN : 
978-1-4673-0267-8
         
        
            Electronic_ISBN : 
1542-1201
         
        
        
            DOI : 
10.1109/NOMS.2012.6211928