Energy-Intensive Manufacturing Enterprises as Active Players in Demand Side Management System

被引:3
作者
Voropai, Nikolai [1 ]
Styczynski, Zbigniew [2 ]
Komarnicki, Przemyslaw [2 ]
Stepanov, Vladimir [3 ]
Suslov, Konstantin [3 ]
Stashkevich, Elena [3 ]
机构
[1] RAS Irkutsk, Energy Syst Inst SB, Irkutsk, Russia
[2] Otto von Guericke Univ, Magdeburg, Germany
[3] Irkutsk Natl Res Tech Univ, Irkutsk, Russia
来源
2016 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE EUROPE (ISGT-EUROPE) | 2016年
关键词
Demand side management; Demand response; Electrical load curve; Electric power system; Active consumers; ELECTRICITY; GAME;
D O I
10.1109/ISGTEurope.2016.7856321
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Nowadays, one of the primary problems in the energy industry is ensuring rational operating conditions of electric power systems under variable loads and with regard to cost-effectiveness and technical capabilities of power plants. Supply fluctuated load considerably increases the costs in the power systems. The price of electricity in the case by changed load is generally higher than by constant load. This price cannot be decreased without cooperation with consumers. The last decade has shown an intensive adoption of new smart tools and technologies for automation in the electricity supply systems, which make it possible to increase the speed of receiving, transferring, processing and mapping the information, and to implement new capabilities of active behavior of consumers in managing their electricity demand on the basis of market mechanisms. The paper addresses a technique for the optimization of daily load curve for the case of a specified tariff mix. The genetic algorithms are used to apply the cost benefits. The usefulness of this method is illustrated by two case studies of energy-intensive manufacturing enterprises as active consumers and players on the energy market
引用
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页数:6
相关论文
共 22 条
  • [1] [Anonymous], 2013, INT J REVENUE MANAGE
  • [2] Bachry A., P 2003 IEEE POW ENG, V2, P763
  • [3] Flexible demand in the GB domestic electricity sector in 2030
    Drysdale, Brian
    Wu, Jianzhong
    Jenkins, Nick
    [J]. APPLIED ENERGY, 2015, 139 : 281 - 290
  • [4] Fazeli A., P 2011 IEEE PES INN
  • [5] Lombardi P., P 2009 IEEE POW EN S
  • [6] Use of Energy Storage in Isolated Micro Grids
    Lombardi, Pio
    Styczynski, Zbigniew
    Sokolnikova, Tatiana
    Suslov, Kostantin
    [J]. 2014 POWER SYSTEMS COMPUTATION CONFERENCE (PSCC), 2014,
  • [7] Typification of load curves for DSM in Brazil for a smart grid environment
    Macedo, Maria N. Q.
    Galo, Joaquim J. M.
    Almeida, Luiz A. L.
    Lima, Antonio C. C.
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2015, 67 : 216 - 221
  • [8] Development of an Application for Brazilian Energy Tariff Choice
    Magalhaes, F. B.
    Fortes, F. Z.
    Vidaurre, R. M.
    Fortes, M. Z.
    [J]. IEEE LATIN AMERICA TRANSACTIONS, 2015, 13 (04) : 1005 - 1010
  • [9] A Novel Demand Response Model with an Application for a Virtual Power Plant
    Mnatsakanyan, Ashot
    Kennedy, Scott W.
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2015, 6 (01) : 230 - 237
  • [10] Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid
    Mohsenian-Rad, Amir-Hamed
    Wong, Vincent W. S.
    Jatskevich, Juri
    Schober, Robert
    Leon-Garcia, Alberto
    [J]. IEEE TRANSACTIONS ON SMART GRID, 2010, 1 (03) : 320 - 331