Header menu link for other important links
X
Optimization of microgrid with demand side management using genetic algorithm
Published in
2013
Volume: 2013
   
Issue: 15377
Abstract
In a smart grid environment, economic operation means not only to economic scheduling of generation, but also to scheduling the load. In a Microgrid (MG), which comprises of intermittent Distributed Generators (DGs) (eg. solar and wind energy sources), the need of Demand Side Management (DSM)/Demand Response (DR) becomes significant. The key point in DSM is to shift the load to some other point in time, this causes inconvenience to the customer and therefore it should be minimized. Minimizing the cost of generation and also minimizing the inconvenience caused due to shifting of loads is a multi-objective optimization problem. In this work the authors consider an industrial/commercial MG with one solar source, two diesel generators and one battery, with the assumption that the utility grid uses dynamic pricing. The objective function contains discontinuous functions which will be difficult to solve using conventional optimization techniques and hence a Genetic Algorithm (GA) based solution is proposed. The simulation results show that there is savings for the customer with DSM compared to the case without DSM.
About the journal
JournalIET Seminar Digest
Open AccessNo
Concepts (13)
  •  related image
    CONVENTIONAL OPTIMIZATION
  •  related image
    Demand side managements
  •  related image
    DISCONTINUOUS FUNCTIONS
  •  related image
    DISTRIBUTED GENERATOR (DGS)
  •  related image
    ECONOMIC SCHEDULING
  •  related image
    Micro grid
  •  related image
    Multi-objective optimization problem
  •  related image
    SOLAR AND WIND ENERGIES
  •  related image
    Distributed power generation
  •  related image
    Optimization
  •  related image
    Scheduling
  •  related image
    Wind power
  •  related image
    Genetic algorithms