Intelligent Agent-Based Architecture for Demand Side Management Considering Space Heating and Electric Vehicle Load
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Author(s)
Contraction of resilience on generation side due to
the introduction of inflexible renewable energy sources is demanding
more elasticity on consumption side. It requires more intelligent
systems to be implemented to maintain power balance in the grid and to
fulfill the consumer needs. This paper is concerned about the energy
balance management of the system using intelligent agent-based
architecture. The idea is to limit the peak power of each individual
household for different defined time regions of the day according to
power production during those time regions. Monte Carlo Simulation (MCS)
has been employed to study the behavior of a particular number of
house- holds for maintaining the power balance based on proposed
technique to limit the peak power for each household and even individual
load level. Flexibility of two major loads i.e. heating load (heat
storage tank) and electric vehicle load (battery) allows us to shift the
peaks on demand side proportionally with the generation in real time.
Different parameters related to heating and Electric Vehicle (EV) load
e.g. State of Charge (SOC), storage capacities, charging power, daily
usage, peak demand hours have been studied and a technique is proposed
to mitigate the imbalance of power intelligently.
Cite this paper
Malik, F. , Ali, M. and Lehtonen, M. (2014)
Intelligent Agent-Based Architecture for Demand Side Management
Considering Space Heating and Electric Vehicle Load. Engineering, 6, 670-679. doi: 10.4236/eng.2014.611066.
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