Optimal energy management of a micro-grid with renewable energy resources and demand response

With the introduction of smart energy grids and extensive penetration of renewable energy resources in distribution networks, Micro-Grids (MGs), which are comprised of various alternative energy resources and Advanced Metering Infrastructure (AMI) systems for better implementation of DR programs, ar...

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Bibliographic Details
Published in:Journal of renewable and sustainable energy 2013-09, Vol.5 (5)
Main Authors: Parvizimosaed, M., Farmani, F., Anvari-Moghaddam, A.
Format: Article
Language:English
Subjects:
Alternative energy sources
Distribution management
Electric power grids
Electric vehicles
Energy distribution
Energy management
Energy management systems
Energy resources
Energy sources
Hybrid electric vehicles
Mixed integer
Multiple objective analysis
Optimization
Renewable energy
Renewable resources
Resource management
System effectiveness
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Summary:With the introduction of smart energy grids and extensive penetration of renewable energy resources in distribution networks, Micro-Grids (MGs), which are comprised of various alternative energy resources and Advanced Metering Infrastructure (AMI) systems for better implementation of DR programs, are effectively employed. The design and development of Smart Energy Management Systems (SEMSs) for MGs are interesting and attractive research problems. In this paper a new SEMS architecture is presented to solve the multi-objective operation management and scheduling problem in a typical MG while considering different energy resource technologies, Plug-in Hybrid Electric Vehicles (PHEVs) and DR programs. The energy management problem is formulated as a constrained mixed integer nonlinear multi-objective optimization problem, in which the MG's total operating cost and net emissions must be minimized simultaneously. Three different optimization algorithms are used to solve the above mentioned problem and their outputs (Pareto optimal solutions) for the same problem are compared and analyzed.
ISSN:1941-7012
1941-7012
DOI:10.1063/1.4826880