Optimal planning of combined heat and power systems within microgrids

In this paper, an optimal deployment with respect to capacity sizes and types of DG (distributed generation) for CHP (combined heat and power) systems within microgrids was presented. The objective was to simultaneously minimize the total net present cost and carbon dioxide emission. A multi-objecti...

Full description

Saved in:
Bibliographic Details
Published in:Energy (Oxford) 2015-12, Vol.93, p.235-244
Main Authors: Zidan, Aboelsood, Gabbar, Hossam A., Eldessouky, Ahmed
Format: Article
Language:English
Subjects:
CHP
Combined heat and power
Demand
Electric power generation
Electric power grids
Gas-power
Generators
Genetic algorithm
Genetic algorithms
Microgrid system
Multi-objective
Optimization
Renewable
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, an optimal deployment with respect to capacity sizes and types of DG (distributed generation) for CHP (combined heat and power) systems within microgrids was presented. The objective was to simultaneously minimize the total net present cost and carbon dioxide emission. A multi-objective GA (genetic algorithm) was applied to solve the planning problem including the optimization of DG type and capacity. The constraints include power and heat demands constraints, and DGs capacity limits. The candidate technologies involved in this study include CHP generators (with different characteristics), boilers, thermal storage, renewable generators (wind and photovoltaic), and a main power grid connection. The surplus/deficient electricity can possibly be sold to/bought from the main grid. Costs of CHP generators are based on their types and the capacity range. The approach was applied to a typical CHP system within microgrid system as a case study, and the effectiveness of the proposed method was verified. •Optimal deployment of CHP within microgrids based on capacity.•Minimize total cost and carbon dioxide emission in microgrids.•Use GA (genetic algorithm) to optimize the planning of CHP within microgrids.•CHP integration with boilers within microgrids.
ISSN:0360-5442
DOI:10.1016/j.energy.2015.09.039