Optimization of Building Energy Exchange Using Simulated Annealing

Exchange of energy between buildings is in nowadays a major field of research. The demanding for clean energy production have led a lot of households to install photovoltaics (PV) in order to produce energy and reduce their overall energy cost. This paper presents an energy exchange model between buildings with different load demands during the day according to their use. Four categories of buildings are examined: Residential, Public, Commerce and Entertainment. Assuming that PVs with different levels of power generation are installed and that all buildings are available for cooperation results to a Linear Optimization (LP) problem. The unknown variables are the presentence of energy that each building can provide to a set of other cooperative buildings from the remaining PV energy in order to reduce the overall total energy demand from the grid. LP problems are easy to solve with a small number of unknowns but large-scale problems cannot always be solved. Thus, Simulated Annealing (SA) algorithm is used for the optimization. SA is used to a variety of optimization problems giving very good results, has very low complexity and is easy to implement. MatLab is used for both implementing SA and analyzing the results. Implementation of the proposed cooperative model results to an energy saving up to 22% of total energy demand from the grid without cooperation between buildings.