Optimal operation of energy systems of groups of large buildings


== Abstract ==

The development of microgrids has enabled prosumers to develop optimal power management and demand response (DR) strategies. Based on this idea, virtual prosumers and microgrids can be created in a traditional city structure, exploiting microgrids’ ability to operate connected or disconnected to the grid. Therefore, the development of more complex energy control and management systems becomes necessary.  In this thesis, an easy to apply and computationally efficient energy management system (EMS) has been developed in Matlab. It is based on a hierarchical multi-agent system aiming to minimize the operating cost of a microgrid, that consists of a group of buildings, renewable energy sources (RES), energy storage systems (ESS) and electric vehicles (EVs). The examined optimization problem is solved using the particle swarm optimization algorithm (PSO), that ensures the optimum use of every microgrid’s component. Based on the results obtained by applying the algorithm to the operation of the microgrid, both in the time frame of one day and one week, cost savings of 40% can be achieved while all the microgrid’s energy needs and operation constraints are met.


== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.26233/heallink.tuc.84794 http://dx.doi.org/10.26233/heallink.tuc.84794]

* [http://purl.tuc.gr/dl/dias/924BBF62-2E1E-4D9F-94C7-2F40FF44C202 http://purl.tuc.gr/dl/dias/924BBF62-2E1E-4D9F-94C7-2F40FF44C202] under the license License: http://creativecommons.org/licenses/by-nd/4.0/