Abstract
Exporting generated electricity by on-site renewable energy systems from buildings to the grid is only slightly profitable in many countries. Therefore, it is required to investigate the benefits of sharing generated energy in a microgrid within a community of buildings. Exploiting the benefits of peer-to-peer energy exchange between prosumers in a community can make the best use of the on-site generation while reducing their bills. This study elaborates the potential of energy management to minimize the electricity cost of a community consisted of multiple buildings and connected to a microgrid. To implement this, an energy management system is designed based on non-linear economic model predictive control and successive linear programming for sharing the on-site surplus generated electricity between the buildings in the community. Four buildings are simulated and studied as an example of a small community. These buildings are dissimilar in their age, thermal mass, insulation, heating system and on-site renewable energy systems. It is shown that considering the community of buildings as a single entity, the novel model predictive control can be efficiently used for minimizing the energy cost of the community that has various sources of energy generation, conversion and storage, including significant non-linear interactions. Three different scenarios of the energy management system for the studied community are investigated, and the results indicate that the annual electricity energy cost for single buildings can be reduced by 3.0% to 87.9%, depending on the building and its systems, and by 5.4% to 7.7% on the community level.
| Original language | English |
|---|---|
| Article number | 114178 |
| Journal | Energy Conversion and Management |
| Volume | 239 |
| DOIs | |
| Publication status | Published - 1 Jul 2021 |
| MoE publication type | A1 Journal article-refereed |
Funding
The first author is supported by a personal grant from The Finnish Foundation for Technology Promotion/The Foundations' Post Doc Pool. This paper was partly funded by two Academy of Finland projects: “Advanced Energy Matching for Zero-Energy Buildings in Future Smart Hybrid Networks 2014-2018, Decision no. 277680” and the Strategic Research Council (SRC) project “Smart Energy Transition (SET) – Realizing Its Potential for Sustainable Growth for Finland’s Second Century, Decision no. 314325”. The work is connected to the authors’ participation in the IEA-EBC Annex 67 – Energy Flexible Buildings.
