Optimal management of energy sharing in a community of buildings using a model predictive control

Behrang Vand,Reino Ruusu,Ala Hasan,Benjamin Manrique Delgado

doi:10.1016/j.enconman.2021.114178

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.

Highlights

Buildings are responsible for approximately 40% of energy con sumption and 36% of carbon dioxide emissions in the European Union Countries [1,2]
Significant research has been conducted on: improving the solar heating factor of a community through seasonal storage [5]; pro sumers that export surplus heat to the district heating grid [6]; the economic competitiveness of microgrids and how they are affected by policies [7]; the energetic and economic potential of heat and electricity prosumers exporting to the distribution grids [8,9] or as part of a community [10] and life-cycle optimizations for embodied and opera tional emissions of buildings [11,12]
This study presents the results of the implementation of a developed energy management system in a community of buildings with the aim to minimize the operational energy cost

Summary

Introduction

Buildings are responsible for approximately 40% of energy con sumption and 36% of carbon dioxide emissions in the European Union Countries [1,2]. The energy management strategies that aim to reduce the demand by the end-user in coordination/collaboration with the utilities are cate gorized as demand-side management (DSM) [13,14,15]. Among the different DSM methods applied in buildings, demand response pursues optimal matching between the dynamics of energy demand and supply [16,17]. Demand response has sparked vast interest in the field due to its multiple advantages for both the end-user and the grid operator: for the former, demand response allows reducing the expenses on energy by shifting loads to times of the day when prices are lower [18] for the latter, demand response allows reducing the peak loads and distributing the energy demand to times when the grid is less saturated [19,20]. The implementation of this strategy requires a detailed investigation of its effect on the comfort level inside the building: if this aspect is overseen, the indoor temperature might be undesirable

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Results

Conclusion