A Mixed-Binary Linear Programming Model for Optimal Energy Management of Smart Buildings

Abstract

Efficient alternatives in energy production and consumption are constantly investigated by increasingly strict policies. In this way, the pollutant emissions that contribute to the greenhouse effect reduce and sustainability of the electricity sector increase. With more than a third of the world's energy consumption, buildings have great potential to contribute these sustainability goals. Additionally, with growing incentives in the Distributed Generation (DG) and Electric Vehicle (EV) industry, it is believed that Smart Buildings (SBs) can be a key in the field of residential energy sustainability in the future. In this work, an energy management system in SBs are developed to reduce the power demanded of a residential building. In order to balance the demand and power provided by the grid, microgrids such as Battery Energy Storage System (BESS), EVs and Photovoltaic Generation panels (PV) are used. Here, a Mixed Binary Linear Programming formulation (MBLP) is proposed to optimize the charge and discharge scheduling of EVs and also BESS. In order to show the efficiency of the model, a case study involving three scenarios and an economic analysis is considered. The results point a 65% reduction in peak load consumption supplied by grid and a 28.4% reduction in electricity consumption costs.

Goal Programming Approach for Energy Management of Smart Building

“…As mentioned in Section IV-A, the Goal Programming approach is proposed aiming to minimize the total electricity cost of each apartment. To evaluate the performance of the proposed model (23), the obtained results were compared with the classic model [20]. In the classic model, the objective function is considered as a single-objective Mixed-Binary linear Problem (MBLP) that minimizes the total consumption cost of the whole building [21].…”

“…Despite the best values for all 3 performance parameters cannot being achieved simultaneously, the implemented heuristic algorithm (hybrid elephant adaptive cuckoo) revealed efficiency in managing the load consumption. The authors of papers [19] and [20] investigate the possibility of decreasing the energy costs by moving loads from high-demand to lowdemand periods time by charging and discharging EVs and BESS.…”

“…In Reference [20], the peak load is minimized in the SB by using an energy management system. It is assumed that the CP of each client is flexible and a single CP is applied for the whole building.…”

“…In [21], an MBLP formulation is proposed to minimize the total electricity cost, in which the the whole residential building is powered by a single contract power and an energy management system is considered for managing the flow of power among the resources. In the proposed problem, the optimal contract power value is determined where in [20] the contract power was fixed. Moreover, the best charging and discharging schedule for EVs and BESS id obtained.…”

“…The main difference of this work with previous work [19], [20] and [21] is proposing a MOMBLP model in which the energy consumption cost of each consumer is considered as objective functions. In addition, the GP approach is used for solving the proposed model to find the more appropriate solution with fair benefit among the building users.…”