Abstract
Generally, energy management in smart buildings is formulated by mixed-integer linear programming, with different optimization goals. The most targeted goals are the minimization of the electricity consumption cost, the electricity consumption value from external power grid, and peak load smoothing. All of these objectives are desirable in a smart building, however, in most of the related works, just one of these mentioned goals is considered and investigated. In this work, authors aim to consider two goals via a multi-objective framework. In this regard, a multi-objective mixed-binary linear programming is presented to minimize the total energy consumption cost and peak load in collective residential buildings, considering the scheduling of the charging/discharging process for electric vehicles and battery energy storage system. Then, the Pascoletti-Serafini scalarization approach is used to obtain the Pareto front solutions of the presented multi-objective model. In the final, the performance of the proposed model is analyzed and reported by simulating the model under two different scenarios. The results show that the total consumption cost of the residential building has been reduced 35.56% and the peak load has a 45.52% reduction.
Highlights
The use of renewable energy resources solar photovoltaic (PV)panels in buildings are rapidly increasing, which contributes to supply the needed electric power of the building
Note that, when e = 0, the single-Objective problem is solved in order to minimize the total energy cost(the optimal achieved value is 39.031 7 EUR). when e = 1, the singleObjective problem is solved in order to minimize the demanded peak load
Each residential consumers has its own electrical contract power. This approach proposes the flexibility of the customer contracted power taking into consideration the energy management resources, namely, photovoltaic generation, battery energy storage system and electrical vehicles usage
Summary
The use of renewable energy resources solar photovoltaic (PV)panels in buildings are rapidly increasing, which contributes to supply the needed electric power of the building. Electric Vehicles (EVs) scheduling usage, could be useful for energy management in. Extensive research work has been done on the topic of building energy management in order to schedule renewable energy sources with different goals [2,3,4,5,6] and, as well as other studies, largely focused on the energy resource, such as the EV [7]. The model in [8] proposes to minimizes the buildings power demand and its electricity costs by optimizing the charging and discharging process of Plug-In Hybrid Electric Vehicles (PHEVs).The restrictions contain limitations for the State of Charge (SoC) of the PHEV and imposes that the electrical energy is not sold and bought at the same time for or from power grid. The main goal in the research work [9] is to minimize the daily electricity cost
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