Optimal Model for Energy Management Strategy in Smart Building with Energy Storage Systems and Electric Vehicles

Abstract

The aim of this work was to develop an optimal model for an energy management strategy in a real micro-grid, which involves a smart building, a photovoltaic system with storage, and a plug-in full electric vehicle. A controller based on a mathematical algorithm was the core of each strategy, which directly acted on a relay board managing the interconnection between the different elements comprising the micro-grid. The development of an optimization model involving binary variables required an efficient code that achieved solutions in a short time. The analyzed case-study corresponded to the solar energy research center (CIESOL) smart building, a bioclimatic building, that is located at the University of Almería (Spain), designated to research in renewable energies. Using the methodologies described in this work, the total cost of the smart building energy consumption was minimized by decreasing the power supplied from the grid, especially at peak hours. Highlighting the use of a simple model that provided better performance than the current state of the art methodologies. The optimal model for energy management strategy demonstrated the advantages of using classical optimization techniques to solve this specific optimization problem, compared to a rule-based controller. The linear modeling was capable of producing a simple algorithm with less code development and a reduction in the computational effort.

Smart District Energy Management With Cooperative Microgrids

“…• day-ahead based approaches: [1]- [3], [7], [8], [10]- [25], [46]- [48], [50], [52], [55]; • deterministic approaches: [7]- [9], [13], [15], [17], [18], [20], [21], [26]- [35], [42], [44]- [46], [49]- [57]; • uncertainties management/stochastic approaches: [1],…”

“…[3], [10]- [19], [21], [23], [26]- [29], [34], [36]- [41], [44], [47]- [50], [52], [53], [55], [56]; • EV and V2G based approaches: [2], [7]- [9], [14], [15], [19], [23], [24], [31], [32], [35], [36], [49], [51]; • RES and/or ESS based approaches: [1]- [3], [7]- [42],…”

Towards Optimal Management in Microgrids: An Overview

“…Starting with the latter, an MILP problem was presented in [75] that minimized the power supplied by the public grid, which included continuous variables to model the power flow and binary variables for the state of the relays enabling or disabling certain power fluxes. The problem was solved for an MG located in the CIESOL bioclimatic building at the University of Almería, which was described in [47].…”

Energy Management in Smart Building by a Multi-Objective Optimization Model and Pascoletti-Serafini Scalarization Approach

“…In this work, the schedule of the EVs/BESS charge and discharge processes is optimized using a Mixed Binary Linear Programming (MBLP) model in which the charging/discharging of EVs and BESS, in each time period, is modeled by binary variables. In Reference [13], a mathematical model is developed for building energy management that consisted a BESS, a PV and a fully plug-in EV. The model in this work manage the power flow between the resources by using a rule-based controller.…”