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

Publication . Foroozandeh, Zahra; Ramos, Sérgio; Soares, João; Lezama, Fernando; Vale, Zita; Gomes, António; Joench, Rodrigo L.

Efficient alternatives in energy production and consumption are constantly being investigated and conducted by increasingly strict policies. Buildings have a significant influence on electricity consumption, and their management may contribute to the sustainability of the electricity sector. Additionally, with growing incentives in the distributed generation (DG) and electric vehicle (EV) industries, it is believed that smart buildings (SBs) can play a key role in sustainability goals. In this work, an energy management system is developed to reduce the power demands of a residential building, considering the flexibility of the contracted power of each apartment. In order to balance the demand and supply, the electrical power provided by the external grid is supplemented by microgrids such as battery energy storage systems (BESS), EVs, and photovoltaic (PV) generation panels. Here, a mixed binary linear programming formulation (MBLP) is proposed to optimize the scheduling of the EVs charge and discharge processes and also those of BESS, in which the binary decision variables represent the charging and discharging of EVs/BESS in each period. In order to show the efficiency of the model, a case study involving three scenarios and an economic analysis are considered. The results point to a 65% reduction in peak load consumption supplied by an external power grid and a 28.4% reduction in electricity consumption costs.

2020Journal article

Open access

Optimizing Energy Consumption of Household Appliances Using PSO and GWO

Publication . Tavares, Inês; Almeida, José; Soares, João; Ramos, Sérgio; Vale, Zita; Foroozandeh, Zahra

Due to the increasing electricity consumption in the residential sector, new control systems emerged to control the demand side. Some techniques have been developed, such as shaping the curve’s load peaks by planning and shifting the electricity demand for household appliances. This paper presents a comparative analysis for the energy consumption optimization of two household appliances using two Swarm Intelligence (SI) algorithms: Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO). This problem’s main objective is to minimize the energy cost according to both machines’ energy consumption, respecting the restrictions applied. Three scenarios are presented: changing the energy market price during the day according to three types of energy tariffs. The results show that the user in the cheapest periods could switch on both machines because both techniques presented the highest energy consumption values. Regarding the objective function analysis, PSO and GWO obtained the best (more economical) values for the simple tariff due to its lower energy consumption. The GWO technique also presented more diverging values from the average objective function value than the PSO algorithm.

2021Journal article

Open access

Optimal Contract Power and Battery Energy Storage System Capacity for Smart Buildings

Publication . Foroozandeh, Zahra; Ramos, Sérgio; Soares, João; Vale, Zita

This paper proposed a Mixed Binary Linear Programming (MBLP) approach to find the optimal size of some components of a Smart Building (SB) attempting to reduce the overall cost. The considered SB is equipped with local resources such as Photovoltaic (PV) panels, Electrical Vehicles (EVs), and the Battery Energy Storage System (BESS). Moreover, the SB is only connected with the grid by an Energy Management System (EMS) in which the whole SB has a single Contract Power (CP) such that EMS manages the power flow among external grid, local resources, apartments, and common services, for the goal of reducing the electricity bill. Hence, the wrong choice of CP and BESS capacity will impose unnecessary charges on the electricity bill. As a results, EMS has played a crucial role in SB in determining the best CP and BESS values. The obtained results of this work show the efficiency of the model in which by finding the optimal capacity of CP and BESS, the electricity bill improves by a 34% reduction

2021Journal article

Open access

Shared PV Production in Energy Communities and Buildings Context

Publication . Ramos, Sérgio; Foroozandeh, Zahra; Soares, João; Tavares, Inés; Faria, Pedro; Vale, Zita

Across Europe, householders have taken the opportunity to produce their electricity, helping them to reduce their electricity bill as well as reducing carbon emissions, by installing rooftop Photovoltaic Panels (PV) on their buildings. New adequate business models are needed for improving the sharing of PV between consumers in a community. Both technical and economic aspects should be considered in a clear way for consumers to understand and benefit from the community. In this paper, an overview of energy communities is provided to support the innovative PV sharing models for buildings, which are proposed in a way to be clear for community members. The developed concepts are supported by the formulation of the optimization problem to be solved by the community manager.

2021-09Conference object

Open access