Optimal energy management and sizing of renewable energy and battery systems in residential sectors via a stochastic MILP model

Abstract

Energy supply through integrated renewable energy sources (RESs) and battery systems will be of higher importance for future residential sectors. Optimal energy management and sizing for the components of residential systems can enhance efficiency, self-suffiency, and meanwhile can be cost-effective by reducing investment as well as operating costs. Accordingly, this paper proposes an exhaustive optimization model for determining the capacity of RESs, namely: wind turbines and photovoltaic (PV) systems. In this study, batteries and electric vehicles (EVs) are utilized in line with other sources to capture fluctuations of RESs. To model the uncertainties of RESs, energy prices, and load demands a linearized stochastic programming framework is applied. The proposed framework involves long-term and efficient resource development alongside with short-term management and utilization of these resources for supplying the demand load. In our study, we utilize the roulette wheel mechanism (RWM) method as well as proper probability distribution functions (PDFs) to generate scenarios for all sources of uncertainties, including wind turbines, PV systems, demand, and electricity market price. The approach is verified in two different cases, including an individual home and a larger micro-grid (MG). The results of multiple numerical simulations demonstrate the effectiveness of the proposed stochastic model.

Simulation of Electric Vehicle Charging Stations Load Profiles in Office Buildings Based on Occupancy Data

“…Previous research supports the importance of conducting EV modeling, investigating EVs and the related impact on the electric power system. Reference [9] proposes an optimization model for determining the capacity of RES, while utilizing EVs with other sources to capture fluctuations of RES. Reference [10] utilizes Support Vector Regression (SVR) approach to create a charging load forecasting model based on various historical data.…”

Optimal Sizing of Rooftop PV and Battery Storage for Grid-Connected Houses Considering Flat and Time-of-Use Electricity Rates

“…The impact of energy management systems on the optimal sizing problem of rooftop PV and BESS was evaluated in [20]. In [21], a techno-economic analysis of rooftop PV and BESS for GCHs in Finland was adopted.…”

“…Electricity Rate DSOC Degradation of BESS Grid Constraint Salvation Value [12] Flat [13] TOU and RTP [14] TOU [15] Flat [16] Flat and TOU [17] TOU [18] Flat [19] TOU [20] Flat [21] TOU [22] Flat [23] TOU [24] Flat [25] Flat [26] Flat…”

Development of the Technical Structure of the “Cow Energy” Concept

“…In the case of e-mobility, coordination between the various users is difficult to plan [17]. This results in uncertainties about when and where energy is needed and high safety reserves [18]. In the building sector, there is again uncertainty about the needs of the different users, which limits flexibility [19].…”