scholarly journals Mixed integer smart off-grid home energy management system

2021 ◽  
Vol 7 ◽  
pp. 9094-9107
Author(s):  
Rasha Elazab ◽  
Omar Saif ◽  
Amr M.A. Amin Metwally ◽  
Mohamed Daowd
Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3323 ◽  
Author(s):  
Bharath Rao ◽  
Friederich Kupzog ◽  
Martin Kozek

Most typical distribution networks are unbalanced due to unequal loading on each of the three phases and untransposed lines. In this paper, models and methods which can handle three-phase unbalanced scenarios are developed. The authors present a novel three-phase home energy management system to control both active and reactive power to provide per-phase optimization. Simplified single-phase algorithms are not sufficient to capture all the complexities a three-phase unbalance system poses. Distributed generators such as photo-voltaic systems, wind generators, and loads such as household electric and thermal demand connected to these networks directly depend on external factors such as weather, ambient temperature, and irradiation. They are also time dependent, containing daily, weekly, and seasonal cycles. Economic and phase-balanced operation of such generators and loads is very important to improve energy efficiency and maximize benefit while respecting consumer needs. Since homes and buildings are expected to consume a large share of electrical energy of a country, they are the ideal candidate to help solve these issues. The method developed will include typical distributed generation, loads, and various smart home models which were constructed using realistic models representing typical homes in Austria. A control scheme is provided which uses model predictive control with multi-objective mixed-integer quadratic programming to maximize self-consumption, user comfort and grid support.


Author(s):  
Yue Zhao ◽  
Yan Chen ◽  
Brian Keel

For a household microgrid with renewable photovoltaic (PV) panel and plug-in electric vehicles (PEVs), a home energy management system (HEMS) using model predictive control (MPC) is designed to achieve optimal PEV charging and energy flow scheduling. Soft electric loads and an energy storage system (ESS) are also considered in the optimization of PEV charging in the MPC framework. The MPC is solved through a mixed-integer linear programming (MILP) by considering the relationship of energy flows in the optimization problem. Through the simulation results, the performance of optimization results under various electricity price plans is evaluated. The influences of PV capacities on the optimization results of electricity cost are also discussed.


2018 ◽  
Vol 40 (8) ◽  
pp. 2498-2508 ◽  
Author(s):  
Hasan İzmitligil ◽  
Hanife Apaydn Özkan

In this study, an offline home energy management system that reduces electricity expense and peak demand without deteriorating residents’ contentment is considered. The main goal is to improve the system in the sense of reducing electricity expense, via interfering with appliances by means of interrupting as well as shifting their operation; and keeping up with the benefits of the newest technology, via plug-in hybrid electrical vehicle integration. The proposed offline home energy management system (OF-HEM) consists of smart electrical appliances, power resources (photovoltaic system, grid, backup battery), main controller, communication network and plug-in hybrid electrical vehicle. The main controller manages the power resources, appliances and plug-in hybrid electrical vehicle based on the solution of a mixed integer linear program with defined smart and energy-efficient operation constraints related to the smart appliances and power sources for data collected at the beginning of the day from the power resources and residents’ preferences. Conducted case studies demonstrate that OF-HEM significantly reduces electricity expenses and high peak demand.


2012 ◽  
Vol 132 (10) ◽  
pp. 695-697 ◽  
Author(s):  
Hideki HAYASHI ◽  
Yukitoki TSUKAMOTO ◽  
Shouji MOCHIZUKI

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