Optimal smart home energy management considering energy saving and a comfortable lifestyle

Anvari‐Moghaddam, Amjad; Monsef, Hassan; Rahimi-Kian, Ashkan

doi:10.1109/pesgm.2016.7741432

Cited by 64 publications

(113 citation statements)

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“…Moreover, if a room/building is supplied by the multiple energy systems, we just need to add energy balance equations for energy flow from supply to demand and operational constraints for energy generation devices to the model. As shown in many references, such as [9], [11], and [29], the energy balance equation is always linear and the constraints for the energy generation devices are always formulated by the mixed integer linear programming. Therefore, these extensions can easily be integrated with our problem and would not provide any difficulties to the application of the proposed ETM method.…”

Section: Discussionmentioning

confidence: 99%

“…We used a set of two-day (Nov. [11][12]2016) measured data of indoor air temperature, surface temperature of all the walls, cooling supplied by HVAC, solar radiation, and outdoor temperature to identify the optimal parameters of the room model by minimizing the error between the measured temperature and the simulated temperature obtained by the room model based on (8)- (9). The typical values of the parameters in (8)-(9), which are obtained from ASHRAE handbook [31], are used as the initial guesses in this optimization program.…”

Section: Set-up Of the Case Studiesmentioning

confidence: 99%

“…For example, based on the second type of the methods, an optimization problem was developed in [6] to capture a tradeoff between energy saving and thermal comfort level, a multi-objective optimization of energy consumption and thermal comfort was formulated in [7], and optimal control problems for HVAC system were developed in [10] and [24] respectively. Based on the third type of the methods, an optimization problem of a tradeoff between energy saving and air quality was developed in [8], an optimal scheduling problem for energy devices in smart homes was formulated in [9], and an joint control problem of active and passive heating, cooling, lighting, shading, and ventilation in buildings was addressed in [25].…”

Section: Introductionmentioning

confidence: 99%

“…For example, mixed integer programming is such a conventional method, since the problem always contains both continuous and discrete variables [9], [11]. Model predictive control (MPC) is another method usually used to address the problem under uncertainties.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

PMV-based event-triggered mechanism for building energy management under uncertainties

Spanos

et al. 2017

Energy and Buildings

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This paper provides a study of the optimal scheduling of building operation to minimize its energy cost under building operation uncertainties. Opposed to the usual way that describes thermal comfort using a static range of air temperature, the optimization of a tradeoff between energy cost and thermal comfort predicted mean vote (PMV) index is addressed in this paper. In order to integrate the calculation of the PMV index with the optimization procedure, we develop a sufficiently accurate approximation of the original PMV model which is computationally efficient. We develop a model-based periodic eventtriggered mechanism (ETM) to handle the uncertainties in the building operation. Upon the triggering of predefined events, the ETM determines whether the optimal strategy should be recalculated. In this way, the communication and computational resources required can be significantly reduced. Numerical results show that the ETM method is robust with respect to the uncertainties in prediction errors and results in a reduction of more than 60% in computation without perceivable degradation in system performance as compared to a typical closed-loop model predictive control.

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Section: Discussionmentioning

confidence: 99%

Section: Set-up Of the Case Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

PMV-based event-triggered mechanism for building energy management under uncertainties

Spanos

et al. 2017

Energy and Buildings

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“…Moreover, the relation between smart building residents' comfort and power consumption has recently drawn much interest. Therefore, a smart energy management solution that will reduce energy wastage while meaningfully balancing between energy cost savings and smart home residents' comfort level is necessary [5]. In addition, ways to reduce the impact of energy generation and consumption on the environment through minimization of greenhouse emission have drawn much interest.…”

Section: Introductionmentioning

confidence: 99%

Scheduling Distributed Energy Resource Operation and Daily Power Consumption for a Smart Building to Optimize Economic and Environmental Parameters

et al. 2018

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Abstract:In this paper, we address the problem of minimizing the total daily energy cost in a smart residential building composed of multiple smart homes with the aim of reducing the cost of energy bills and the greenhouse gas emissions under different system constraints and user preferences. As the household appliances contribute significantly to the energy consumption of the smart houses, it is possible to decrease electricity cost in buildings by scheduling the operation of domestic appliances. In this paper, we propose an optimization model for jointly minimizing electricity costs and CO 2 emissions by considering consumer preferences in smart buildings that are equipped with distributed energy resources (DERs). Both controllable and uncontrollable tasks and DER operations are scheduled according to the real-time price of electricity and a peak demand charge to reduce the peak demand on the grid. We formulate the daily energy consumption scheduling problem in multiple smart homes from economic and environmental perspectives and exploit a mixed integer linear programming technique to solve it. We validated the proposed approach through extensive experimental analysis. The results of the experiment show that the proposed approach can decrease both CO 2 emissions and the daily energy cost.

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Optimal planning and scheduling of smart homes' energy hubs

Pazouki

Haghifam

2021

Int Trans Electr Energ Syst

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This article presents a mathematical model for optimal planning and scheduling of smart homes' energy hubs (SHEHs). The electricity demand of the SHEH model is formulated and categorized into four different loads: lighting loads, delay intolerant loads (DILs), delay tolerant loads (DTLs), and other electrical loads (OELs). The SHEH also includes heat, cooling, and water demands. Lighting demand includes sunlight that illuminates the house during the day and the required electricity power for illuminating the house in the absence of daylight. Cooler/heater, freezer, and fridge are DILs and they cannot tolerate any electricity interruption. Washer, dryer, and dishwasher are DTLs which can be operated at different times. Electricity demand is supplied by wind turbine (WT), photovoltaic (PV), and combined heat and power (CHP). Electric vehicle-charging station (EV-CS) can be used as a backup for them. The heat demand is supplied by CHP and boiler (B). Thermal storage (TS) is used as their backup. Water demand is supplied via water pump (WP) and cooling demand is supplied by absorption chiller (AC). Simulation is applied to a residential building. General algebraic modeling system (GAMS) software is utilized to solve the problem. The simulation results demonstrate the electricity demand formed by the DILs, DTLs, lighting, and OELs. The sizes of the aforementioned SHEH components (WT, PV, CHP, EV-CS, B, TS, WP, and AC) are calculated. The SHEH is scheduled based on the mathematical model and the optimal size of the components. Finally, sensitive analysis is implemented to confirm the proposed approach.

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Optimal smart home energy management considering energy saving and a comfortable lifestyle

Cited by 64 publications

References 0 publications

PMV-based event-triggered mechanism for building energy management under uncertainties

PMV-based event-triggered mechanism for building energy management under uncertainties

Scheduling Distributed Energy Resource Operation and Daily Power Consumption for a Smart Building to Optimize Economic and Environmental Parameters

Optimal planning and scheduling of smart homes' energy hubs

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