Parameter identification and model based predictive control of temperature inside a house

Bălan, Radu; Cooper, Joshua; Chao, Kuo‐Ming; Stan, Sergiu-Dan; Donca, Radu

doi:10.1016/j.enbuild.2010.10.023

Cited by 94 publications

(44 citation statements)

References 8 publications

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“…The unsteady-state heat flow across walls is very complicated as part of heat passing through walls is captured and later released to either the indoor air or outdoor ambient. Therefore, the thermal dynamic model of a two-parameter model could be expressed as below [17].…”

Section: Thermostatically Load Modelingmentioning

confidence: 99%

Direct load control by distributed imperialist competitive algorithm

Luo

Zhao

Wang

et al. 2014

J. Mod. Power Syst. Clean Energy

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Demand side management techniques have drawn significant attentions along with the development of smart grid. This paper proposes a new direct load control (DLC) model for scheduling interruptible air conditioner loads. The model is coordinated with the unit commitment and economic dispatch to minimize the total operation cost over the whole dispatch horizon. The network constraints are also considered in the model. To ensure the thermal comfort of the occupants, we are among the first to incorporate the advanced two-parameter thermal inertia dynamical model of customer houses into the DLC model to calculate the indoor temperature variation. This paper also proposes a distributed imperialist competitive algorithm to effectively solve the model. The simulation studies prove the efficiency of the proposed methodology.

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Section: Thermostatically Load Modelingmentioning

confidence: 99%

Direct load control by distributed imperialist competitive algorithm

Luo

Zhao

Wang

et al. 2014

J. Mod. Power Syst. Clean Energy

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show abstract

“…An adequate model can be the basis of for example model based control, model predictive control, or hybrid control systems [8,9]. Model based approaches can be used in the field of temperature control using HVAC systems [2] A CFD model can be used to understand the operating conditions, and the temperature profiles in a device, and then the obtained information can be used to support controller design, and tuning tasks [6].…”

Section: Introductionmentioning

confidence: 99%

Examination of temperature probe setup using computational fluid dynamics simulators

Egedy

Varga

Chován

2012

Per. Pol. Chem. Eng.

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“…Compared with the thermal models in [19,22], we innovatively improve the model performance by calculating air conditioner coefficient of performance (COP) shown in (5), which defines the ratio of cooling or heating energy supplied by the air conditioner over its consumed electrical energy. The efficiency of this novel two-parameter thermal model has been shown in our previous published works [12,18,24].…”

Section: Introductionmentioning

confidence: 99%

“…Since the thermal Fig. 1 Schematic of thermal models models' complexity can pose significant impact on the accuracy of calculating cooling energy, the more complex and accurate model in [22] is chosen here.…”

Section: Introductionmentioning

confidence: 99%

Optimal air-conditioning load control in distribution network with intermittent renewables

Wang

Meng

Gao

et al. 2016

J. Mod. Power Syst. Clean Energy

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The coordinated operation of controllable loads, such as air-conditioning load, and distributed generation sources in a smart grid environment has drawn significant attention in recent years. To improve the wind power utilization level in the distribution network and minimize the total system operation costs, this paper proposes a MILP (mixed integer linear programming) based approach to schedule the interruptible air-conditioning loads. In order to mitigate the uncertainties of the stochastic variables including wind power generation, ambient temperature change, and electricity retail price, the rolling horizon optimization (RHO) strategy is employed to continuously update the real-time information and proceed the control window. Moreover, to ensure the thermal comfort of customers, a novel two-parameter thermal model is introduced to calculate the indoor temperature variation more precisely. Simulations on a five node radial distribution network validate the efficiency of the proposed method.

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Parameter identification and model based predictive control of temperature inside a house

Cited by 94 publications

References 8 publications

Direct load control by distributed imperialist competitive algorithm

Direct load control by distributed imperialist competitive algorithm

Examination of temperature probe setup using computational fluid dynamics simulators

Optimal air-conditioning load control in distribution network with intermittent renewables

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