A novel linear predictive control approach for auxiliary energy supply to a solar thermal combistorage

Pichler, Martin; Lerch, Werner; Heinz, Andreas; Goertler, Gregor; Schranzhofer, Hermann; Rieberer, René

doi:10.1016/j.solener.2013.12.015

Cited by 19 publications

(7 citation statements)

References 26 publications

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“…Heat transfer coefficient between the water in the tank and environment air is 33 . 0 = s U ) /( 2 K m W [10]. The heat flux w Q delivered from storage tank to the user is expressed as:…”

Section: The Mathematical Modelmentioning

confidence: 99%

“…Loomans and Visser [9] pointed out the application of the genetic algorithm in a design support tool to optimize the design parameters of solar hot water systems such as the collector areas, the thermal storage tank volumes, and the collector heat exchanger area and so on. Pichler et al [10] proposed a linear predictive control approach for auxiliary energy supply to improve collected solar energy and minimize auxiliary heat demand of the solar assisted heating systems for a single-family house. From the numerical results the authors concluded that the auxiliary energy demand can be reduced up to 40% while the maximum increasing of the monthly solar fractions is 5%.…”

Section: Introductionmentioning

confidence: 99%

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Theoretical and Experimental Investigation on Performance Improvement of Solar Hot Water System Under Real Weather Conditions at Ho Chi Minh City, Vietnam

Nhut¹

2018

AJETM

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This paper presents the results of theoretical and experimental investigation to determine the optimal flow rate of collector loop to improve the performance of a solar hot water system under real weather conditions at Ho Chi Minh City, Vietnam. The optimal flow rate of flat-plate collector loop is researched based on the relationship between the useful heat gain of the flat plate collectors and the electricity consumption of the collector pump. The result of the simulation and experiment shows that the optimal flow rate was determined at the value of 0.132 (kg/s). Besides, the effects of various parameters such as initial water temperature of storage tank, flat plate collector area and volume of storage tank are investigated. Furthermore, the validation of simulation and experiment results of the progress of the water temperature in the storage tank is also evaluated.

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“…Heat transfer coefficient between the water in the tank and environment air is 33 . 0 = s U ) /( 2 K m W [10]. The heat flux w Q delivered from storage tank to the user is expressed as:…”

Section: The Mathematical Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Theoretical and Experimental Investigation on Performance Improvement of Solar Hot Water System Under Real Weather Conditions at Ho Chi Minh City, Vietnam

Nhut¹

2018

AJETM

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“…Another attempt to use linear predictive control approach to reduce the use of auxiliary energy demand and increase solar yields by using weather forecast data, was made by [22], which demonstrated the feasibility of the proposed approach for a solar thermal water tank with auxiliary heating elements for a residential house.…”

Section: Literature Reviewmentioning

confidence: 99%

Maximizing photovoltaic array energy usage within a house using model predictive controla

Ahmad

Anderson

Lie

et al. 2017

2017 Asian Conference on Energy, Power and Transportation Electrification (ACEPT)

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In this study, the problems of modeling, energy dispatching and Photovoltaic (PV) array energy priorities for a grid connected residential house with PV array and battery storage using model predictive control (MPC) have been investigated. Artificial neural network (ANN) based global solar radiation forecast was used to plan in advance for periods of low sunshine. MPC was able to reduce electricity consumption in the house when solar radiation forecast was unfavorable. Quadratic programming optimization was used to maximize usage of the PV system. Excess energy from the PV array was used to further raise hot water cylinder (HWC) temperature, rather than exporting it to the utility grid. Performance of the overall model predictive control system was verified using simulation results.

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“…The control problems addressed can be classified in two categories: energy demand matching and indoor climate control. In the demand‐matching case the problem relates to proper scheduling of the operation of available energy systems to cover predicted energy demands (Pichler et al., ). Although a physics‐based model can be utilized as part of the control‐design process, in many cases machine learning techniques utilizing available historical data have been successfully used to generate empirical models.…”

Section: The Sta Frameworkmentioning

confidence: 99%

Sense‐Think‐Act Framework for Intelligent Building Energy Management

Katsigarakis

Kontes

Giannakis

et al. 2015

Computer aided Civil Eng

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The realization of smart and energetically efficient buildings is contingent upon the successful implementation of two tasks that occur on distinct phases component. An illustrative application of the proposed methodology in an office building is provided. MOTIVATIONEffective utilization of energy in buildings is receiving significant attention. This interest is justified on the observation that buildings account for a significant portion of end-energy use: in Europe 40% of the total energy consumed is used for the operation of buildings (Perez-Lombard et al., 2008) with a significant part of that energy used for conditioning occupied spaces. Energy retrofits, properly selected and executed, can yield appreciable reduction in energy demands. But the value of effective energy utilization during the building operational phase is undisputed both in terms of achieving good occupant comfort and in reducing energy consumption.In domestic environments the extensive research on intelligent temperature regulation and the proliferation of smart thermostats and home automation solutions are partly a response to that need. In the nondomestic building sector Building Energy Management Systems (BEMS) are used to ensure proper operation of systems and components in an energyefficient manner. Typical BEMS installations comprise a communication and data management layer enabling communication and data transfer between interacting field devices (sensors, actuators, field controllers); C 2015 Computer-Aided Civil and Infrastructure Engineering.

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A novel linear predictive control approach for auxiliary energy supply to a solar thermal combistorage

Cited by 19 publications

References 26 publications

Theoretical and Experimental Investigation on Performance Improvement of Solar Hot Water System Under Real Weather Conditions at Ho Chi Minh City, Vietnam

Theoretical and Experimental Investigation on Performance Improvement of Solar Hot Water System Under Real Weather Conditions at Ho Chi Minh City, Vietnam

Maximizing photovoltaic array energy usage within a house using model predictive controla

Sense‐Think‐Act Framework for Intelligent Building Energy Management

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