A Novel Thermal Energy Storage System in Smart Building Based on Phase Change Material

Wei, Fanrong; Li, Yuanzheng; Sui, Quan; Lin, Xin; Chen, Le; Chen, Zhe; Li, Zhengtian

doi:10.1109/tsg.2018.2812160

Cited by 47 publications

(18 citation statements)

References 34 publications

(50 reference statements)

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“…This paper develops a new DR using distributed electric heating storage (DEHS) in distributed heating networks for the optimal dispatch of CEHN. Compared with the above DRs, DEHS has the following characteristics which have also been indicated in the previous works such as [12] and [13]. a) DEHS operates as both an electric load and a heat source.…”

Section: Introductionmentioning

confidence: 86%

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Optimal dispatch based on prediction of distributed electric heating storages in combined electricity and heat networks

Wang

Chen

et al. 2020

Applied Energy

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The volatility of wind power generations could significantly challenge the economic and secure operation of combined electricity and heat networks. To tackle this challenge, this paper proposes a framework of optimal dispatch with distributed electric heating storage based on a correlation-based long short-term memory prediction model. The prediction model of distributed electric heating storage is developed to model its behavior characteristics which are obtained by the autocorrelation and correlation analysis with external factors including weather and time-of-use price. An optimal dispatch model of combined electricity and heat networks is then formulated and resolved by a constraint reduction technique with clustering and classification. Our method is verified through numerous simulations. The results show that, compared with the state-of-the-art techniques of support vector machine and recurrent neural networks, the mean absolute percentage error with the proposed correlation-based long short-term memory can be reduced by 1.009 and 0.481 respectively. Compared with conventional method, the peak wind power curtailment with dispatching distributed electric heating storage is reduced by nearly 30% and 50% in two cases respectively.

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Section: Introductionmentioning

confidence: 86%

“…Based on the above analysis, DEHS can be considered as an excellent choice to provide additional flexibility to the CEHN. The electric heating storage system has been studied in [13]. However, its focus is the performance of the device without the consideration of prediction and optimal dispatch in CEHN.…”

Section: Introductionmentioning

confidence: 99%

Optimal dispatch based on prediction of distributed electric heating storages in combined electricity and heat networks

Wang

Chen

et al. 2020

Applied Energy

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“…In addition to the above mentioned, many other cases have been studied on HVAC [18][19][20][21][22][23][24][25][26][27]. In the present paper, a model predictive control (MPC) method has been used for controlling temperature and humidity which was previously only introduced for controlling temperature in [28][29][30].…”

Section: Related Workmentioning

confidence: 99%

Modeling and Controlling of Temperature and Humidity in Building Heating, Ventilating, and Air Conditioning System Using Model Predictive Control

et al. 2019

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Nowadays, by huge improvements in industrial control and the necessity of efficient energy consumption for buildings, unified managing systems are established to monitor and control mechanical equipment and energy usage. One of the main portions of the building management system (BMS) is the cooling and heating equipment called heating and ventilation and air-conditioning (HVAC). Based on temperature slow dynamic and presented uncertainty in modeling, a model predictive control (MPC) strategy to track both temperature and humidity is proposed in this study. The main goal of this study is to provide a framework to describe temperature and humidity elements required for dynamic modeling. Following that, by utilizing a predictive approach, a control strategy is obtained, which optimizes the tracking error of two interactional channel and performs the effort control by minimizing the optimization index. Other articles have mostly only had control over the temperature variable, but in our article, we tried to study the equations of temperature and humidity as well as their interference and according to the ASHRAE standard, both temperature and humidity controls must be accurate. The humidity was the novelty in our article. Simulation results proved the effectiveness of the proposed approach compared to the conventional proportional-integral controller. Evidently, the key idea behind the control objective is providing the comfort condition while consuming the least possible energy.

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“…Relevant research has proved that large-scale thermal storage system can e ectively improve the exible dispatching ability of the system. However, new materials such as thermal storage or phase-change thermal storage need to be further studied [65]. At present, the related research of solar thermal power generation technology [66] has attracted wide attention.…”

Section: Optimal Operation Of Ies Considering Electro-gas-ermalmentioning

confidence: 99%

A Survey on Optimal Control and Operation of Integrated Energy Systems

Wei

Zhang

et al. 2019

Complexity

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At present, the transformation of energy structure is at a critical stage, and emerging renewable energy technologies and multienergy equipment have been widely used. How to improve the energy efficiency of integrated energy system (IES) and promote large-scale absorption of renewable energy is of great significance to the application forms of energy in the future. The development of new internet technology and sensor technology provides strong technical support for the optimal operation and coordinated control of IES. In recent years, the IES is experiencing unprecedented changes, which has attracted great attention from academia and industry. In this paper, the optimal control and operation behavior of IES are reviewed. Firstly, the research status of IES in recent years is summarized. Then, the modeling methods of different equipment in IES are analyzed in detail. The optimal operation of user, regional, and cross-regional IES are taken as typical research objects and the research status of optimization problems and operation modes, energy management planning, and power market allocation are summarized and analyzed. Finally, the key scientific issues and related frontier technologies in the IES are concluded, and the future research directions are prospected.

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A Novel Thermal Energy Storage System in Smart Building Based on Phase Change Material

Cited by 47 publications

References 34 publications

Optimal dispatch based on prediction of distributed electric heating storages in combined electricity and heat networks

Optimal dispatch based on prediction of distributed electric heating storages in combined electricity and heat networks

Modeling and Controlling of Temperature and Humidity in Building Heating, Ventilating, and Air Conditioning System Using Model Predictive Control

A Survey on Optimal Control and Operation of Integrated Energy Systems

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