Opportunities for Smart Electric Thermal Storage on Electric Grids With Renewable Energy

Wong, Steven; Pinard, Jean-Paul

doi:10.1109/tsg.2016.2526636

Cited by 34 publications

(27 citation statements)

References 10 publications

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“…The working principle of electrical heat storage technology is to heat the medium using the electrical heat devices during the valley period and release the thermal energy at the peak period to meet the demand of buildings and houses [25][26][27]. The typical heat storage devices include electrical boilers with heat storage and heat pump units.…”

Section: Electrical Boilers With Heat Storage and Heat Pump Unitsmentioning

confidence: 99%

A review on the influence of intelligent power consumption technologies on the utilization rate of distribution network equipment

He¹,

Chen²,

Yang

et al. 2018

Prot Control Mod Power Syst

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The economy of distribution networks largely depends on the utilization rate of distribution network equipment. Most of the emerging intelligent power consumption technologies have a positive effect on equipment utilization and their use can save investment of distribution networks. In this paper, the influence of intelligent power consumption technologies on the utilization rate of distribution network equipment is reviewed. The evaluation methods and indexes are assessed first and then intelligent power consumption equipment with energy storage function, vehicle-to-grid (V2G) technology and time-of-use (TOU) tariff are reviewed respectively. It is concluded that these intelligent power consumption technologies and measures have great potential to improve utilization rate of distribution network equipment because of their effective improvement to power load. Meanwhile, recommendations on how to utilize these intelligent power consumption technologies to improve utilization rate of distribution network equipment are proposed.

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Section: Electrical Boilers With Heat Storage and Heat Pump Unitsmentioning

confidence: 99%

A review on the influence of intelligent power consumption technologies on the utilization rate of distribution network equipment

He¹,

Chen²,

Yang

et al. 2018

Prot Control Mod Power Syst

View full text Add to dashboard Cite

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“…It is found that ETS and wind resources can play complementary roles to meet energy demands in isolated grids. 45 ETS is effective in reducing diesel consumption, and thus greenhouse gas emissions, by capturing the wind and hydro potential that would otherwise be spilled.…”

Section: Energy Efficiency and Renewable Energymentioning

confidence: 99%

A review on the features and technologies for energy efficiency of smart grid

Anjana¹,

Shaji

2017

Int J Energy Res

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Summary In today's world striving for efficiency in every sector, especially power generation and distribution, smart grids emerge as the solution for efficiently meeting the increasing demand. They adjust themselves to optimally deliver energy at the lowest cost and highest quality possible. The grid successfully makes use of renewable energy resources, electric vehicles, and smart pricing techniques in its attempt to achieve energy efficiency. It also promotes a greener environment by striving to reduce greenhouse gas emissions. Information communication technology (ICT) helps the grid in collecting consumption data from the consumers and in sharing tariff information. ICT also helps to gather information about the status of the grid with regard to aspects like power quality, faults etc. The purpose of this paper is to review recent literature with a view to comprehensively present the technologies employed in the smart grid for achieving energy efficiency and the challenges involved therein.

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“…A physical model (PM) of SETS is integrated into an energy management system for isolated microgrids [3]. SETS is used to accommodate wind power to supply heat load in isolated microgrids [4]. A PM for residential…”

Section: Introductionmentioning

confidence: 99%

Electricity Consumption Prediction of Solid Electric Thermal Storage with a Cyber–Physical Approach

Yang

Wang

et al. 2019

Energies

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This paper proposes a cyber-physical approach to enhance the prediction accuracy of electricity consumption of solid electric thermal storage (SETS) system, which integrates a physical model and a data-based cyber model. In the cyber-physical model, the prediction error of the physical model is used as an input of the cyber model to further calibrate the prediction error. Firstly, customers' behavior characteristics are extracted by the integration of K-means and one-versus-one support vector machine. Secondly, based on the behavior characteristics and ambient temperature, the physical model is developed to predict daily electricity consumption. Finally, the error levels of physical model are classified, together with the temperature and prediction values of the physical model, are selected as the inputs of the cyber model using the back propagation (BP) neural network to calibrate the results of the physical model. The effectiveness of the proposed cyber-physical model (CPM) is verified by a 1 MW SETS system. The simulation results show that, compared with the physical model (PM) and cyber model (CM), the maximum relative errors (MRE) with the CPM are reduced to 25.4% and 4.8%, respectively.Energies 2019, 12, 4744 2 of 18 forced-air electric furnaces is built to predict the thermal energy storage, which is an early application of SETS [5]. This work does not take into account the effect of continuously changing the ambient temperature on thermal energy storage. A PM is integrated into the TRNSYS calculation tool to evaluate the optimal thermal energy storage of forced-air electric furnaces with changing ambient temperature [6]. Therefore, it is necessary to improve the basis of the existing methods, and enhance the prediction accuracy. However, the customers' behavior characteristics of SETS are not considered in the above-mentioned PMs, which is very important to improve the accuracy of prediction.In [7], a sparse continuous conditional random fields method was proposed to predict electric load with the identification of behavior. The data from advanced metering infrastructure is used to understand the power consumption patterns to improve the load forecasting accuracy in [8].The prediction accuracy would be significantly enhanced with the consideration of behavior. However, the working mode of SETS are completely different from those of conventional electric loads [9]. SETS is charged by the off-peak electricity, and its thermal energy is released all-day. During the off-peak hours, usually from 21:00 to 6:00, the heating elements quickly heat the dense bricks to a high temperature owning to its cheaper electricity prices. During the peak period from 6:00 to 21:00, the heating elements are switched off, and SETS continues to release its thermal energy to warm the rooms. Many behavior characteristics of SETS directly affect the heat load demand, such as all-day continuous work (e.g., convenience store), and holiday and non-holiday period (e.g., star hotel), which need to be considered. The conventional models o...

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Opportunities for Smart Electric Thermal Storage on Electric Grids With Renewable Energy

Cited by 34 publications

References 10 publications

A review on the influence of intelligent power consumption technologies on the utilization rate of distribution network equipment

A review on the influence of intelligent power consumption technologies on the utilization rate of distribution network equipment

A review on the features and technologies for energy efficiency of smart grid

Electricity Consumption Prediction of Solid Electric Thermal Storage with a Cyber–Physical Approach

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