Parameter identification of thermal models for domestic electric water heaters in a direct load control program

Shaad, M.; Momeni, Ahmad; Diduch, C. P.; Kaye, Mary E.; Chang, Liuchen

doi:10.1109/ccece.2012.6334885

Cited by 33 publications

(14 citation statements)

References 19 publications

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“…Residential EWH models show changes in the water temperature inside the tank due to water usage, heat loss, and incoming power. A single‐element EWH model is proposed in Dolan et al and Gustafson et al and widely used in many other studies . This model is easy to implement, and its parameters are easily identified.…”

Section: Methodsmentioning

confidence: 99%

“…A single-element EWH model is proposed in Dolan et al 32 and Gustafson et al 33 and widely used in many other studies. [34][35][36][37][38] This model is easy to implement, and its parameters are easily identified. One assumption this model makes is that the water temperature remains uniform inside the tank and depends on the thermal characteristics of the EWH tank.…”

Section: Single Ewh Modelmentioning

confidence: 99%

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Optimizing 100%‐renewable grids through shifting residential water‐heater load

Ali¹,

Lenzen

Tyedmers

2019

Int J Energy Res

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Summary A low‐carbon electricity supply for Australia was simulated, and the installed capacity of the electrical grid was optimized by shifting the electricity demand of residential electric water heaters (EWHs). The load‐shifting potential of Australia was estimated for each hour of the simulation period using a nationwide aggregate EWH load model on a 90 × 110 raster grid. The electricity demand of water heaters was shifted from periods of low renewable resource and high demand to periods of high renewable resource and low demand, enabling us to effectively reduce the installed capacity requirements of a 100%‐renewable electricity grid. It was found that by shifting the EWH load by just 1 hour, the electricity demand of Australia could be met using purely renewable electricity at an installed capacity of 145 GW with a capacity factor of 30%, an electricity spillage of 20%, and a generation cost of 15.2 ¢/kWh. A breakdown of the primary energy sources used in our scenario is as follows: 43% wind, 29% concentrated solar thermal power, and 20% utility photovoltaic. Sensitivity analysis suggested that further reduction in installed capacity is possible by increasing the load‐shifting duration as well as the volume and insulation level of the EWH tank.

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Section: Methodsmentioning

confidence: 99%

Section: Single Ewh Modelmentioning

confidence: 99%

Optimizing 100%‐renewable grids through shifting residential water‐heater load

Ali¹,

Lenzen

Tyedmers

2019

Int J Energy Res

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“…The water inside the boiler is supposed to have unique homogeneous temperature [13]. When a given volume of hot water is used, the same volume of cold water flows into the boiler from outside.…”

Section: B Domestic Water Heatersmentioning

confidence: 99%

Impact analysis of load control for frequency regulation: The case of Sardinia in 2020

Baccino

Conte

Silvestro

et al. 2014

IEEE PES Innovative Smart Grid Technologies, Europe

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This paper analyses the impact on the frequency regulation of a possible strategy of demand side management (DSM) within a realistic scenario of the Sardinian electric network, in a 2020 forecast horizon. The DSM method is designed for supporting primary and secondary frequency regulation through thermostatically controlled loads. The cases of domestic refrigerators and water heaters are considered. The proposed solution is evaluated through a simulation study carried out within a dedicated simulation platform. Results show the potential advantages and drawbacks of the considered strategy and help to identify modifications and improvements for increasing the performances and the feasibility in the use of DSM for frequency regulation.

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“…This design choice makes the control problem more challenging because on each device the identification of the TCL dynamics, the estimation of its state on its control has to be carried out with only power consumption measurements and ON/OFF control capability. For instance, in [12] the problem of identifying the dynamics of the TCL was addressed by either considering its internal temperature measurable or at least assuming that the temperature range of the thermostat (maximum and minimum temperature) was known in absolute terms. In this paper, we only exploit power consumption measurement to develop a real plug-and-play approach which does not require any system configuration by the user.…”

Section: Introductionmentioning

confidence: 99%

Multi-Agent Coordination of Thermostatically Controlled Loads by Smart Power Sockets for Electric Demand Side Management

Franceschelli

Pilloni

Gasparri

2021

IEEE Trans. Contr. Syst. Technol.

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This paper presents a multi-agent control architecture and an online optimization method based on dynamic average consensus to coordinate the power consumption of a large population of Thermostatically Controlled Loads (TCLs). Our objective is to penalize peaks of power demand, smooth the load profile and enable Demand Side Management (DSM). The proposed architecture and methods exploit only local measurements of power consumption via Smart Power Sockets (SPSs) with no access to their internal temperature. No centralized aggregator of information is exploited and agents preserve their privacy by cooperating anonymously only through consensus-based distributed estimation, robust to node/link failure. The interactions among devices are designed to occur through an unstructured peer-to-peer (P2P) network over the internet.The architecture includes novel methods for parameter identification, state estimation and mixed logical modelling of TCLs and SPSs. It is designed from a multi-agent and plug-and-play perspective in which existing household appliances can interact with each other in an urban environment.Finally, a novel low cost testbed is proposed along with numerical tests and an experimental validation. Index TermsMulti-agent systems, demand side management, thermostatically controlled loads, online optimization, dynamic consensus, anonymous agents, distributed predictive control.The research leading to these results has received funding from the Italian Ministry of Research and Education (MIUR) with project "CoNetDomeSys", code RBSI14OF6H, under call SIR 2014.M. Franceschelli is with the

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Parameter identification of thermal models for domestic electric water heaters in a direct load control program

Cited by 33 publications

References 19 publications

Optimizing 100%‐renewable grids through shifting residential water‐heater load

Optimizing 100%‐renewable grids through shifting residential water‐heater load

Impact analysis of load control for frequency regulation: The case of Sardinia in 2020

Multi-Agent Coordination of Thermostatically Controlled Loads by Smart Power Sockets for Electric Demand Side Management

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