Modelling residential house electricity demand profile and analysis of peaksaver program using ANN: case study for Toronto, Canada

Poulad, M. Ebrahim; Fung, Alan S.; Lei, He; Çolpan, C. Özgür

doi:10.1504/ijgw.2016.077911

Cited by 1 publication

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“…Residential-scale DR initiatives have also been implemented in the real world. In Ontario, Canada, a group of LDCs have implemented the peaksaver PLUS program (Poulad, Fung, He, & Colpan, 2016). This program involved signaling participating residential thermostats to pause during certain summer peak hours, halting air conditioner operation (Hydro Ottawa Ltd., 2016).…”

Section: Energy Management Systemsmentioning

confidence: 99%

Residential energy management systems with renewables and battery energy storage

Brookson¹

2021

Preprint

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With increasing concern towards the environmental impact of energy production, distribution, and consumption in the modern world, the overall energy landscape is changing. This Master’s Thesis investigates methods of addressing these inevitable transformations through the incorporation of renewable energy and energy storage on the residential-scale using energy management systems (EMSs). A simulated residential house model was developed in order to compare a variety of different energy management techniques on the same basis. The simulated EMS investigation has covered: deterministic EMSs, those in their most basic forms; adaptive EMSs, utilizing machine learning and predictive control algorithms; and, a transactional EMS. The deterministic EMSs produced the least annual cost savings, but are the simplest to implement. Adaptive EMSs have shown the highest estimated cost savings, with increased controller complexity as a trade-off. The transactive EMS has shown intermediate cost savings, with additional potential benefits such as demand response and community integration capabilities. Experimental work has been conducted verifying critical claims of the systems, focusing on battery output control and inter-agent controller communication. The most interesting areas warranting future research involve implementing predictive control experimentally – and on a wider scale – and investigating transactive control on the community level.

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Section: Energy Management Systemsmentioning

confidence: 99%

Residential energy management systems with renewables and battery energy storage

Brookson¹

2021

Preprint

View full text Add to dashboard Cite

show abstract

Modelling residential house electricity demand profile and analysis of peaksaver program using ANN: case study for Toronto, Canada

Cited by 1 publication

References 0 publications

Residential energy management systems with renewables and battery energy storage

Residential energy management systems with renewables and battery energy storage

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