A standard framework to analyze electricity market couplings and system operator coordination

Janssen, Tanguy; Rebours, Yann

doi:10.1109/eem.2012.6254724

Cited by 3 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, integrating wind energy into electric power systems tends to reduce the reliability of the grid [2]- [4] due to the intermittency of wind [5] where its availability may be low during peak power demands time [2]. It is the system operator's responsibility to make a balance between generation and consumption [6]. Demand-side Management (DSM) is one method for this purpose [7].…”

Section: Introductionmentioning

confidence: 99%

Aggregate Load Forecast with Payback Model of the Electric Water Heaters for a Direct Load Control Program

Shaad

Errouissi

Diduch

et al. 2014

2014 IEEE Electrical Power and Energy Conference

View full text Add to dashboard Cite

Domestic electric water heaters (DEWH) hold a large share of residential load in North America. The aggregated load profile of electric water heaters follows a similar pattern to the total household load profile, which means that changing the profile of DEWH load can significantly change the shape of the aggregated load profile. To change the load profile, the controller requires an estimation of future load profile and the payback effect of the control action on the forecasted load. This paper presents a load forecast module that uses a Kalman filtered neural network to forecast the aggregated controllable load combined with a statistical payback model to identify the impact of the control action on the load forecast. The proposed method was used by the University of New Brunswick as part of a pilot project named PowerShift Atlantic that aims to provide more than 11MW of ancillary services by controlling more than 1200 controllable loads. The experimental results on the real pilot project shows that the forecast method can be adapted with the dynamic behaviour of the customers. The payback model was also verified by applying various control signals on the pilot project.

show abstract