Towards the Interactive Effects of Demand Response Participation on Electricity Spot Market Price

Abstract The electricity market is threatened by supply scarcity, which may lead to very sharp price spikes in the spot market. On the other hand, demand-side’s activities could effectively mitigate the supply scarcity and absorb most of these shocks and therefore smooth out the price volatility. In this paper, the positive effects of employing demand response programs on the spot market price are investigated. A demand-price elasticity based model is used to simulate the customer reaction function in the presence of a real time pricing. The demand achieve by DR program is used to adjust the spot market price by using a price regression model. SAS software is used to run the multiple linear regression model and MATLAB is used to simulate the demand response model. The approach is applied on one week data in summer 2014 of Connecticut in New England ISO. It could be concluded from the results of this study that applying DR program smooths out most of the price spikes in the electricity spot market and considerably reduces the customers’ electricity cost.

[1]  Dilan Jayaweera,et al.  Fundamentals of power systems , 2016, CDC 2016.

[2]  Juan M. Morales,et al.  Real-Time Demand Response Model , 2010, IEEE Transactions on Smart Grid.

[3]  M. P. Moghaddam,et al.  Demand response modeling considering Interruptible/Curtailable loads and capacity market programs , 2010 .

[4]  N. Amjady Day-ahead price forecasting of electricity markets by a new fuzzy neural network , 2006, IEEE Transactions on Power Systems.

[5]  A. Faruqui,et al.  Household response to dynamic pricing of electricity: a survey of 15 experiments , 2010 .

[6]  Seyed Hossein Hosseinian,et al.  A Novel Approach to Utilize PLC to Detect Corroded and Eroded Segments of Power Transmission Lines , 2015, IEEE Transactions on Power Delivery.

[7]  C. Senabre,et al.  Development of a methodology for clustering electricity-price series to improve customer response initiatives , 2010 .

[8]  Payam Teimourzadeh Baboli,et al.  Present status and future trends in enabling demand response programs , 2011, 2011 IEEE Power and Energy Society General Meeting.

[9]  J. Contreras,et al.  ARIMA models to predict next-day electricity prices , 2002 .

[10]  Saeed Mohajeryami,et al.  A novel economic model for price-based demand response , 2016 .

[11]  C. Rodriguez,et al.  Energy price forecasting in the Ontario competitive power system market , 2004, IEEE Transactions on Power Systems.

[12]  N. Pindoriya,et al.  An Adaptive Wavelet Neural Network-Based Energy Price Forecasting in Electricity Markets , 2008, IEEE Transactions on Power Systems.

[13]  D C Washington,et al.  ELECTRICITY MARKETS Consumers Could Benefit from Demand Programs , but Challenges Remain a , 2004 .

[14]  Andrea Garulli,et al.  Models and Techniques for Electric Load Forecasting in the Presence of Demand Response , 2015, IEEE Transactions on Control Systems Technology.

[15]  Farshid Keynia,et al.  Day-ahead electricity price forecasting by modified relief algorithm and hybrid neural network , 2010 .

[16]  M. Shahidehpour,et al.  Restructured Electrical Power Systems: Operation: Trading, and Volatility , 2001 .

[17]  A. Faruqui,et al.  Quantifying Customer Response to Dynamic Pricing , 2005 .

[18]  J. Contreras,et al.  ARIMA Models to Predict Next-Day Electricity Prices , 2002, IEEE Power Engineering Review.

[19]  M. P. Moghaddam,et al.  Flexible demand response programs modeling in competitive electricity markets , 2011 .

[20]  Sanem Sergici,et al.  Arcturus: International Evidence on Dynamic Pricing , 2013 .

[21]  Parviz Famouri,et al.  Design, Modeling, and Simulation of On-Demand Communication Mechanisms for Cyber-Physical Energy Systems , 2014, IEEE Transactions on Industrial Informatics.

[22]  G. Gross,et al.  Short-term load forecasting , 1987, Proceedings of the IEEE.

[23]  Seyed Hossein Hosseinian,et al.  Distributed cooperative control system for smart microgrids , 2016 .

[24]  Mohammed H. Albadi,et al.  A summary of demand response in electricity markets , 2008 .

[25]  Wenxian Yang,et al.  A Statistical Demand-Price Model With Its Application in Optimal Real-Time Price , 2012, IEEE Transactions on Smart Grid.

[26]  Hanne Sæle,et al.  Demand Response From Household Customers: Experiences From a Pilot Study in Norway , 2011, IEEE Transactions on Smart Grid.

[27]  D. Kirschen,et al.  Factoring the elasticity of demand in electricity prices , 2000 .

[28]  V. C. Gungor,et al.  Smart Grid and Smart Homes: Key Players and Pilot Projects , 2012, IEEE Industrial Electronics Magazine.

[29]  M. Parsa Moghaddam,et al.  Modeling and prioritizing demand response programs in power markets , 2010 .

[30]  J. Torriti,et al.  Demand response experience in Europe: Policies, programmes and implementation , 2010 .