TY - JOUR
T1 - Impact of Load Profile on Dynamic Interactions between Energy Markets
T2 - A Case Study of Power Exchange and Demand Response Exchange
AU - Konda, Srikanth Reddy
AU - Al-Sumaiti, Ameena Saad
AU - Panwar, Lokesh Kumar
AU - Panigrahi, Bijaya Ketan
AU - Kumar, Rajesh
N1 - Funding Information:
Manuscript received October 26, 2018; revised January 30, 2019; accepted March 25, 2019. Date of publication April 11, 2019; date of current version November 5, 2019. This work was supported by Khalifa University, Abu Dhabi, UAE, under Award FSU-2018-25. Paper no. TII-18-2798. (Corresponding author: Srikanth Reddy Konda.) S. R. Konda is with Department of Electrical and Computer Engineering, Khalifa University, Abu Dhabi 127788, UAE (e-mail:, [email protected]).
Publisher Copyright:
© 2005-2012 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - Demand response exchange (DRX) presents a pool-based approach for optimal clearing/scheduling of demand response (DR) services through bid clearing. The same is intended to minimize the limitations of price-based and incentive-based mechanisms. However, unlike the price-based or incentive-based DR schemes, the DR sellers in DRX do not have a clear motivation to formulate the bid offers. Similarly, the DR buyers' bid formulation should also include optimal benefit analysis. This paper formulates and analyzes the bid formulation for DR sellers and buyers considering respective operation objectives. The DR seller bid formulation is derived considering load behavior through utilization index and availability index obtained from load profile of respective loads. On the other hand, DR buyer bid formulation is derived from power exchange operation attributes/cost of generation. Therefore, the DR clearing ultimately affects the operational cost of operation which, in turn, is reflected in DR buying bid and DR clearing finally. This paper develops an iterative approach in which the continuous interactions between ISO/power exchange would finally converge to a stable operation. The load profile-based strategic bid formulation is modeled using mathematical as well as fuzzy inference system (FIS). In addition, an adaptive FIS has been devised to improve the performance of DR scheduling. The simulation results illustrate the impact of customer behavior, intelligent decision-making, and penetration level on the performance and convergence of power markets (DRX and power exchange).
AB - Demand response exchange (DRX) presents a pool-based approach for optimal clearing/scheduling of demand response (DR) services through bid clearing. The same is intended to minimize the limitations of price-based and incentive-based mechanisms. However, unlike the price-based or incentive-based DR schemes, the DR sellers in DRX do not have a clear motivation to formulate the bid offers. Similarly, the DR buyers' bid formulation should also include optimal benefit analysis. This paper formulates and analyzes the bid formulation for DR sellers and buyers considering respective operation objectives. The DR seller bid formulation is derived considering load behavior through utilization index and availability index obtained from load profile of respective loads. On the other hand, DR buyer bid formulation is derived from power exchange operation attributes/cost of generation. Therefore, the DR clearing ultimately affects the operational cost of operation which, in turn, is reflected in DR buying bid and DR clearing finally. This paper develops an iterative approach in which the continuous interactions between ISO/power exchange would finally converge to a stable operation. The load profile-based strategic bid formulation is modeled using mathematical as well as fuzzy inference system (FIS). In addition, an adaptive FIS has been devised to improve the performance of DR scheduling. The simulation results illustrate the impact of customer behavior, intelligent decision-making, and penetration level on the performance and convergence of power markets (DRX and power exchange).
KW - Customer baseline load
KW - demand response
KW - demand response exchange
KW - energy markets
KW - independent system operator
KW - load profiling
UR - https://www.scopus.com/pages/publications/85077495539
U2 - 10.1109/TII.2019.2910349
DO - 10.1109/TII.2019.2910349
M3 - Article
AN - SCOPUS:85077495539
SN - 1551-3203
VL - 15
SP - 5855
EP - 5866
JO - IEEE Transactions on Industrial Informatics
JF - IEEE Transactions on Industrial Informatics
IS - 11
M1 - 8686190
ER -