TY - JOUR
T1 - Demand Response and Ancillary Service Management Using Fractional-Order Integral Indicator and Dynamic Game Model for an Aggregator Program in Smart Grids
AU - Chang, Long Yi
AU - Chung, Yi Nung
AU - Chen, Shi Jaw
AU - Kuo, Chao Lin
AU - Lin, Chia Hung
N1 - Funding Information:
This work is supported in part by the National Chin-Yi University of Technology, Taiwan, under contract number: NCUT 15-T-CE-018, duration: September 1 2015 ∼ July 31 2016, and is supported in part by the Ministry of Science and Technology (MOST), Taiwan, under contract number: MOST 104-2221-E-244-010, duration: August 1 2015 ∼ October 31 2016.
PY - 2016/12/1
Y1 - 2016/12/1
N2 - To avoid penalties on over-contract demand, electricity customers can adopt a demand response strategy to shift or reduce demands from main grid during peak periods or partial peak periods. The direct or indirect load control is a common strategy used to change operational conditions with or without incentive / contractual strategies. The time-of-use and real-time pricing in addition to incentive services can encourage customers to change their preferences, further reducing demands during contractual periods. Therefore, ancillary services can manage and dispatch ancillary power, such as renewable energy, stored energy, and onsite generation, to reduce expensive power generation from main grid and to meet the customers’ extra demands in smart grids. The fractional-order integral operation is used to calculate the area under the curve for evaluating power consumption at a scheduled timing interval of 15min / 1hour and identify demand levels. The dynamic game model is employed to dispatch the available distributed generations to meet the customers’ extra demands. For an aggregator program, results will show that the proposed method can reduce the demand from the main grid and increase system flexibility to activate the active-duty distributed generations. Benefits for billing charges may arise.
AB - To avoid penalties on over-contract demand, electricity customers can adopt a demand response strategy to shift or reduce demands from main grid during peak periods or partial peak periods. The direct or indirect load control is a common strategy used to change operational conditions with or without incentive / contractual strategies. The time-of-use and real-time pricing in addition to incentive services can encourage customers to change their preferences, further reducing demands during contractual periods. Therefore, ancillary services can manage and dispatch ancillary power, such as renewable energy, stored energy, and onsite generation, to reduce expensive power generation from main grid and to meet the customers’ extra demands in smart grids. The fractional-order integral operation is used to calculate the area under the curve for evaluating power consumption at a scheduled timing interval of 15min / 1hour and identify demand levels. The dynamic game model is employed to dispatch the available distributed generations to meet the customers’ extra demands. For an aggregator program, results will show that the proposed method can reduce the demand from the main grid and increase system flexibility to activate the active-duty distributed generations. Benefits for billing charges may arise.
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U2 - 10.1007/s40866-016-0015-0
DO - 10.1007/s40866-016-0015-0
M3 - Article
AN - SCOPUS:85070074895
VL - 1
JO - Technology and Economics of Smart Grids and Sustainable Energy
JF - Technology and Economics of Smart Grids and Sustainable Energy
SN - 2199-4706
IS - 1
M1 - 16
ER -