Critical peak pricing demand response participant assessment

• US 10,181,165 B2
• Filed: 02/12/2016
• Issued: 01/15/2019
• Est. Priority Date: 02/12/2016
• Status: Active Grant

• Current Assignee: Fujitsu Limited
• Original Assignee: Fujitsu Limited
• Inventors: Chen, Wei-Peng, He, Dawei
• Primary Examiner(s): Miller, Alan S
• Application Number:
  US15/043,334
• Publication Number:
  US 20170236222A1
• Time in Patent Office: 1,068 Days
• Field of Search: 705 711- 742
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors
• CPC Class Codes: G06Q 50/06 Energy or water supply

Abstract

A method of critical peak pricing (CPP) demand response (DR) event implementation includes performing an initial CPP participant selection assessment. The method includes generating an initial CPP participant selection and an estimated CPP curtailment based on the initial CPP participant selection assessment. The method includes calculating a reduced day-ahead demand. The method includes evaluating the reduced day-ahead demand. The method includes submitting an energy bid to a market server. The method includes forecasting a revised real time price. The method includes performing a final CPP participation selection assessment. The method may include generating a final CPP participant selection to include the CPP participants having accumulated individual participant revenue effects up to the reduced day-ahead demand. The method includes communicating CPP event notifications to each of the CPP participants in the final CPP participant selection.

Claims

1. A method of critical peak pricing (CPP) demand response (DR) event implementation, the method comprising:

determining whether CPP event notifications are broadcast to CPP participants in a CPP DR system;

in response to the CPP event notifications being unicast, determining whether curtailment behavior of one or more of the CPP participants is a factor in load estimations during the CPP DR event;

in response to the curtailment behavior being a factor, determining whether DR assessments consider one or more energy market condition factors;

in response to the DR assessments considering the one or more energy market condition factors;

receiving energy usage data from a plurality of sites via smart meters configured to measure energy distributed to the plurality of sites by a utility;

performing an initial CPP participant selection assessment, the initial CPP participant selection assessment including calculating an individual participant revenue effect for the CPP participants;

setting participant revenue thresholds based on event participant limit; and

comparing the individual participant revenue effects and the participant revenue thresholds;

generating an initial CPP participant selection and an estimated CPP curtailment for an immediately subsequent day based on the initial CPP participant selection assessment;

based on the initial CPP participant selection, calculating a reduced day-ahead demand as a portion of the estimated CPP curtailment;

evaluating the reduced day-ahead demand to ensure that reductions in energy use by the CPP participants of the initial CPP participant selection do not frustrate efficiencies introduced through the estimated CPP curtailment;

submitting an energy bid to a market server, the energy bid including a day-ahead demand and a day-ahead price based on the reduced day-ahead demand;

forecasting a revised real time price for the immediately subsequent day based on day-ahead market results received from the market server;

performing a final CPP participation selection assessment, the final CPP participation selection assessment including re-calculation of the individual participant revenue effects for the CPP participants based on a forecasted revised real time price, sorting the individual participant revenue effects in decreasing order, calculating accumulated CPP curtailments from the sorted individual participant revenue effects, and comparing the accumulated CPP curtailments with the reduced day-ahead demand; and

generating a final CPP participant selection to include the CPP participants having accumulated individual participant revenue effects up to the reduced day-ahead demand; and

implementing the CPP DR event in the CPP DR system during a period in which the CPP is applied, the implementing the CPP DR event including communication of CPP event notifications to each of the selected participants to lower energy consumption by appliances of the CPP participants.

2. The method of claim 1, wherein:

the individual participant revenue effects are calculated for each of the CPP participants from a current day until a final day of a designated time period; and

the initial CPP participation assessment includes;

estimating a long-term price and a long-term load based on historical real-time price data and historical load data, the long-term price and the long-term load being estimated for a seasonal time period;

estimating a short-term price and short-term load for each of the CPP participants based on the historical load data, the historical real-time price data, recent price data, and recent load data;

training an empirical curtailment model for each of the CPP participants;

sorting the individual participant revenue effect in decreasing order for each of the CPP participants;

setting participant revenue thresholds for each of the CPP participants as a value of the individual participant revenue effect that occupies a position in the sorted individual participant revenue effect that corresponds to the event participation limit of the CPP participant;

comparing each of the individual participant revenue effect of each of the CPP participants to the participant revenue threshold of the CPP participant; and

in response to the individual participant revenue effect of the CPP participant being greater than the participant revenue threshold of the CPP participant including the CPP participant in a CPP participant selection.

3. The method of claim 2, wherein:

the individual participant revenue effect are re-calculated for each of the CPP participants from a current day until a final day of the designated time period based on the forecasted revised real time price; and

the final CPP participation assessment includes;

sorting the re-calculated individual participant revenue effect in decreasing order for each of the CPP participants; and

re-setting participant revenue thresholds for each of the CPP participants as the value of the individual participant revenue effect that occupies a position in the sorted individual participant revenue effect that corresponds to the event participation limit of the CPP participant.

4. The method of claim 2, wherein:

the empirical curtailment model is defined by a curtailment model expression;

LΔ

_idh=k·

L_idh, in which

LΔ

_idh represents a load curtailment of one of the CPP participants indicated by an indexing variable i at a day and an hour during the CPP DR event;

k represents a constant factor; and

L_idh represents a regular load of a CPP participant (i) at a day (d) and an hour (h) when the CPP DR event is called; and

the setting of the participant revenue thresholds includes;

determining whether the event participation limit is reached; and

in response to the event participation limit being reached, setting the participant revenue threshold to an infinite value.

5. The method of claim 1, wherein the individual participant revenue effect is defined by individual participant effect expressions:

6. The method of claim 1, wherein the evaluating the reduced day-ahead demand includes:

determine whether a real-time price at a day (d) and an hour (h) is less than a reduced day-ahead price at a day (d) and an hour (h);

in response to the real-time price being less than the reduced real-time price, setting the reduced day-ahead demand to a sum of products of decision variables and load curtailments of the CPP participants at a day (d) and an hour (h) when the CPP DR event is called; and

in response to the real-time price being greater than the reduced day-ahead price, setting the reduced day-ahead demand based on a reduced day-ahead demand inequality and a reduced DA demand expression, wherein;

the reduced day-ahead demand inequality includes;

7. The method of claim 1, further comprising:

in response to the CPP event notifications being broadcast, determining whether curtailment behavior of one or more of the CPP participants is a factor in load estimations during the CPP DR event;

in response to the curtailment behavior being a factor;

calculating curtailment revenues for each day from a current day until a final day of a designated time period based on historical data from a previous designated time period;

sorting the calculated curtailment revenues in descending order;

calculating a remaining quota value of an event participation limit;

setting a participation threshold as a value of the curtailment revenue that occupies a position in the sorted calculated curtailment revenues that corresponds to the remaining quota value;

determining whether a calculated curtailment revenue for a current day is greater than the participation threshold; and

in response to the calculated curtailment revenue being greater than the participation threshold, broadcasting CPP event notifications to the CPP participants.

8. The method of claim 7, wherein the curtailment revenues are calculated according to a curtailment revenue expression:

9. The method of claim 1, further comprising:

in response to the CPP event notifications being broadcast, determining whether curtailment behavior of one or more of the CPP participants is a factor in load estimations during the CPP DR event;

in response to the curtailment behavior not being a factor;

based on historical data from a previous designated time period, calculating price sums during a CPP DR event period for each day from a current day to an end of a designated time period;

sorting the calculated price sums in descending order;

calculating a remaining quota value of an event participation limit;

setting a participation threshold as the value of a price sum that occupies a position in the sorted price sums that corresponds to the remaining quota value;

determining whether a real-time price for the CPP DR event period is greater than the participation threshold; and

in response to the real-time price being greater than the participation threshold, broadcasting CPP event notifications to the CPP participants,

wherein the real-time price is based on broadcast/price-only expressions;

10. The method of claim 1, further comprising in response to DR assessments not considering any energy market condition factors:

calculating individual participant evaluation criteria for each of the CPP participants from a current day until a final day of a designated time period based on a forecasted real-time price;

sorting the individual participant evaluation criteria in decreasing order for each of the CPP participants;

setting participant revenue thresholds for each of the CPP participants as a value of the individual participant evaluation criteria that occupies a position in the sorted individual participant evaluation criteria that corresponds to the event participation limit of the CPP participant;

comparing each of the individual participant evaluation criteria of each of the CPP participants to the participant revenue threshold of the CPP participant; and

in response to the individual participant evaluation criteria of the CPP participant being greater than the participant revenue threshold of the CPP participant;

including the CPP participant in a CPP participant selection,

recording inclusion of the CPP participant in the CPP participant selection relative to an event participation limit, and

communicating a CPP event notification to each of the CPP participants in the CPP participation selection, the CPP event notification configured to prompt adjustment of loads of the CPP participants.

11. A non-transitory computer-readable medium having encoded therein programming code executable by a processor to perform or control performance of operations comprising:

determining whether critical peak pricing (CPP) event notifications are broadcast to CPP participants in a CPP DR system;

in response to the CPP event notifications being unicast, determining whether curtailment behavior of one or more of the CPP participants is a factor in load estimations during a CPP DR event;

in response to the curtailment behavior being a factor, determining whether DR assessments consider one or more energy market condition factors;

in response to the DR assessments considering the one or more energy market condition factors;

receiving energy usage data from a plurality of sites via smart meters configured to measure energy distributed to the plurality of sites by a utility;

performing an initial CPP participant selection assessment, the initial CPP participant selection assessment including calculating an individual participant revenue effect for the CPP participants;

setting participant revenue thresholds based on event participant limit; and

comparing the individual participant revenue effects and the participant revenue thresholds;

generating an initial CPP participant selection and an estimated CPP curtailment for an immediately subsequent day based on the initial CPP participant selection assessment;

based on the initial CPP participant selection, calculating a reduced day-ahead demand as a portion of the estimated CPP curtailment;

evaluating the reduced day-ahead demand to ensure that reductions in energy use by the CPP participants of the initial CPP participant selection do not frustrate efficiencies introduced through the estimated CPP curtailment;

submitting an energy bid to a market server, the energy bid including a day-ahead demand and a day-ahead price based on the reduced day-ahead demand;

forecasting a revised real time price for the immediately subsequent day based on day-ahead market results received from the market server;

performing a final CPP participation selection assessment, the final CPP participation selection assessment including re-calculation of the individual participant revenue effects for the CPP participants based on a forecasted revised real time price, sorting the individual participant revenue effects in decreasing order, calculating accumulated CPP curtailments from the sorted individual participant revenue effects, and comparing the accumulated CPP curtailments with the reduced day-ahead demand; and

generating a final CPP participant selection to include the CPP participants having accumulated individual participant revenue effects up to the reduced day-ahead demand; and

implementing the CPP DR event in the CPP DR system during a period in which the CPP is applied, the implementing the CPP DR event including communication of CPP event notifications to each of the selected participants to lower energy consumption by appliances of the CPP participants.

12. The non-transitory computer-readable medium of claim 11, wherein:

the individual participant revenue effects are calculated for each of the CPP participants from a current day until a final day of a designated time period; and

the initial CPP participation assessment includes;

estimating a long-term price and a long-term load based on historical real-time price data and historical load data, the long-term price and the long-term load being estimated for a seasonal time period;

estimating a short-term price and short-term load for each of the CPP participants based on the historical load data, the historical real-time price data, recent price data, and recent load data;

training an empirical curtailment model for each of the CPP participants;

sorting the individual participant revenue effects in decreasing order for each of the CPP participants;

setting participant revenue thresholds for each of the CPP participants as a value of the individual participant revenue effect that occupies a position in the sorted individual participant revenue effect that corresponds to the event participation limit of the CPP participant;

comparing each of the individual participant revenue effect of each of the CPP participants to the participant revenue threshold of the CPP participant; and

in response to the individual participant revenue effect of the CPP participant being greater than the participant revenue threshold of the CPP participant including the CPP participant in a CPP participant selection.

13. The non-transitory computer-readable medium of claim 12, wherein:

the individual participant revenue effects are re-calculated for each of the CPP participants from a current day until a final day of the designated time period based on the forecasted revised real time price; and

the final CPP participation assessment includes;

sorting the re-calculated individual participant revenue effects in decreasing order for each of the CPP participants; and

re-setting participant revenue thresholds for each of the CPP participants as the value of the individual participant revenue effects that occupies a position in the sorted individual participant revenue effects that corresponds to the event participation limit of the CPP participant.

14. The non-transitory computer-readable medium of claim 12, wherein:

the empirical curtailment model is defined by a curtailment model expression;

LΔ

_idh=k·

L_idh, in which

L<sub>Δ

idh</sub> represents a load curtailment of one of the CPP participants indicated by an indexing variable i at a day and an hour during the CPP DR event;

k represents a constant factor; and

L_idh represents a regular load of a CPP participant (i) at a day (d) and an hour (h) when the CPP DR event is called; and

the setting of the participant revenue thresholds includes;

determining whether the event participation limit is reached; and

in response to the event participation limit being reached, setting the participant revenue threshold to an infinite value.

15. The non-transitory computer-readable medium of claim 11, wherein the individual participant revenue effect is defined by individual participant effect expressions:

16. The non-transitory computer-readable medium of claim 11, wherein the evaluating the reduced day-ahead demand includes:

determine whether a real-time price at a day (d) and an hour (h) is less than a reduced day-ahead price at a day (d) and an hour (h);

in response to the real-time price being less than the reduced real-time price, setting the reduced day-ahead demand to a sum of products of decision variables and load curtailments of the CPP participants at a day (d) and an hour (h) when the CPP DR event is called; and

in response to the real-time price being greater than the reduced day-ahead price, setting the reduced day-ahead demand based on a reduced day-ahead demand inequality and a reduced DA demand expression, wherein;

the reduced day-ahead demand inequality includes;

17. The non-transitory computer-readable medium of claim 11, wherein the operations further comprise:

in response to the CPP event notifications being broadcast, determining whether curtailment behavior of one or more of the CPP participants is a factor in load estimations during the CPP DR event;

in response to the curtailment behavior being a factor;

calculating curtailment revenues for each day from a current day until a final day of a designated time period based on historical data from a previous designated time period;

sorting the calculated curtailment revenues in descending order;

calculating a remaining quota value of an event participation limit;

setting a participation threshold as a value of the curtailment revenue that occupies a position in the sorted calculated curtailment revenues that corresponds to the remaining quota value;

determining whether a calculated curtailment revenue for a current day is greater than the participation threshold; and

in response to the calculated curtailment revenue being greater than the participation threshold, broadcasting CPP event notifications to the CPP participants.

18. The non-transitory computer-readable medium of claim 17, wherein the curtailment revenues are calculated according to a curtailment revenue expression:

19. The non-transitory computer-readable medium of claim 11, wherein the operations further comprise:

in response to the CPP event notifications being broadcast, determining whether curtailment behavior of one or more of the CPP participants is a factor in load estimations during the CPP DR event;

in response to the curtailment behavior not being a factor;

based on historical data from a previous designated time period, calculating price sums during a CPP DR event period for each day from a current day to an end of a new designated time period;

sorting the calculated price sums in descending order;

calculating a remaining quota value of an event participation limit;

setting a participation threshold as the value of a price sum that occupies a position in the sorted price sums that corresponds to the remaining quota value;

determining whether a real-time price for the CPP DR event period is greater than the participation threshold; and

in response to the real-time price being greater than the participation threshold, broadcasting CPP event notifications to the CPP participants,

wherein the real-time price is based on broadcast/price-only expressions;

20. The non-transitory computer-readable medium of claim 11, wherein the operations further comprise in response to DR assessments not considering any energy market condition factors:

calculating individual participant evaluation criteria for each of the CPP participants from a current day until a final day of a designated time period based on a forecasted real-time price;

sorting the individual participant evaluation criteria in decreasing order for each of the CPP participants;

setting participant revenue thresholds for each of the CPP participants as a value of the individual participant evaluation criteria that occupies a position in the sorted individual participant evaluation criteria that corresponds to the event participation limit of the CPP participant;

comparing each of the individual participant evaluation criteria of each of the CPP participants to the participant revenue threshold of the CPP participant; and

in response to the individual participant evaluation criteria of the CPP participant being greater than the participant revenue threshold of the CPP participant;

including the CPP participant in a CPP participant selection,

recording inclusion of the CPP participant in the CPP participant selection relative to an event participation limit, and

communicating a CPP event notification to each of the CPP participants in the CPP participation selection, the CPP event notification configured to prompt adjustment of loads of the CPP participants.

21. A critical peak pricing (CPP) demand response (DR) system comprising:

a utility that is associated with a utility server;

a first site that receives energy distributed by the utility, the first site including a first appliance that consumes energy or controls operation of a first device that consumes energy distributed by the utility;

a second site that receives energy distributed by the utility, the second site including a second appliance that consumes energy or controls operation of a second device that consumes energy distributed by the utility;

a first smart meter connected to the first site that is configured to communicate energy usage data to the utility server;

a second smart meter connected to the second site that is configured to communicate energy usage data to the utility server; and

an energy market server communicatively coupled to the utility server and one or more energy sources via a network,

wherein the utility server includes one or more processors and non-transitory computer-readable medium having encoded therein programming code executable by the one or more processors to perform or control performance of operations comprising;

performing an initial CPP participant selection assessment of the CPP DR system, the initial CPP participant selection assessment including calculating an individual participant revenue effect for each of the first site and the second site based at least partially on the energy usage data received from the first and second smart meters;

setting participant revenue thresholds for a CPP DR event based on event participant limit; and

comparing the individual participant revenue effects for the first site and the second site to the participant revenue thresholds;

generating an initial CPP participant selection that includes one or both of the first site and the second site;

further generating an estimated CPP curtailment for an immediately subsequent day based on the initial CPP participant selection assessment;

based on the initial CPP participant selection, calculating a reduced day-ahead demand as a portion of the estimated CPP curtailment;

evaluating the reduced day-ahead demand to ensure that reductions in energy use by the CPP participants of the initial CPP participant selection do not frustrate efficiencies introduced through the estimated CPP curtailment;

submitting an energy bid to the market server, the energy bid including a day-ahead demand and a day-ahead price based on the reduced day-ahead demand;

receiving day-ahead market results based on the energy bid sent by the utility server and one or more additional energy bids communicated by one or more energy sources;

forecasting a revised real time price for the immediately subsequent day based on day-ahead market results received from the market server;

performing a final CPP participation selection assessment of the CPP DR system, the final CPP participation selection assessment including re-calculation of the individual participant revenue effects for each of the first site and the second site based on the forecasted revised real time price, sorting the individual participant revenue effects in decreasing order, calculating accumulated CPP curtailments from the sorted individual participant revenue effects, and comparing the accumulated CPP curtailments with the reduced day-ahead demand;

determining that the first site has a first accumulated individual participant revenue effect that is included in the reduced day-ahead demand and that the second site has a second accumulated individual participant revenue effect that exceeds the reduced day-ahead demand;

generating a final CPP participant selection to include the first site and exclude the second site; and

implementing a CPP DR event in the CPP DR system during a period in which the CPP is applied, the implementing the CPP DR event including communication of a first CPP event notification to the first site to lower energy consumption by the first appliance or the first device.