Critical peak pricing demand response participant assessment

Patent metadata

Field	Value
Publication number	US-10181165-B2
Application number	US-201615043334-A
Country	US
Kind code	B2
Filing date	Feb 12, 2016
Priority date	Feb 12, 2016
Publication date	Jan 15, 2019
Grant date	Jan 15, 2019

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.

First claim

What is claimed is:

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:

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Assignees

• Fujitsu Ltd

Inventors

• Chen Wei-Peng
• He Dawei

Classifications

• G06Q30/0206

  Price or cost determination based on market factors · CPC title

• G06Q50/06 Primary

  Energy or water supply · CPC title