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Risk-Based Purchasing Energy for Electricity Consumers by Retailer Using Information Gap Decision Theory Considering Demand Response Exchange

  • Ramin NourollahiEmail author
  • Sayyad Nojavan
  • Kazem Zare
Chapter
  • 20 Downloads

Abstract

Electricity retailer using demand response (DR) programs can reduce their cost in procuring consumers energy. In this chapter, several new demand response schemes are proposed to reduce retailer cost. These new schemes include pool-order DR, forward DR, and reward-base DR. Information gap decision theory (IGDT) technique is proposed to handle the pool market price uncertainty. Furthermore, optimal bidding strategy of electricity retailer is obtained using IGDT technique based on opportunity and robustness functions. Optimal bidding strategy provides stepwise power price in the power price uncertainty condition for submiting to day-ahead market in order to purchase power from pool market. The proposed model based on IGDT technique can be solved using standard Branch and Bound (SBB) solver under GAMS software.

Keywords

Forward, pool-order, and reward-base DR programs Information gap decision theory (IGDT) Optimal bidding strategy of electricity retailer 

Nomenclature

Parameters

Cb

Minimum expected cost of retailer

Co

Critical cost for opportunity function

Cr

Critical cost for robustness function

d(t)

Time period

\( {f}_{po}^{\mathrm{pen}}(t) \)

Penalty of not running pool-order DR in time period t

\( {P}_{f,b}^{\mathrm{DR},\operatorname{MAX}}(t) \)

Highest demand in block b of forward DR f in time period t

\( {P}_{f,b}^{\mathrm{MAX}}(t) \)

Highest demand in block b of forward contract in time period t

\( {\overline{P}}_j^{\mathrm{DR}}(t) \)

Demand in jth step of reward-base DR in time period t

\( {P}_{po}^{\mathrm{MAX}}(t) \)

Highest demand in pool-order DR in time period t

Preq(t)

Value of purchased power by retailer in period t

\( {\overline{R}}_j^{\mathrm{DR}}(t) \)

Highest value in jth step of reward-base DR in time period t

λpo(t)

Price of pool-order DR in period t

\( {\lambda}_{f,b}^{\mathrm{DR}}(t) \)

Price of block b of forward DR f option in time period t

\( {\lambda}_{f,b}^{\mathrm{F}}(t) \)

Price of the block b of forward contract f in time period t

\( {\tilde{\lambda}}^{\mathrm{p}}(t) \)

Forecasted pool market price

ω

Percentage increase in cost for retailer

ϒ

Percentage decrease in cost for retailer

Numbers

NBDR

Number of blocks in forward DR

NF

Number of forward contracts

NFB

Number of blocks in forward contracts

NFDR

Number of contract in forward DR

NJ

Number of steps in reward-base DR

Npo

Number of pool-order options

Variables

C(F)

Total cost of forward contracts

C(FDR)

Total cost of forward DR program

C(PO)

Total cost of pool-order options

EC(P)

Total cost of power procurement from pool market

EC(RDR)

Total cost of reward-base DR

PDR(t)

Purchased power from reward-base DR in time period t

Pp(t)

Purchased power from the pool market in time period t

Ppo(t)

Purchased power from pool-order in time period t

\( {P}_{f,b}^{\mathrm{DR}}(t) \)

Purchased power from block b of forward DR f in time period t

\( {P}_{f,b}^{\mathrm{F}}(t) \)

Purchased power from block b of forward contract f in time periodt

RDR(t)

Value of reward in time period t

\( {R}_j^{\mathrm{DR}}(t) \)

Value of reward of step j in time period t

vDR, j(t)

Binary variable that shows which step is executed in time period t

vpo(t)

Binary variable which is 1 if pool-order is run in time period t

λp(t)

Actual pool market price

Functions

C(p, λ)

Procurement cost function of retailer

\( \hat{\alpha}\left({C}_{\mathrm{r}}\right) \)

Robustness function

\( \hat{\beta}\left({C}_{\mathrm{o}}\right) \)

Opportunity function

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Faculty of Electrical and Computer EngineeringUniversity of TabrizTabrizIran
  2. 2.Department of Electrical EngineeringUniversity of BonabBonabIran

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