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Consideration of a Combined Cycle Gas Turbine’s Operating Modes in Pricing Mechanisms: A Korean Electricity Market Study

  • Tae Hyun Kim
  • Hansol Shin
  • Wook KimEmail author
  • Kangwook Cho
  • Sungwoo Lee
Original Article
  • 6 Downloads

Abstract

This study proposes a modeling technique for applying combined cycle gas turbines (CCGTs) to the unit commitment problem. The proposed method does not specify the turbine operation order in advance, and uses a simple and basic formula structured as mixed integer linear programming (MILP). In addition, we propose a system marginal price (SMP) calculation considering combination modeling of CCGTs, and we analyze market price change and its effect. After applying the proposed method to the unit commitment problem and calculating the market price from January 2017, although average market price and volatility increased, there was no rapid change, such as inversion of the dispatching rank of fuel sources or excessive fuel costs. And the profitability of the CCGTs participating in the day-ahead energy market improve.

Keywords

Unit commitment Optimal dispatch Market clearing Day-ahead market SMP CCGT modeling methodology 

List of Symbols

Abbreviations and acronyms

CCGT

Combined cycle gas turbine

CFBM

Configuration-based model

CPBM

Component-based model

GT

Gas turbine

ST

Steam turbine

KRW

Korean won

KPX

Korea power exchange (the independent system operator in South Korea)

Sets and Indices

\({\mathcal{G}}\)

Set of generators

\({\mathcal{G}}_{ccgt}\)\(\subset {\mathcal{G}}\)

Set of CCGT generators

\({ \mathcal{K}}\)

Set of buses

\({\mathcal{T}}\)

Set of hourly periods

\({\mathcal{L}}\)

Set of output blocks

\({\mathcal{Y}}_{g}\)

Set of configurations within each CCGT generator \(g\)

\({\mathcal{X}}_{g}\)

Set of individual turbines within each CCGT generator \(g\)

\({\mathcal{X}}_{g}^{GT}\)\(\subset {\mathcal{X}}_{g}\)

Set of GTs within each CCGT generator \(g\)

\({\mathcal{X}}_{g}^{ST}\)\(\subset {\mathcal{X}}_{g}\)

Set of STs within each CCGT generator \(g\)

\({\mathcal{F}}{\mathcal{S}}_{g}^{yy'}\)

Set of feasible state transitions within CCGT generator \(g\), where \(y\) and \(y^{\prime}\) represent from and to configurations

\({\mathcal{I}}{\mathcal{F}}{\mathcal{S}}_{g}^{{yy^{\prime}}}\)

Set of infeasible state transitions within CCGT generator \(g\), where \(y\) and \(y^{\prime}\) represent from and to configurations

\(g \in {\mathcal{G}}\)

Index for generators

\(i,j \in {\mathcal{K}}\)

Indices for buses

\(t,\tau \in {\mathcal{T}}\)

Indices for hourly time steps

\(l\in L\)

Index for blocks

\(y \in {\mathcal{Y}}_{g}\)

Index for configurations within each CCGT generator \(g\)

\({\mathcal{X}}\)\(\in {\mathcal{X}}_{g}\)

Index for individual turbines within each CCGT generator \(g\)

Parameters

\(C_{g}^{SU}\)

Unit start-up cost of generator \(g\)

\(F_{g}^{(l)}\)

Slope of block \(l\) of generator \(g\)

\(\text{P}_{g}^{{\rm min} }\), \(\text{P}_{g}^{{\rm max} }\)

Minimum and maximum output level of generator \(g\)

\(\text{RD}_{g}\), \(\text{RU}_{g}\)

Ramp-down and -up rate of generator \(g\)

\(\text{UT}_{g}\), \(\text{DT}_{g}\)

Minimum up- and down-time of generator \(g\)

\(X_{ij}\)

Reactance of transmission line between bus \(i\) and \(j\)

\(D_{it}\)

Active power demand of bus \(i\) at hour \(t\)

\(a_{g}\), \(b_{g}\), \(c_{g}\)

Quadratic, linear, and no-load price coefficients of generator \(g\)

Continuous Variables

\(p_{gt}\)

Power output of generator \(g\) at hour \(t\)

\(\delta_{gt}^{(l)}\)

Piecewise power output in block \(l\) of generator \(g\) at hour \(t\)

\(suc_{gt}\)

Start-up cost of generator \(g\) at hour \(t\)

\(\theta_{it}\)

Voltage angle of bus \(i\) at hour \(t\)

Binary variables

\(i_{gt}\)

Binary variable for operational status of generator \(g\) at hour \(t\) (1: Operational, 0: Otherwise)

\(v_{gt}\)

Binary variable for start-up status of generator \(g\) at hour \(t\) (1: Start-up, 0: Otherwise)

\(w_{gt}\)

Binary variable for shutdown status of generator \(g\) at hour \(t\) (1: Under shutdown, 0: Otherwise)

Notes

Funding

This work was supported by BK21PLUS, Creative Human Resource Development Program for IT Convergence, and also was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2019R1I1A3A01059931).

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Copyright information

© The Korean Institute of Electrical Engineers 2019

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringPusan National UniversityBusanKorea
  2. 2.Korea Power ExchangeNajuKorea

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