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Optimal Dispatch of Electrical Transmission Systems Considering Interdependencies with Natural Gas Systems

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Game Theory for Security and Risk Management

Abstract

This chapter presents a novel model to assess the interdependencies between electric power systems interconnected with natural gas systems. The impact from natural gas systems in the electric power system can be evaluated with the proposed model in normal operation and contingency situations. To reduce the impact of interdependencies, additional constraints to the optimal dispatch problem are formulated. The interdependency constraints can be integrated into the normal optimal power flow problem and security-constrained optimal power flow problem to improve the robustness of the electric power system. A co-simulation platform is built in MATLAB environment. We evaluate the proposed model using the IEEE 14-bus system and a corresponding natural gas transmission system. According to the simulation results, the reliability of the power system is improved when interdependency constraints are considered.

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References

  1. Mohammad Shahidehpour, Yong Fu, and Thomas Wiedman. Impact of natural gas infrastructure on electric power systems. Proceedings of the IEEE, 93(5):1042–1056, 2005.

    Article  Google Scholar 

  2. Alberto Martinez-Mares and Claudio R Fuerte-Esquivel. A unified gas and power flow analysis in natural gas and electricity coupled networks. IEEE Transactions on Power Systems, 27(4):2156–2166, 2012.

    Article  Google Scholar 

  3. Zhinong Wei, Sheng Chen, Guoqiang Sun, Dan Wang, Yonghui Sun, and Haixiang Zang. Probabilistic available transfer capability calculation considering static security constraints and uncertainties of electricity–gas integrated energy systems. Applied Energy, 167:305–316, 2016.

    Article  Google Scholar 

  4. Tao Li, Mircea Eremia, and Mohammad Shahidehpour. Interdependency of natural gas network and power system security. IEEE Transactions on Power Systems, 23(4):1817–1824, 2008.

    Article  Google Scholar 

  5. Moein Moeini-Aghtaie, Ali Abbaspour, Mahmud Fotuhi-Firuzabad, and Ehsan Hajipour. A decomposed solution to multiple-energy carriers optimal power flow. IEEE Transactions on Power Systems, 29(2):707–716, 2014.

    Article  Google Scholar 

  6. Michele Arnold, Rudy R Negenborn, Goran Andersson, and Bart De Schutter. Model-based predictive control applied to multi-carrier energy systems. In Power & Energy Society General Meeting, 2009. PES’09. IEEE, pages 1–8. IEEE, 2009.

    Google Scholar 

  7. Xianjun Zhang, George G Karady, and Samuel T Ariaratnam. Optimal allocation of chp-based distributed generation on urban energy distribution networks. IEEE Transactions on Sustainable Energy, 5(1):246–253, 2014.

    Article  Google Scholar 

  8. Nilufar Neyestani, Maziar Yazdani-Damavandi, Miadreza Shafie-Khah, Gianfranco Chicco, and João PS Catalão. Stochastic modeling of multienergy carriers dependencies in smart local networks with distributed energy resources. IEEE Transactions on Smart Grid, 6(4):1748–1762, 2015.

    Google Scholar 

  9. Xiaping Zhang, Mohammad Shahidehpour, Ahmed Alabdulwahab, and Abdullah Abusorrah. Hourly electricity demand response in the stochastic day-ahead scheduling of coordinated electricity and natural gas networks. IEEE Transactions on Power Systems, 31(1):592–601, 2016.

    Article  Google Scholar 

  10. Ahmed Alabdulwahab, Abdullah Abusorrah, Xiaping Zhang, and Mohammad Shahidehpour. Stochastic security-constrained scheduling of coordinated electricity and natural gas infrastructures. IEEE Systems Journal, 2015.

    Google Scholar 

  11. Cong Liu, Mohammad Shahidehpour, Yong Fu, and Zuyi Li. Security-constrained unit commitment with natural gas transmission constraints. IEEE Transactions on Power Systems, 24(3):1523–1536, 2009.

    Article  Google Scholar 

  12. Carlos M Correa-Posada and Pedro Sanchez-Martin. Security-constrained optimal power and natural-gas flow. IEEE Transactions on Power Systems, 29(4):1780–1787, 2014.

    Article  Google Scholar 

  13. E Shashi Menon. Gas pipeline hydraulics. CRC Press, 2005.

    Google Scholar 

  14. Stephen J Wright. Primal-dual interior-point methods. SIAM, 1997.

    Google Scholar 

  15. Hongye Wang, Carlos E Murillo-Sanchez, Ray D Zimmerman, and Robert J Thomas. On computational issues of market-based optimal power flow. IEEE Transactions on Power Systems, 22(3):1185–1193, 2007.

    Article  Google Scholar 

  16. Allen J Wood and Bruce F Wollenberg. Power generation, operation, and control. John Wiley & Sons, 2012.

    Google Scholar 

  17. Ray Daniel Zimmerman, Carlos Edmundo Murillo-Sánchez, and Robert John Thomas. Matpower: Steady-state operations, planning, and analysis tools for power systems research and education. IEEE Transactions on power systems, 26(1):12–19, 2011.

    Article  Google Scholar 

  18. Brian Stott and Eric Hobson. Power system security control calculations using linear programming, part i. IEEE Transactions on Power Apparatus and Systems, (5):1713–1720, 1978.

    Google Scholar 

  19. James Jamal Thomas and Santiago Grijalva. Flexible security-constrained optimal power flow. IEEE Transactions on Power Systems, 30(3):1195–1202, 2015.

    Article  Google Scholar 

  20. Wai Y Ng. Generalized generation distribution factors for power system security evaluations. IEEE Transactions on Power Apparatus and Systems, (3):1001–1005, 1981.

    Google Scholar 

  21. Teoman Guler, George Gross, and Minghai Liu. Generalized line outage distribution factors. IEEE Transactions on Power Systems, 22(2):879–881, 2007.

    Article  Google Scholar 

  22. Tianqi Hong, Ashhar Raza, and Francisco de León. Optimal power dispatch under load uncertainty using a stochastic approximation method. IEEE Transactions on Power Systems, 31(6):4495–4503, 2016.

    Article  Google Scholar 

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Correspondence to Tianqi Hong .

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Appendices

Appendix

The electrical consumption data after re-dispatch are shown in Table 9.5. The information on the buses of the artificial natural gas system is presented in Table 9.6. The constant pressure node in the natural gas system is denoted as “CP,” and the constant flow rate node is denoted as “CQ.” The regular nodes are denoted as “L.” All pipelines are assumed to have equal lengths of 80 km and equal inner diameters of 635 mm. The upper bounds of the pipeline are set to be 15 Mm3/day. The data of the sources in the natural gas system are provided in Table 9.7.

Table 9.5 Electrical consumption data after re-dispatch
Table 9.6 Artificial 14-bus natural gas system data sheet of buses
Table 9.7 Artificial 14-bus natural gas system data sheet of sources

List of Abbreviations and Symbols

Abbreviations

IDI

Interdependency impact

ENG system

Electric natural gas system

PCIDI

Post-contingency interdependency impact

ONGF

Optimal natural gas flow

PDIPA

Primal-dual interior point algorithm

OPF

Optimal power flow

SCOPF

Security-constrained optimal power flow

PTDF

Power transfer distribution factor

LODF

Line outage distribution factor

Symbols

FkI, FkD, Fkm

Flow rates of injection, demand of node k, and pipeline km in m3/day

pb, pk, pkw

Base pressure, pressure at node k, and well pressure at node k in kPa

r km

Compression ratio at node k of pipeline km

G

Specific gravity of the gas delivered by pipeline, unitless

R

Ideal gas constant equals to 8.314 J/K/mol

γ

Ratio of specific heats of gas

Dkm, Lkm

Pipe inside diameter in mm, length of pipe in km

Zk, Zkm

Compressibility factors of nodes k and pipeline km

ηkmp, ηkmc

Efficiencies of pipeline and compressor station of pipeline km

Tb, Tf, Tk

Base, average gas flow temperature; temperature at node k in K

NN, NC, NP

Number of nodes, number of compressors, and number of pipelines

N S

Number of total contingency scenarios in natural gas system

M NG

Operational cost of natural gas system

CS km

Compressor station at pipeline km

P km E

Electric power consumption of compressor at pipeline km in kW

PiG, QiG

Active and reactive powers of generator at bus i

PiD, QiD

Active and reactive power demands at bus i

Pi, Qi

Active and reactive power flows at bus i

Vi, Iij

Per unit voltage of bus i and per unit current of line ij

aiE, biE, ciE

Coefficients of the thermal generator at bus i

N B

Number of buses

M E

Operational cost of electrical system

Functions and Operators

sign(x)

Function to extract the sign of variable x

\(\underline{x},\overline{x}\)

Lower and upper limits of variable x

≤,  ≥

Component-wise operators

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Hong, T., de León, F., Zhu, Q. (2018). Optimal Dispatch of Electrical Transmission Systems Considering Interdependencies with Natural Gas Systems. In: Rass, S., Schauer, S. (eds) Game Theory for Security and Risk Management. Static & Dynamic Game Theory: Foundations & Applications. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-75268-6_9

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