Abstract
The increasing share of variable renewable energy sources and the improving requirements on system security and reliability are calling for important changes in the LSIES. The synergies between energy supply networks are of great importance to satisfy the development of LSIES. Hence, this chapter presents the study of the coordinated scheduling strategy (CSS), in which, the models of the electricity network and gas network are developed in detail, and the operation constraints of the networks are fully considered. The purpose of the CSS is to optimize the conflicting benefits of the electricity network and gas network for daily operation of the LSIES, while satisfying the operation constraints. In the CSS, a multi-objective optimization algorithm is applied to obtain a Pareto-optimal solution set, and a multiple attribute decision analysis (MADA) using interval evidential reasoning (IER) is developed to determine a final optimal daily operation solution for the LSIES.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Amir R, Grilo I, Jin J (1999) Demand-induced endogenous price leadership. Int Game Theory Rev 1(03n04):219–240
An S, Li Q, Gedra TW (2003) Natural gas and electricity optimal power flow. In: Transmission and distribution conference and exposition, 2003 IEEE PES, vol 1. IEEE, pp 138–143
Auger A, Hansen N (2012) Tutorial CMA-ES: evolution strategies and covariance matrix adaptation. In: GECCO (Companion), pp 827–848
Bai L, Li F, Cui H, Jiang T, Sun H, Zhu J (2015) Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty. Appl Energy 1(1):1–10
Balcombe P, Rigby D, Azapagic A (2015) Environmental impacts of microgeneration: integrating solar PV, stirling engine CHP and battery storage. Appl Energy 139:245–259
Chaudry M, Jenkins N, Qadrdan M, Wu J (2014) Combined gas and electricity network expansion planning. Appl Energy 113:1171–1187
De Wolf D, Smeers Y (2000) The gas transmission problem solved by an extension of the simplex algorithm. Manag Sci 46(11):1454–1465
Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197
Dommel HW, Tinney WF (1968) Optimal power flow solutions. IEEE Trans Power Appar Syst 10:1866–1876
EIA-US (2011) Annual energy review. Energy information administration, US department of energy, Washington, DC. http://www.eia.doe.gov/emeu/aer
U.S. Energy Information Administration, Monthly energy review. https://www.eia.gov/totalenergy/data/monthly/pdf/mer.pdf
Gebremedhin A (2012) Introducing district heating in a Norwegian town-potential for reduced local and global emissions. Appl Energy 95:300–304
Gil M, Dueñas P, Reneses J (2016) Electricity and natural gas interdependency: comparison of two methodologies for coupling large market models within the European regulatory framework. IEEE Trans Power Syst 31(1):361–369
He S, Wu QH, Saunders J (2009) Group search optimizer: an optimization algorithm inspired by animal searching behavior. IEEE Trans Evol Comput 13(5):973–990
Hu Y, Bie ZH, Ding T, Lin YL (2016) An NSGA-II based multi-objective optimization for combined gas and electricity network expansion planning. Appl Energy 167:280–293
Jing ZX, Jiang XS, Wu QH, Tang WH, Hua B (2014) Modelling and optimal operation of a small-scale integrated energy based district heating and cooling system. Energy 73:399–415
Li YZ, Wu QH, Li MS, Zhan JP (2014) Mean-variance model for power system economic dispatch with wind power integrated. Energy 72:510–520
Li YZ, Wu QH, Jiang L, Yang JB, Xu DL (2016) Optimal power system dispatch with wind power integrated using nonlinear interval optimization and evidential reasoning approach. IEEE Trans Power Syst 31(3):2246–2254
Liu C, Shahidehpour M, Fu Y, Li Z (2009) Security-constrained unit commitment with natural gas transmission constraints. IEEE Trans Power Syst 24(3):1523–1536
Liu X, Wu J, Jenkins N, Bagdanavicius A (2016) Combined analysis of electricity and heat networks. Appl Energy 162:1238–1250
Martínez-Mares A, Fuerte-Esquivel CR (2012) A unified gas and power flow analysis in natural gas and electricity coupled networks. IEEE Trans Power Syst 27(4):2156–2166
Milgrom P, Shannon C (1994) Monotone comparative statics. Econometrica: Journal of the Econometric Society, pp 157–180
Mokhatab S, Poe WA (2012) Handbook of natural gas transmission and processing. Gulf Professional Publishing
Niknam T, Khodaei A, Fallahi F (2009) A new decomposition approach for the thermal unit commitment problem. Appl Energy 86(9):1667–1674
Niknam T, Azizipanah-Abarghooee R, Aghaei J (2013) A new modified teaching-learning algorithm for reserve constrained dynamic economic dispatch. IEEE Trans Power Syst 28(2):749–763
Overbye TJ, Cheng X, Sun Y (2004) A comparison of the AC and DC power flow models for LMP calculations. In: Proceedings of the 37th annual Hawaii international conference on system sciences, p 9
Partovi F, Nikzad M, Mozafari B, Ranjbar AM (2011) A stochastic security approach to energy and spinning reserve scheduling considering demand response program. Energy 36(5):3130–3137
Qadrdan M, Wu J, Jenkins N, Ekanayake J (2014) Operating strategies for a GB integrated gas and electricity network considering the uncertainty in wind power forecasts. IEEE Trans Sustain Energy 5(1):128–138
Qiao Z, Guo Q, Sun H, Pan Z, Liu Y, Xiong W (2016) An interval gas flow analysis in natural gas and electricity coupled networks considering the uncertainty of wind power. Appl Energy (in press)
Qiu J, Dong ZY, Zhao JH et al (2015) Multi-stage flexible expansion co-planning under uncertainties in a combined electricity and gas market. IEEE Trans Power Syst 30(4):2119–2129
Salimi M, Ghasemi H, Adelpour M, Vaez-ZAdeh S (2015) Optimal planning of energy hubs in interconnected energy systems: a case study for natural gas and electricity. IET Gener Transm Distrib 9(8):695–707
Schroeder JR, Donald W, et al (2010) A tutorial on pipe flow equations. In: PSIG annual meeting, Pipeline simulation interest group, p 1
Street A, Barroso LA, Chabar R, Mendes AT, Pereira MV (2008) Pricing flexible natural gas supply contracts under uncertainty in hydrothermal markets. IEEE Trans Power Syst 23(3):1009–1017
Strogatz SH (2014) Nonlinear dynamics and chaos: with applications to physics, biology, chemistry, and engineering. Westview Press
Talatahari S, Azar BF, Sheikholeslami R, Gandomi A (2012) Imperialist competitive algorithm combined with chaos for global optimization. Commun Nonlinear Sci Numer Simul 17:1312–1319
Tan ZF, Zhang HJ, Shi QS, Song YH, Ju LW (2014) Multi-objective operation optimization and evaluation of large-scale NG distributed energy system driven by gas-steam combined cycle in China. Energy Build 76:572–587
Tang WH, Spurgeon K, Wu QH, Richardson ZJ (2004) An evidential reasoning approach to transformer condition assessments. IEEE Trans Power Deliv 19(4):1696–1703
Thapar V, Agnihotri G, Sethi VK (2011) Critical analysis of methods for mathematical modelling of wind turbines. Renew Energy 36:3166–3177
Tichler R, Lehner M, Steinmüller H, Koppe M (2014) Power-to-gas: technology and business models. In: Briefs in Energy. Springer
Ting T, Rao M, Loo C (2006) A novel approach for unit commitment problem via an effective hybrid particle swarm optimization. IEEE Trans Power Syst 21(1):411–418
Topkis DM (1978) Minimizing a submodular function on a lattice. Oper Res 26(2):305–321
Topkis DM (1979) Equilibrium points in nonzero-sum n-person submodular games. SIAM J Control Optim 17(6):773–787
Tushar W, Zhang JA, Smith DB, Poor HV, Thiébaux S (2014) Prioritizing consumers in smart grid: a game theoretic approach. IEEE Trans Smart Grid 5(3):1429–1438
Tushar W, Yuen C, Smith DB, Poor HV (2015) Price discrimination for energy trading in smart grid: a game theoretic approach 99:1–12
Ugranli F, Karatepe E (2016) Transmission expansion planning for wind turbine integrated power systems considering contingency. IEEE Trans Power Syst 31(2):1476–1485
Üster H, Dilaveroğlu S (2014) Optimization for design and operation of natural gas transmission networks. Appl Energy 133:56–69
Varadarajan M, Swarup KS (2008) Solving multi-objective optimal power flow using differential evolution. IET Gener Transm Distrib 2(5):720–730
Venkatesh P, Gnanadass R, Padhy NP (2003) Comparison and application of evolutionary programming techniques to combined economic emission dispatch with line flow constraints. IEEE Trans Power Syst 18(2):688–697
Viana EM, de Oliveira EJ, Martins N, Pereira JLR, de Oliveira LW (2013) An optimal power flow function to aid restoration studies of long transmission segments. IEEE Trans Power Syst 28(1):121–129
Viswanathan GM, Buldyrev SV, Havlin S, Luz MGED, Raposo EP, Stanley HE (1999) Optimizing the success of random searches. Nature 401(6756):911–914
Wang JL, Wu JY, Zheng CY (2014) Simulation and evaluation of a CCHP system with exhaust gas deep-recovery and thermoelectric generator. Energy Convers Manag 86:992–1000
Wang JX, Zhong HW et al (2017) Review and prospect of integrated demand response in the multi-energy system. Appl Energy 202:772–782
Wang LX, Jing ZX, Zheng JH, Wu QH, Wei F (2018a) Decentralized optimization of coordinated electrical and thermal generations in hierarchical integrated energy systems considering competitive individuals. Energy 158:607–622
Wang K, Qi XX, Liu HD, Song JK (2018b) Deep belief network based k-means cluster approach for short-term wind power forecasting. Energy 165:840–852
Wang LF, Singh CN (2008) Balancing risk and cost in fuzzy economic dispatch including wind power penetration based on particle swarm optimization. Electr Power Syst Res 78(8):1361–1368
Wang MG, Tian LX, Du RJ (2016) Research on the interaction patterns among the global crude oil import dependency countries: a complex network approach. Appl Energy 180:779–791
Wang Y, Xia Q, Kang CQ (2011) Unit commitment with volatile node injections by using interval optimization. IEEE Trans Power Syst 26:1705–1713
Wang H, Yao X (2016) Objective reduction based on nonlinear correlation information entropy. Soft Comput 20(6):2393–2407
Wang H, Yao, X (2015) Objective reduction based on nonlinear correlation information entropy. Soft Comput: 1–15
Wang H, Yin W, Abdollahi E, Lahdelma R, Jiao W (2015) Modelling and optimization of CHP based district heating system with renewable energy production and energy storage. Appl Energy 159:401–421
Wei F, Jing ZX, Wu PZ, Wu QH (2017) A stackelberg game approach for multiple energies trading in integrated energy systems. Appl Energy 200:315–329
Wei F, Wu Q, Jing Z, Chen J, Zhou X (2016) Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach. Energy 111:933–946
Wood AJ, Wollenberg BF (2012) Power generation, operation, and control. Wiley
Wu QH, Liao HL (2013) Function optimisation by learning automata. Inf Sci 220:379–398
Wu QH, Lu Z, Li MS, Ji TY (2008) Optimal placement of facts devices by a group search optimizer with multiple producer. In: IEEE Congress on Evolutionary Computation, 2008. CEC 2008 (IEEE World Congress on Computational Intelligence). IEEE, pp 1033–1039
Wu T, Yang Q, Bao ZJ, Yan WJ (2013) Coordinated energy dispatching in microgrid with wind power generation and plug-in electric vehicles. IEEE Trans Smart Grid 4(3):1453–1463
Wu QH, Zheng JH, Jing ZX (2015) Coordinated scheduling of energy resources for distributed DHCs in an integrated energy grid. CSEE J Power Energy Syst 1(1):95–103
Wu L, Shahidehpour M, Li ZY (2012) Comparison of scenario-based and interval optimization approaches to stochastic SCUC. IEEE Trans Power Syst 27:913–921
Xiong HG, Cheng HZ, Li HY (2008) Optimal reactive power flow incorporating static voltage stability based on multi-objective adaptive immune algorithm. Energy Convers Manag 49(5):1175–1181
Xu DH, Qu M (2013) Energy, environmental, and economic evaluation of a CCHP system for a data center based on operational data. Energy Build 67:176–186
Xu JZ, Sui J, Li BY, Yang ML (2010) Research, development and the prospect of combined cooling, heating, and power systems. Energy 35(11):4361–4367
Xu X, Jia HJ, Chiang HD, Yu DC, Wang D (2015) Dynamic modeling and interaction of hybrid natural gas and electricity supply system in microgrid. IEEE Trans Power Syst 30(3):1212–1221
Yang XS (2010) Firefly algorithm, levy flights and global optimization. In: Research and development in intelligent systems XXVI, pp 209–218. Springer
Yang JB, Xu DL (2002) On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty. IEEE Trans Syst Man Cybern Part A Syst Hum 32(3):289–304
Yang L, Jian J, Zhu Y, Dong Z (2015) Tight relaxation method for unit commitment problem using reformulation and lift-and-project. IEEE Trans Power Syst 30:13–23
Yao W, Wen JY, Cheng SJ, Jiang L (2012) Development of a matlab/simulink based power system simulation toolbox. Power Syst Technol 36(6):95–101
Yuan ZX, Jing ZX, Hu RX, Wu QH (2015) Operation optimization of CCHP-type microgrid considering units’ part-load characteristics. In: Smart Grid Technologies—Asia (ISGT ASIA), 2015 IEEE Innovative, pp 1–7
Zeng Q, Zhang BH, Fang JK, Chen Z (2017) A bi-level programming for multistage co-expansion planning of the integrated gas and electricity system. Appl Energy 200:192–203
Zhai XQ, Wang RZ, Dai YJ, Wu JY, Xu YX, Ma Q (2007) Solar integrated energy system for a green building. Energy Build 39(8):985–993
Zhan ZH, Zhang J, Li Y, Chung HH (2009) Adaptive particle swarm optimization. IEEE Trans Syst Man Cybern Part B Cybern 39(6):1362–1381
Zhang X, Shahidehpour M, Alabdulwahab AS, Abusorrah A (2015) Security-constrained co-optimization planning of electricity and natural gas transportation infrastructures. IEEE Trans Power Syst 30(6):2984–2993
Zhang X, Shahidehpour M, Alabdulwahab A, Abusorrah A (2016) Hourly electricity demand response in the stochastic day-ahead scheduling of coordinated electricity and natural gas networks. IEEE Trans Power Syst 31(1):592–601
Zheng JH, Chen JJ, Wu QH, Jing ZX (2015) Multi-objective optimization and decision making for power dispatch of a large-scale integrated energy system with distributed DHCs embedded. Appl Energy 154:369–379
Zheng JH, Wu QH, Jing ZX (2017) Coordinated scheduling strategy to optimize conflicting benefits for daily operation of integrated electricity and gas networks. Appl Energy 192:370–381
Zhou Z, Liu P, Li Z, Pistikopoulos EN, Georgiadis MC (2013) Impacts of equipment off-design characteristics on the optimal design and operation of combined cooling, heating and power systems. Comput Chem Eng 48:40–47
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Wu, Qh., Zheng, J., Jing, Z., Zhou, X. (2019). Optimal Operation of Large-Scale Integrated Energy Systems . In: Large-Scale Integrated Energy Systems. Energy Systems in Electrical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-6943-8_6
Download citation
DOI: https://doi.org/10.1007/978-981-13-6943-8_6
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-6942-1
Online ISBN: 978-981-13-6943-8
eBook Packages: EnergyEnergy (R0)