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Abstract: We propose a new robust optimization approach to evaluate the impact of an intermittent renewable energy source on transmission expansion planning (TEP). The objective function of TEP is composed of the investment cost of the transmission line and the operating cost of conventional generators. A method to select suitable scenarios representing the intermittent renewable energy generation and loads is proposed to obtain robust expansion planning for all possible scenarios. A meta-heuristic algorithm called adaptive tabu search (ATS) is employed in the proposed TEP. ATS iterates between the main problem, which minimizes the investment and operating costs, and the subproblem, which minimizes the cost of power generation from conventional generators and curtailments of renewable energy generation and loads. The subproblem is solved by nonlinear programming (NLP) based on an interior point method. Moreover, the impact of an intermittent renewable energy source on TEP was evaluated by comparing expansion planning with and without consideration of a renewable energy source. The IEEE Reliability Test System 79 (RTS 79) was used for testing the proposed method and evaluating the impact of an intermittent renewable energy source on TEP. The results show that the proposed robust optimization approach provides a more robust solution than other methods and that the impact of an intermittent renewable energy source on TEP should be considered.

This paper proposes a new optimization approach to evaluating the impact of intermittent renewable energy source on transmission expansion planning (TEP). The results show that the proposed optimization approach can provide a solution which is more robust that the other works and that the impact of intermittent renewable energy source on TEP needs to be appropriately considered.

一种评估间歇式可再生能源对输电网扩展规划影响的方法

[1]Akbari, T., Heidarization, M., Siab, M.S., et al., 2012. Towards integrated planning: simultaneous transmission and substation expansion planning. Electr. Power Syst. Res., 86:131-139.

[2]Alizadeh, B., Dehghan, S., Amjady, N., et al., 2013. Robust transmission system expansion considering planning uncertainties. IET Gener. Transm. Distrib., 7(11):1318-1331.

[3]Asadamongkol, S., Eua-Arporn, B., 2010. Benders Decomposition Based Method for Multistage Transmission Expansion Planning with Security Constraints. PhD Thesis, Department of Electrical Engineering, Chulalongkorn University, Bangkok.

[4]Bahiense, L., Oliveira, G.C., Pereira, M., et al., 2001. A mixed integer disjunctive model for transmission network expansion. IEEE Trans. Power Syst., 16(3):560-565.

[5]Bent, R., Berscheid, A., Loren Toole, G., 2011. Generation and transmission expansion planning for renewable energy integration. Power Systems Computation Conf.

[6]Bertsimas, D., Litvinov, E., Sun, X.A., et al., 2013. Adaptive robust optimization for the security constrained unit commitment problem. IEEE Trans. Power Syst., 28(1):52-63.

[7]Cebeci, M.E., Eren, S., Tor, O.B., et al., 2011. Transmission and substation expansion planning using mixed integer programming. North American Power Symp., p.1-5.

[8]Chanda, R.S., Bhattacharjee, P.K., 1994. Application of computer software in transmission expansion planning using variable load structure. Electr. Power Syst. Res., 31(1):13-20.

[9]da Silva, E.L., Ortiz, J.M.A., Oliviera, G.C., et al., 2001. Transmission network expansion planning under a tabu search approach. IEEE Trans. Power Syst., 16(1):62-68.

[10]Department of Alternative Energy Development and Efficiency (DEDE), 2012. Alternative Energy Development Plan: AEDP 2012–2021. Ministry of Energy, Thailand.

[11]Dusonchet, Y.P., El-Abiad, A.H., 1973. Transmission planning using discrete dynamic optimization. IEEE Trans. Power Appar. Syst., PAS-92(4):1358-1371.

[12]Ekwue, A.O., Cory, B.J., 1984. Transmission system expansion planning by interactive methods. IEEE Trans. Power Appl. Syst., PAS-103(7):1583-1591.

[13]Escobar, A.H., Gallego, R.A., Romero, R., 2004. Multistage and coordinated planning of the expansion of transmission systems. IEEE Trans. Power Syst., 19(2):735-744.

[14]Fuchs, I., Völler, S., Gjengedal, T., 2011. Improved method for integrating renewable energy sources into the power system of northern Europe: transmission expansion planning for wind power integration. 10th Int. Conf. on Environment and Electrical Engineering, p.1-4.

[15]Grainger, J., William, S.J., 1994. Power System Analysis. McGraw Hill, Singapore.

[16]Hajimiragha, A.H., Cañizares, C.A., Fowler, M.W., et al., 2011. A robust optimization approach for planning the transition to plug-in hybrid electric vehicles. IEEE Trans. Power Syst., 26(4):2264-2274.

[17]Jabr, R.A., 2013. Robust transmission network expansion planning with uncertain renewable generation and loads. IEEE Trans. Power Syst., 28(4):4558-4567.

[18]Katdee, A., 2010. Tabu Searching. Rangsit University, Thailand.

[19]Khatib, H., 2003. Economic Evaluation of Projects in the Electricity Supply Industry. The Institution of Engineering and Technology, London, England.

[20]Latorre, G., Cruz, R.D., Areiza, J.M., et al., 2003. Classification of publications and models on transmission expansion planning. IEEE Trans. Power Syst., 18(2):938-946.

[21]Leite da Silva, A.M., Fonseca Manso, L.A., de Sousa Sales, W., et al., 2012. Chronological power flow for planning transmission systems considering intermittent sources. IEEE Trans. Power Syst., 27(4):2314-2322.

[22]Monticelli, A., Santos, A.Jr., Pereira, M.V.F., et al., 1982. Interactive transmission network planning using a least-effort criterion. IEEE Trans. Power Appar. Syst., PAS-101(10):3919-3925.

[23]Mori, H., Sone, Y., 2001. A parallel tabu search based approach to transmission network expansion planning. IEEE Porto Power Tech Conf.

[24]Muñoz, C., Sauma, E., Contreras, J., et al., 2012. Impact of high wind power penetration on transmission network expansion planning. IET Gener. Transm. Distrib., 6(12):1281-1291.

[25]Rezaee Jordehi, A., 2014a. A chaotic-based big bang–big crunch algorithm for solving global optimization problems. Neur. Comput. Appl., 25(6):1329-1335.

[26]Rezaee Jordehi, A., 2014b. Optimal setting of TCSCs in power systems using teaching-learning-based optimisation algorithm. Neur. Comput. Appl., 26(5):1249-1256.

[27]Rezaee Jordehi, A., 2015a. Brainstorm optimisation algorithm (BSOA): an efficient algorithm for finding optimal location and setting of FACTS devices in electric power. Int. J. Electr. Power Energy Syst., 69:48-57.

[28]Rezaee Jordehi, A., 2015b. Chaotic bat swarm optimisation (CBSO). Appl. Soft Comput., 26:523-530.

[29]Rezaee Jordehi, A., 2015c. Enhanced leader PSO (ELPSO): a new algorithm for allocating distributed TCSC’s in power systems. Int. J. Electr. Power Energy Syst., 64:771-784.

[30]Rezaee Jordehi, A., 2015d. Enhanced leader PSO (ELPSO): a new PSO variant for solving global optimisation problems. Appl. Soft Comput., 26:401-417.

[31]Rider, M.J., Garcia, A.V., Romero, R., 2007. Power system transmission network expansion planning using AC model. IET Gener. Transm. Distrib., 1(5):731-742.

[32]Romero, R., Gallego, R.A., Monticelli, A., 1996. Transmission system expansion planning by simulated annealing. IEEE Trans. Power Syst., 11(1):364-369.

[33]Sarić, A.T., Stanković, A.M., 2009. A robust algorithm for volt/var control. IEEE Power Systems Conf. and Exposition, p.1-8.

[34]Sepasian, M.S., Seifi, H., Foroud, A.A., et al., 2006. A new approach for substation expansion planning. IEEE Trans. Power Syst., 21(2):997-1004.

[35]Stoll, H.G., 1989. Least-Cost Electric Utility Planning. John Wiley & Sons, New York, United States.

[36]Sullivan, W.G., Wicks, E.M., Luxhoj, J.T., 2003. Engineering Economy. Pearson Education, New Jersey, USA.

[37]University of York, 2004. Orthogonal Arrays (Taguchi Designs). Available from http://www.york.ac.uk/depts/maths/tables/orthogonal.htm [Accessed on June 20, 2014].

[38]Youssef, H.K., Hackam, R., 1989. New transmission planning model. IEEE Trans. Power Syst., 4(1):9-18.

[39]Yu, H., Rosehart, W.D., 2012. An optimal power flow algorithm to achieve robust operation considering load and renewable generation uncertainties. IEEE Trans. Power Syst., 27(4):1808-1817.

[40]Yu, H., Chung, C.Y., Wong, K.P., et al., 2009. A chance constrained transmission network expansion planning method with consideration of load and wind farm uncertainties. IEEE Trans. Power Syst., 24(3):1568-1576.

[41]Yu, H., Chung, C.Y., Wong, K.P., 2011. Robust transmission network expansion planning method with Taguchi’s orthogonal array testing. IEEE Trans. Power Syst., 26(3):1573-1580.

[42]Zahedi, A., 2012. Performance evaluation of wind turbine using Monte Carlo method and turbine power curve. Int. Power and Energy Conf., p.161-165.