Full Text:   <2522>

Summary:  <1880>

CLC number: TM715

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2015-09-21

Cited: 0

Clicked: 6606

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Rongrit Chatthaworn

http://orcid.org/0000-0001-9258-7141

-   Go to

Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2015 Vol.16 No.10 P.871-882

http://doi.org/10.1631/FITEE.1500049


An approach for evaluating the impact of an intermittent renewable energy source on transmission expansion planning


Author(s):  Rongrit Chatthaworn, Surachai Chaitusaney

Affiliation(s):  Department of Electrical Engineering, Chulalongkorn University, Bangkok 10330, Thailand

Corresponding email(s):   c.rongrit@gmail.com, surachai.c@chula.ac.th

Key Words:  Adaptive tabu search, Renewable energy generation, Robust optimization, Transmission expansion planning


Rongrit Chatthaworn, Surachai Chaitusaney. An approach for evaluating the impact of an intermittent renewable energy source on transmission expansion planning[J]. Frontiers of Information Technology & Electronic Engineering, 2015, 16(10): 871-882.

@article{title="An approach for evaluating the impact of an intermittent renewable energy source on transmission expansion planning",
author="Rongrit Chatthaworn, Surachai Chaitusaney",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="16",
number="10",
pages="871-882",
year="2015",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1500049"
}

%0 Journal Article
%T An approach for evaluating the impact of an intermittent renewable energy source on transmission expansion planning
%A Rongrit Chatthaworn
%A Surachai Chaitusaney
%J Frontiers of Information Technology & Electronic Engineering
%V 16
%N 10
%P 871-882
%@ 2095-9184
%D 2015
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1500049

TY - JOUR
T1 - An approach for evaluating the impact of an intermittent renewable energy source on transmission expansion planning
A1 - Rongrit Chatthaworn
A1 - Surachai Chaitusaney
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 16
IS - 10
SP - 871
EP - 882
%@ 2095-9184
Y1 - 2015
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1500049


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

目的:针对间歇式可再生能源对输电网扩展规划(Transmission expansion planning, TEP)的影响,提出一种稳健的最优化评估方法。
创新点:TEP的目标函数由传输线的投资成本和常规发电机的运行成本组成。为对所有的运行场景都获取稳健的扩展规划,提出一种选择恰当“代表间断性可再生能源的生产和负载”运行场景的方法。
方法:在所提出的TEP中,使用自适应禁忌算法(ATS,一种元启发式算法)。ATS在主问题(最小化投资和运营成本)和子问题(最小化常规电机电能生产成本,缩减可再生能源的生产和负载)间相互迭代。其中子问题由基于内点方法的非线性规划求解。此外,通过在考虑或不考虑可再生能源的条件下对比扩展规划,进一步评估间歇式可再生能源对TEP的影响。
结论:使用IEEE Reliability Test System 79(RTS79)测试所述方法,并评估间歇式可再生能源对TEP的影响。结果显示,相较其他方法本文所述最优化方法能够给出更为稳健的结果;而且,间歇式可再生能源对TEP的影响是应当纳入考虑范围的。

关键词:自适应禁忌搜索;可再生能源生产;鲁棒优化;输电扩展规划

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[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.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE