Optimisasi Penjadwalan Pembangkit pada Microgrid dengan Mempertimbangkan Respons Beban

https://doi.org/10.22146/juliet.v3i1.74669

Candra Febri Nugraha(1*), Lukman Subekti(2)

(1) Departemen Teknik Elektro dan Informatika, Universitas Gadjah Mada
(2) Departemen Teknik Elektro dan Informatika, Universitas Gadjah Mada
(*) Corresponding Author

Abstract


Abstract – In a smart grid, the adequacy of electricity supply is not only determined by generation, but the electrical demand can also be involved. Demand response is one way to maintain a balance between electricity supply and load by reducing electricity consumption at a certain period. In this study, a microgrid system operating design is proposed by considering the penetration of new and renewable energy and demand response. Optimization is carried out with the aim of obtaining the lowest generation costs, while maximizing customer benefits from the demand response program. The mixed-integer linear programming method is used to determine generator generation and customer load reduction throughout the planning period. The obtained diesel generator operating cost is $116.40 and the total customer load response benefit is $100. Based on the analysis, the demand response is able to help the system maintain a power balance in critical conditions, namely when the supply from the generator is not sufficient. From the test system used, it was found that the load curtailment throughout the planning  period is 67.04 kWh for three customers. The distribution of the reduced demand depends on the value of the demand response incentive for each customer. The amount of load reduction is strongly influenced by the specified demand response budget.

Keywords – optimal dispatch, demand response, microgrid, mixed-integer linear programming

IntisariDalam smart grid, kecukupan pasokan listrik tidak hanya ditentukan oleh pembangkitan saja, tetapi beban listrik juga dapat dilibatkan. Respons beban merupakan salah satu cara untuk menjaga keseimbangan antara pasokan dan beban listrik dengan cara mengurangi pemakaian listrik pada waktu-waktu tertentu. Dalam studi ini diusulkan sebuah desain operasi sistem microgrid dengan mempertimbangkan penetrasi energi baru dan terbarukan serta respons beban. Optimisasi dilakukan dengan tujuan untuk memperoleh biaya pembangkitan terendah, sekaligus memaksimalkan keuntungan pelanggan dari program respons beban. Metode mixed-integer linear programming digunakan untuk menentukan pembangkitan pada generator dan pengurangan beban pelanggan sepanjang periode perencanaan. Biaya operasi pembangkit diesel yang diperoleh adalah $116,40 dan keuntungan respons beban yang diperoleh pelanggan sebesar $100. Berdasarkan analisis, respons beban mampu membantu sistem menjaga keseimbangan daya pada kondisi-kondisi kritis, yaitu ketika suplai dari pembangkit sedang tidak mencukupi. Dari sistem pengujian yang digunakan, diperoleh penurunan beban yang terjadi selama periode penjadwalan adalah 67,04 kWh pada tiga pelanggan. Distribusi beban yang dikurangi bergantung pada nilai insentif respons beban pada tiap-tiap pelanggan. Besarnya penurunan beban sangat dipengaruhi oleh anggaran respons beban yang ditetapkan.

Kata kuncipenjadwalan pembangkit, respons beban, microgrid, pemrograman mixed-integer linear


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References

[1] C. Cecati, G. Mokryani, A. Piccolo, and P. Siano, “An overview on the Smart Grid concept,” IECON Proc. (Industrial Electron. Conf., pp. 3322–3327, 2010, doi: 10.1109/IECON.2010.5675310.

[2] F. Rahimi and A. Ipakchi, “Demand Response as a Market Resource Under the Smart Smart Grid Paradigm,” IEEE Trans. Smart Grid, vol. 1, no. 1, pp. 82–88, 2010, [Online]. Available: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5454394.

[3] V. S. K. M. Balijepalli, V. Pradhan, S. A. Khaparde, and R. M. Shereef, “Review of demand response under smart grid paradigm,” 2011 IEEE PES Int. Conf. Innov. Smart Grid Technol. ISGT India 2011, pp. 236–243, 2011, doi: 10.1109/ISET-India.2011.6145388.

[4] N. Kagan, C. F. M. Almeida, U. D. S. Paulo, E. Vicentini, and A. E. S. Eletropaulo, “Study of the Distributed Generation Impact on Distributed Networks , Focused on Quality of,” pp. 6–11, 2016.

[5] A. V Shalukho, I. A. Lipuzhin, and A. A. Voroshilov, “Power Quality in Microgrids with Distributed Generation,” pp. 54–58, 2019.

[6] W. Huang, Z. Fu, and L. Hua, “Research on optimal capacity configuration for distributed generation of island micro-grid with wind/solar/battery/diesel engine,” 2018.

[7] N. I. Nwulu and X. Xia, “Optimal dispatch for a microgrid incorporating renewables and demand response,” Renew. Energy, vol. 101, pp. 16–28, 2017, doi: 10.1016/j.renene.2016.08.026.

[8] B. Imtiaz, Y. Cui, and I. Zafar, “Economic Dispatch of Microgrid Incorporating Demand Response Using Dragonfly Algorithm,” 2021 IEEE Int. Conf. Adv. Electr. Eng. Comput. Appl. AEECA 2021, pp. 59–68, 2021, doi: 10.1109/AEECA52519.2021.9574430.

[9] A. R. Jordehi, M. S. Javadi, and J. P. S. Catalao, “Dynamic Economic Load Dispatch in Isolated Microgrids with Particle Swarm Optimisation considering Demand Response,” UPEC 2020 - 2020 55th Int. Univ. Power Eng. Conf. Proc., pp. 13–17, 2020, doi: 10.1109/UPEC49904.2020.9209769.

[10] T. Zhang, J. Zhang, L. Wang, and D. Zhang, “Optimal economic dispatch for intelligent community micro-grid considering demand response,” IGBSG 2018 - 2018 Int. Conf. Intell. Green Build. Smart Grid, pp. 1–4, 2018, doi: 10.1109/IGBSG.2018.8393560.

[11] Z. Wang, Y. Shao, X. Dou, J. Wang, and X. Zhang, “Optimal dispatch of microgrid considering interruptible load,” 2020 12th IEEE PES Asia-Pacific Power Energy Eng. Conf., vol. 3, 2020.

[12] M. Tkiouat and I. Abdou, “Unit Commitment Problem in Electrical Power System: A Literature Review,” Int. J. Electr. Comput. Eng., vol. 8, no. 3, pp. 1357–1372, 2018, doi: 10.11591/ijece.v8i3.pp1357-1372.

[13] IESR, “Technical Report: A Roadmap for Indonesia’s Power Sector: How Renewable Energy Can Power Java-Bali and Sumatera,” 2019.

[14] Westario Power Inc., “May 2021 Electricity Pricing Changes.” Ontario, 2021, [Online]. Available: https://westario.com/may-2021-electricity-pricing-changes/.



DOI: https://doi.org/10.22146/juliet.v3i1.74669

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