Analysis of System Operation Optimization In Steam Power Plants with the Lagrange Method

Aripriharta Aripriharta; Rafli Amirul Husain; Sujito Sujito; Mohamad Rodhi Faiz; Muchamad Wahyu Prasetyo; Arya Kusumawardana; Langlang Gumilar; Muhammad Afnan Habibi

doi:10.33019/jurnalecotipe.v11i1.4479

Aripriharta Aripriharta Department of Electrical Engineering and Informatics, University Negeri Malang https://orcid.org/0000-0002-5313-6978
Rafli Amirul Husain Department of Electrical Engineering and Informatics, University Negeri Malang
Sujito Sujito Department of Electrical Engineering and Informatics, University Negeri Malang https://orcid.org/0000-0001-5917-306X
Mohamad Rodhi Faiz Department of Electrical Engineering and Informatics, University Negeri Malang https://orcid.org/0000-0002-6684-739X
Muchamad Wahyu Prasetyo Department of Electrical Engineering and Informatics, University Negeri Malang
Arya Kusumawardana Department of Electrical Engineering and Informatics, University Negeri Malang https://orcid.org/0000-0001-7919-7528
Langlang Gumilar Department of Electrical Engineering and Informatics, University Negeri Malang https://orcid.org/0000-0001-8772-2046
Muhammad Afnan Habibi Department of Electrical Engineering and Informatics, University Negeri Malang https://orcid.org/0000-0002-7484-480X

DOI: https://doi.org/10.33019/jurnalecotipe.v11i1.4479

Abstract

Steam Power Plant (PLTU) is a plant that relies on kinetic energy from hot steam to produce electrical energy. At the Paiton Power Plant, thermal energy is generated from burning a certain amount of coal. The use of coal-fired power plants still dominates most of the world's electricity supply. The optimal operation of electric power systems has grown in importance in recent years due to ever-increasing fuel costs. An electric power system basically consists of power generation units that aim to serve the needs of the load. Total production costs can be minimized by a combination of power loading on existing generating units so that an optimal load or more is obtained. This optimization process is called Economic Dispatch. Economic Dispatch has conducted a lot of research using various optimization methods. In this study, the optimization method to be used is the Lagrange method. Firefly algorithm and genetic algorithm methods are also used as performance comparisons. The results of this study show that the lagrange method can optimize generation costs with a difference of 243,227,475 $ / hour or 7,043% of the actual cost. While the firefly algorithm gets a difference of 243,227,471 $ / hour or 7.043% of the actual cost. And the genetic algorithm gets a cost difference of 242,119,792 $ / hour or 7,011% of the actual cost.

Keywords: Cost Optimization, Economic Dispatch, Lagrange

Downloads

Download data is not yet available.

References

“Consumption Prediction on Steam Power Plant Using Data Mining Hybrid Particle Swarm Optimization (PSO) and Auto Regressive Integrated Moving Average (ARIMA),” 2019 Int. Work. Big Data Inf. Secur. IWBIS 2019, pp. 15–20, 2019, doi: 10.1109/IWBIS.2019.8935844.

“Electricity Generation-World.”. https://www.iea.org/fuels-and-technologies/electricity

“Optimization of Economic Dispatch of 150 kV Sulselrabar System using Lagrange Approach,” 2019 Int. Conf. Technol. Policies Electr. Power Energy, TPEPE 2019, 2019, doi: 10.1109/IEEECONF48524.2019.9102594.

“Pengiriman Ekonomi Ideal dari Unit Tenaga Panas,” vol. 1, no. 1, 2021.

“Optimal Scheduling Algorithm for Coal-Powered Power Plants-Considering Coal Delivery Constraints,” ICT-PEP 2021 - Int. Conf. Technol. Policy Energy Electr. Power Emerg. Energy Sustain. Smart Grid, Microgrid Technol. Futur. Power Syst. Proc., no. September, pp. 307–312, 2021, doi: 10.1109/ICT-PEP53949.2021.9601098.

“Genetic Algorithm for Solving the Economic Load Dispatch,” Int. J. Electron. Electr. Eng., vol. 7, no. 5, pp. 523–528, 2014.

“A Wind Turbine Generator Design and Optimization for DC Collector Grids,” IEEE J. Emerg. Sel. Top. Power Electron., vol. 10, no. 1, pp. 484–493, 2022, doi: 10.1109/JESTPE.2021.3066278.

“Multi-Objective Optimization Design of Bearingless Permanent Magnet Synchronous Generator,” IEEE Trans. Appl. Supercond., vol. 30, no. 4, 2020, doi: 10.1109/TASC.2020.2970661.

“Combinatorial optimization of pulverizers for blended-coal-fired power plant,” Proc. - Int. Conf. Comput. Distrib. Control Intell. Environ. Monit. CDCIEM 2011, pp. 413–418, 2011, doi: 10.1109/CDCIEM.2011.323.

“Individual Thermal Generator and Battery Storage Bidding Strategies Based on Robust Optimization,” IEEE Access, vol. 9, pp. 66829–66838, 2021, doi: 10.1109/ACCESS.2021.3076872.

“Investigation and optimization of a Co-Generation plant integrated of gasifier, gas turbine and heat pipes using minimization of Gibbs free energy, Lagrange method and response surface methodology,” Int. J. Hydrogen Energy, vol. 45, no. 38, pp. 19027–19044, 2020, doi: 10.1016/j.ijhydene.2020.04.278.

“Analytical optimization of photovoltaic output with Lagrange Multiplier Method,” Optik (Stuttg)., vol. 199, no. June, p. 163379, 2019, doi: 10.1016/j.ijleo.2019.163379.

“Multi-layered optimization of demand resources using lagrange dual decomposition,” IEEE Trans. Smart Grid, vol. 4, no. 4, pp. 2081–2088, 2013, doi: 10.1109/TSG.2013.2261565.

“Passivity-Based Control of photovoltaic-wind hybrid system with Euler-Lagrange modeling,” IECON Proc. (Industrial Electron. Conf., pp. 1126–1131, 2012, doi: 10.1109/IECON.2012.6388614.

“Comparison of the Lagrange’ s and Particle Swarm Optimisation Solutions of an Economic Emission Dispatch Problem” pp. 1–8, 2012.

“Power System Optimization Model Using Economic Load Dispatch,” 2020 IEEE Reg. 10 Symp. TENSYMP 2020, no. June, pp. 469–472, 2020, doi: 10.1109/TENSYMP50017.2020.9230967.

"Comparison of Firefly and Hybrid Firefly-APSO Algorithm for Power Economic Dispatch Problem," 2020 International Conference on Technology and Policy in Energy and Electric Power (ICT-PEP), Bandung, Indonesia, 2020, pp. 94-99, doi: 10.1109/ICT-PEP50916.2020.9249799.

“Penggunaan Algoritma Genetika Dalam Peningkatan Kinerja Fuzzy Clustering Untuk (Application of Genetic Algorithm to Enhance the Performance of Clustering,” Berk. MIPA, vol. 17, no. 2, pp. 1–14, 2007.

“A statistical energy efficiency optimization method for coal-fired power generation systems,” Proc. 2015 IEEE Innov. Smart Grid Technol. - Asia, ISGT ASIA 2015, 2016, doi: 10.1109/ISGT-Asia.2015.7387118.

“Power systems optimization under uncertainty: A review of methods and applications,” Electr. Power Syst. Res., vol. 214, no. May 2022, 2023, doi: 10.1016/j.epsr.2022.108725.

T. De Paula Machado Bazzo, J. F. Kölzer, R. Carlson, F. Wurtz, and L. Gerbaud, “Multiphysics Design Optimization of a Permanent Magnet Synchronous Generator,” IEEE Trans. Ind. Electron., vol. 64, no. 12, pp. 9815–9823, 2017, doi: 10.1109/TIE.2017.2726983.

“An Energy Management System for Isolated Microgrids with Thermal Energy Resources,” IEEE Trans. Smart Grid, vol. 11, no. 4, pp. 2880–2891, 2020, doi: 10.1109/TSG.2020.2973321.

“Comparison of ship power systems from an optimal economic operation point of view,” 2015 IEEE Electr. Sh. Technol. Symp. ESTS 2015, pp. 256–260, 2015, doi: 10.1109/ESTS.2015.7157900.

“PSO Based Controlled Six-phase Grid Connected Induction Generator for Wind Energy Generation,” CES Trans. Electr. Mach. Syst., vol. 5, no. 1, pp. 41–49, 2021, doi: 10.30941/CESTEMS.2021.00006.