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Unit Commitment Effects in Economic Scheduling of Generators


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DOI: https://doi.org/10.15866/iree.v16i3.20266

Abstract


The generator scheduling problem seems simple, i.e., the demand should be met by generators that have been installed. On the other hand, fuel costs optimization is quite challenging. Under certain conditions, e.g., at the lowest load, generating capacity can exceed the demand when all the generators are operated. Thus, some generators should be turned off in order to minimize fuel costs. In this case, unit commitment is one of the interesting issues to be studied. It can reduce fuel costs and transmission losses in accordance with the generator power composition and location. This paper proposes a method that considers unit commitment in the optimization processes quickly and accurately. It will be considered in determining generator scheduling. The optimization process starts with the temporary results based on the direct method. The temporary results will determine whether the generator is on or off by considering the generator limits. At the same time, transmission losses will be evaluated with the B-Loss Matrix once the final results are obtained. This method has been tested with 26 buses and six generators with satisfactory results. Although the transmission losses have increased by 122.8% (i.e., increase of 64.422 MW, from 281.739 MW to 346.161 MW) compared to the results without unit commitment, the fuel costs have fallen to 85.24% (i.e., from $417,996.5 to $356,294.2) of all the generators stated commit.
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Keywords


Generator Scheduling; Fuel Optimization; Turn-Off; Generator Limits; Transmission Losses

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References


H. Sadat, Power System Analysis, Boston, McGraw-Hill, 1999.

R. H. Miller and J.H. Malinowski,Economic Operation of Power Systems, Power System Operation, 3rd ed., New York: McGraw-Hill, 1970, pp. 63-82.

B. M. Weedy and B. J. Corry,Basic power system economics and management, Electric Power Systems, 4th, New York: John Wiley & Sons Ltd, 1999, pp. 493-520.

Abu Siam, M., Mohamed, O., Al-Nazer, H., Comparative Study between Genetic Algorithms and Iterative Optimization for Economic Dispatch of Practical Power System, (2018) International Review of Electrical Engineering (IREE), 13 (2), pp. 128-136.
https://doi.org/10.15866/iree.v13i2.13870

Wachjoe, C., Zein, H., Raharjo, J., A Fast Scheduling Method to Solve Economic Load Dispatch Problem, (2020) International Review of Automatic Control (IREACO), 13 (1), pp. 12-18.
https://doi.org/10.15866/ireaco.v13i1.18130

Shahinzadeh H, Nasr Azadani SM, and Amirkabir Jannesari N., Applications of Particle Swarm Optimization Algorithm to Solving the Economic Load Dispatch of Units in Power Systems with Valve Point Effects, International Journal of Electrical and Computer Engineering (IJECE), 4(6), pp. 858-867, 2014.
https://doi.org/10.11591/ijece.v4i6.6720

Kaur G, and Kumar D., Economic Load Dispatch Problem Using Particle Swarm Optimization Technuque: A Review. An International Journal of Engineering Sciences, 3(1), pp. 31-36, 2014.

L. Daniel and KT Chaturvedi, A crazy Particle Swarm Optimization with Time Varying Acceleration Coefficients for Economic Load Dispatch, International Journal of Engineering and Advanced Technology, Vol. 9, Issue 2, 2019, pp. 1205-1213.
https://doi.org/10.35940/ijeat.b3614.129219

L. Ming, D. Wenqiang, and N. Fuzhong, An Adaptive Particle Swarm Optimization Algorithm Based on Directed Weighted Complex Network, Mathematical Problems in Engineering, School of Computer and Communication, Lan Zhou University of Technology, China. Report number: 434972, pp. 1-7, 2014.
https://doi.org/10.1155/2014/434972

Jabri, M., Helmi, A., Neural Network Based on Artificial Intelligence Solution for a Fast Economic Load Dispatch Using the Hybrid Lagrangian Method, (2019) International Journal on Energy Conversion (IRECON), 7 (5), pp. 181-187.
https://doi.org/10.15866/irecon.v7i5.17794

Sakthivel, V., Suman, M., Sathya, P., Nonconvex Economic Environmental Load Dispatch Using Fuzzy Based Squirrel Search Algorithm, (2020) International Journal on Energy Conversion (IRECON), 8 (2), pp. 61-70.
https://doi.org/10.15866/irecon.v8i2.18593

Sakthivel, V., Suman, M., Sathya, P., Environmental/Economic Dispatch Problem: Coulomb’s and Franklin’s Laws Based Optimization Algorithm, (2020) International Review of Electrical Engineering (IREE), 15 (5), pp. 421-430.
https://doi.org/10.15866/iree.v15i5.18568

Afandi, A., Wibawa, A., Padmantara, S., Fujita, G., Triyana, W., Sulistyorini, Y., Miyauchi, H., Tutkun, N., EL-Shimy Mahmoud, M., Gao, X., Designed Operating Approach of Economic Dispatch for Java Bali Power Grid Areas Considered Wind Energy and Pollutant Emission Optimized Using Thunderstorm Algorithm Based on Forward Cloud Charge Mechanism, (2018) International Review of Electrical Engineering (IREE), 13 (1), pp. 59-68.
https://doi.org/10.15866/iree.v13i1.14687

A. Kamal, A. Fakhar, S. Nisar, and M. Shafiq, Unit Commitment and Generation Scheduling of a Thermal Power Plant Using Economic Load Dispatch, International Electrical Engineering Journal (IEEJ), Vol. 8 No.1, pp. 2464-2478, 2018.

Allen JW. and Bruce FW, Power Generation, Operation, and Control, John Wiley & Sons, 1996.

Idriss Abdou and Mohamed Tkiouat, Unit Commitment Problem in Electrical Power System: A Literature Review, International Journal of Electrical and Computer Engineering (IJECE), Vol. 8, No. 3, pp. 1357-1372, June 2018.
https://doi.org/10.11591/ijece.v8i3.pp1357-1372

Balasim M. Hussein and Aqeel S. Jaber, Unit Commitment Based on Modified Firefly Algorithm, Measurement and Control, 2020, Vol. 53 (3-4), pp. 320-327.
https://doi.org/10.1177/0020294019890630

Saranya S and Saravanan B, A Review On Modeling Approaches For Stochastic Unit Commitment, International Journal Of Scientific & Technology Research, 2020, Vol. 9, Issue 02, pp. 27-37.

Masoud Aliakbari, Pouria Maghouli and Habib Allah Aalami, Reliability Constrained Unit Commitment Considering the Effect of DG and DR Program, International Journal of Electrical and Computer Engineering (IJECE), Vol. 8, No. 4, pp. 1985-1996, August 2018.
https://doi.org/10.11591/ijece.v8i4.pp1985-1996

Jabri, M., Aloui, H., Genetic Lagrangian Relaxation Selection Method for the Solution of Unit Commitment Problem, (2019) International Journal on Engineering Applications (IREA), 7 (2), pp. 59-64.
https://doi.org/10.15866/irea.v7i2.17022

Anthony Papavasilion and Samuel S. Oren, A Comparative Study of Stochastic Unit Commitment and Security-Constrained Unit Commitment Using High Performance Computing, European Control Conference (ECC), Zurich, Switzerland, 2013.
https://doi.org/10.23919/ecc.2013.6669244

Ayman R. Khaled Saed, The Effective Method of Solving Unit Commitment Problems Based on The Lagrange Relaxation Technique, The International Journal of Engineering and Information Technology (IJEIT), 2020, Vol. 6, No. 2, pp.170-175.

Ummuhan Basaran Filik and Mehmet Kurban, Solving Unit Commitment Using Modified Subgradient Method Combined with Simulated Annealing Algorithm, Hindawi Publishing Corporation Mathematical Problem in Engineering, Volume 2010, Article ID 295645,15 pages.
https://doi.org/10.1155/2010/295645

Pineda S, Fernández-Blanco R, Morales JM. Time-Adaptive Unit Commitment. IEEE Trans Power Syst. 2019.

M.S. Krishnarayalu, Unit commitment with economic dispatch, International Electrical Engineering Journal (IEEJ), Vol. 6, No.5, pp. 1913-1916, 2015.

Anurag Mandal and Ramjee Prasad Gupta, Optimal Load Dispatch with Unit Commitment, International Journal for Research & Development, Vol. 3, Issue 05, 2015, pp. 1051-1060.

B. Saravanan, A Solution to the unit commitment problem- a review, Front. Energy 2013, 7(2), pp. 223-236

Rammohan Mallipeddi and Ponnuthuroi Nagaratnam Suganthan, Unit Commitmen-a survey and comparison of conventional and nature inspired algorithms, Int. J. Bio-Inspired Computation, Vol. 6, No. 2, 2014, pp.71-90.
https://doi.org/10.1504/ijbic.2014.060609

Chitra C. and Dr. T. Amudha, Unit Commitment Problem and Solution-A Survey, International Journal of Innovation & Advancement in Computer Science, Vol. 6, Issue 8, 2017, pp.412-420.

Mohammad Masih Sediqi et al., Stochastic Unit Commitment and optimal Power Trading Incorporating PV Uncertainty, Sustainability, 2019, pp. 1-16.
https://doi.org/10.3390/su11164504

Chao-An Li et. al., Hydro Unit Commitment in Hydro-Thermal Optimization, IEEE Transaction on Power Systems, Vol. 12, No. 2, 1997, pp. 764-769.
https://doi.org/10.1109/59.589675

Marcin Pluta, Artur Wyrwa, Wojciech Suwata, Janusz Zysk, Maciej Raczynski, and Stanislaw Tokarski, A Generalized Unit Commitment and Economic Dispatch Approach for Analysing the Polish Power System under High Renewable Penetration, Energies, 2020, 13, 1952, pp. 1-18.
https://doi.org/10.3390/en13081952

L.Alvarado-Barrios, A. Rodriquez del Nozal, A. Tapia, J.L. Martinez-Ramos, and D.G. Reina, An Evolutionary Computational Approach for the Problem of Unit Commitment and Economic Dispatch in Microgrids under Several Operation Modes, Energies, 2019, 12, 2143, pp. 1-23.
https://doi.org/10.3390/en12112143

Nadine Awadah, Rawan AlShikh Ali, Shaika AlBaijan, Ghalia Al-Qallah, Muneerah Al-Hassawi, and Suat Kasap, Dynamic Programming Approach to Unit Commitment Problem for Kuwait Power Generations, Proceeding of the International Conference on Industrial Engineering and Operations Management Paris, France, July, 26-27, 2018, pp. 1939-1947.

Ying-Yi Hong, Gerard Francesco DG. Apolinario, Chen-Nien Chung, Tai-Ken Lu, and Chia-Chi Chu, Effect of Taiwan's Energy Policy on Unit Commitment in 2025, Applied Energy, 277, 2020, 115585, pp. 1-17.
https://doi.org/10.1016/j.apenergy.2020.115585


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