Abstract
The convergence of the electric power industry toward the competitive framework throughout the world has led to a market environment replacing the traditional monopolistic scenario. It has given rise to more efficient production and distribution of electricity, provided a better choice to market participants while maintaining the security and reliability of the power supply. Earlier power utilities had been producing electrical power with the objective to minimize the costs and demand, as well as reserves, were met. Under the new structure, generation companies (GENCOs) schedule their generators to maximize profit. This paper uses a new approach to deal with profit-based unit commitment (PBUC), considering the conditions of power and reserve. The proposed method allows GENCO to decide how much power and reserve should be sold in the markets to achieve maximum profit. For the PBUC problem, three computational techniques, namely ANTIGONE, COUENNE, and BARON in general algebraic modeling system (GAMS), have been applied on three test case studies comprising three, ten, and hundred thermal units in a day-ahead power market. The uncertainty in the energy spot price has been considered using Monte Carlo simulation approach. The various diversified constraints such as system energy load, spinning reserve, ramp rate, unit up and downtime imposed on the PBUC problem have been considered while solving the problem. Simulation results demonstrate that the BARON method has provided better results and has outperformed over the ANTIGONE and COUENNE methods and previously existing techniques reported in the literature in terms of solution quality, the satisfaction of constraints, and an ability to solve large-scale test system.
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Abbreviations
- i:
-
No. of generators
- t :
-
Time interval
- r :
-
Probability of reserve to be served, generated, and called
- a i, :
-
bi, ci, Cost coefficients of ith unit
- DR i :
-
Ramp-down limit of unit i in MW
- UR i :
-
Ramp-up limit of unit i in MW
- F i (P i t ) :
-
Production cost of unit i at tth time
- SR t :
-
Scheduled spinning reserve at time t
- P D t :
-
Power demand at tth time in MW
- T i, up :
-
Minimum up time of unit i in hours
- T i, down :
-
Minimum down time of unit i in hours
- RP t :
-
Scheduled reserve price at time t
- U (I, t) :
-
Binary variable for ON/OFF status
- PF :
-
Profit
- P(i, t) :
-
Power generated of ith generator at time t
- R(i, t) :
-
Reserve generated of ith generator at time t
- RV(i, t) :
-
Revenue earned of ith generator at time t
- TC(i, t) :
-
Total cost incurred of ith generator at time t
- T i, on t :
-
Continuously ON time of unit i till tth time
- T i, off t :
-
Continuously OFF time of unit i till tth time
- SP t :
-
Scheduled spot price at time t
- N :
-
Number of thermal units
- T :
-
Scheduling time intervals in hours
- SU(i, t) :
-
Start-up cost of ith thermal unit at time t.
- HS :
-
Hot start-up costs
- CS :
-
Cold start-up cost
- T i, Cold :
-
Cold hour time of ith thermal unit
- P i, Min :
-
Minimum generating limit
- P i, Max :
-
Maximum generating limit
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Acknowledgements
The research work is sponsored by the Council of Scientific and Industrial Research (CSIR), New Delhi, India, under Human Resources Development Group project Grant 22(0815)/19/EMR-II sanctioned to the second author.
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Submitted with approval from the supervisor (Dr. R. Naresh), the authors declare that they have no conflict of interest.
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Kumar, V., Naresh, R. & Sharma, V. GAMS Environment Based Solution Methodologies for Ramp Rate Constrained Profit Based Unit Commitment Problem. Iran J Sci Technol Trans Electr Eng 45, 1325–1342 (2021). https://doi.org/10.1007/s40998-021-00447-4
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DOI: https://doi.org/10.1007/s40998-021-00447-4