A practical approach for profit-based unit commitment with emission limitations

This paper proposes a practical approach for profit-based unit commitment (PBUC) with emission limitations. Under deregulation, unit commitment has evolved from a minimum-cost optimisation problem to a profit-based optimisation problem. However, as a consequence of growing environmental concern, the impact of fossil-fuelled power plants must be considered, giving rise to emission limitations. The simultaneous address of the profit with the emission is taken into account in our practical approach by a multiobjective optimisation (MO) problem. Hence, trade-off curves between profit and emission are obtained for different energy price profiles, in a way to aid decision-makers concerning emission allowance trading. Moreover, a new parameter is presented, ratio of change, and the corresponding gradient angle, enabling the proper selection of a compromise commitment for the units. A case study based on the standard IEEE 30-bus system is presented to illustrate the proficiency of our practical approach for the new competitive and environmentally constrained electricity supply industry.

[1]  Terje Gjengedd Emission Constrained Unit-Commitment (ECUC) , 1996 .

[2]  O. P. Malik,et al.  Environmentally constrained unit commitment , 1992 .

[3]  Claudio Gentile,et al.  Solving unit commitment problems with general ramp constraints , 2008 .

[4]  Joao P. S. Catalao,et al.  Optimising power generation efficiency for head-sensitive cascaded reservoirs in a competitive electricity market , 2008 .

[5]  Weerakorn Ongsakul,et al.  Enhanced merit order and augmented Lagrange Hopfield network for hydrothermal scheduling , 2008 .

[6]  E. Allen,et al.  Price-Based Commitment Decisions in the Electricity Market , 1998 .

[7]  Malabika Basu,et al.  Dynamic economic emission dispatch using nondominated sorting genetic algorithm-II , 2008 .

[8]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[9]  Sandoval Carneiro,et al.  A Lagrangian multiplier based sensitive index to determine the unit commitment of thermal units , 2008 .

[10]  Joao P. S. Catalao,et al.  Short‐term scheduling of thermal units: emission constraints and trade‐off curves , 2008 .

[11]  Ahmed Yousuf Saber,et al.  Scalable unit commitment by memory-bounded ant colony optimization with A∗ local search , 2008 .

[12]  Kaisa Miettinen,et al.  Nonlinear multiobjective optimization , 1998, International series in operations research and management science.

[13]  V. Mendes,et al.  Short-term electricity prices forecasting in a competitive market: A neural network approach , 2007 .

[14]  G. Sheblé,et al.  Power generation operation and control — 2nd edition , 1996 .

[15]  Farshid Keynia,et al.  Day ahead price forecasting of electricity markets by a mixed data model and hybrid forecast method , 2008 .

[16]  M. A. Abido,et al.  Multiobjective particle swarm optimization for environmental/economic dispatch problem , 2009 .

[17]  Hector Pulgar-Painemal Short-term generation scheduling under a SO2 emissions allowances market , 2005 .

[18]  J.S. McConnach,et al.  A more perfect energy union , 2006, IEEE Power and Energy Magazine.

[19]  Luís Ferreira,et al.  Short-term resource scheduling in multi-area hydrothermal power systems , 1989 .

[20]  Ashwani Kumar,et al.  Electricity price forecasting in deregulated markets: A review and evaluation , 2009 .

[21]  T. Dillon,et al.  Electricity price short-term forecasting using artificial neural networks , 1999 .

[22]  T. Das,et al.  A survey of critical research areas in the energy segment of restructured electric power markets , 2009 .

[23]  K. W. Edwin,et al.  Integer Programming Approach to the Problem of Optimal Unit Commitment with Probabilistic Reserve Determination , 1978, IEEE Transactions on Power Apparatus and Systems.

[24]  Jaspreet Singh Dhillon,et al.  Secure multiobjective real and reactive power allocation of thermal power units , 2008 .

[25]  Joao P. S. Catalao INFLUENCE OF PRICE FORECASTING ON SHORT-TERM THERMAL SCHEDULING WITH ENVIRONMENTAL CONCERNS , 2008 .