Recent approaches of unit commitment in the presence of intermittent renewable energy resources: A review

Unit Commitment (UC) is an optimization problem used to determine the operation schedule of the generating units at every hour interval with varying loads and generations under different generational, environmental and technical constraints. With the significant increase of Renewable Energy Sources (RES) integration into the power networks, effects posed by these system changes to the UC are actively being studied and investigated by global researchers and operation engineers. To this end, this paper firstly provides a literature survey of UC concept, objectives and constraints. Different UC models developed for addressing RES impacts are also reviewed. Moreover, many algorithms have been proposed in the past few decades to optimize the UC problem. This work explores the necessity for alternative optimization approaches for UC solution. In doing that, the work uncovers the advantages and disadvantages of the existing methodologies so that future algorithms could be designed in retaining the advantages of the existing methodologies while avoiding the presented weaknesses. In addition, installation of energy storage devices to balance the fluctuation in power generation and their associated impacts on UC models are reviewed. The contents of this paper provide ready-to-refer and ready-to-use information for the researchers working in the field of UC.

[1]  P. Poggi,et al.  Risk-Constrained Unit Commitment of Power System Incorporating PV and Wind Farms , 2011 .

[2]  I. A. Farhat,et al.  Optimization methods applied for solving the short-term hydrothermal coordination problem , 2009 .

[3]  Mohammad Yusri Hassan,et al.  Review of storage schemes for wind energy systems , 2013 .

[4]  Hiroyuki Mori,et al.  Unit commitment using Tabu search with restricted neighborhood , 1996, Proceedings of International Conference on Intelligent System Application to Power Systems.

[5]  A. Osmani,et al.  Electricity generation from renewables in the United States: Resource potential, current usage, technical status, challenges, strategies, policies, and future directions , 2013 .

[6]  Yuping Huang,et al.  Two-stage stochastic unit commitment model including non-generation resources with conditional value-at-risk constraints , 2014 .

[7]  T. Sawa,et al.  Security Constrained Integrated Unit Commitment Using Quadratic Programming , 2007, 2007 IEEE Lausanne Power Tech.

[8]  Weerakorn Ongsakul,et al.  Ramp rate constrained unit commitment by improved priority list and augmented Lagrange Hopfield network , 2008 .

[9]  Dixit Garg,et al.  Barriers to renewable/sustainable energy technologies adoption: Indian perspective , 2015 .

[10]  Chet Sandberg,et al.  The Role of Energy Storage in Development of Smart Grids , 2011, Proceedings of the IEEE.

[11]  Mohammad Yusri Hassan,et al.  Optimal distributed renewable generation planning: A review of different approaches , 2013 .

[12]  M. M. Aman,et al.  Solving Unit Commitment Problem Using Multi-agent Evolutionary Programming Incorporating Priority List , 2015 .

[13]  Florian Steinke,et al.  Grid vs. storage in a 100% renewable Europe , 2013 .

[14]  P.W. Sauer,et al.  Applying Stochastic Programming to the Unit Commitment Problem , 2008, Proceedings of the 10th International Conference on Probablistic Methods Applied to Power Systems.

[15]  I. Erlich,et al.  A Stochastic Model for the Optimal Operation of a Wind-Thermal Power System , 2009, IEEE Transactions on Power Systems.

[16]  Adrian Ilinca,et al.  Energy storage systems—Characteristics and comparisons , 2008 .

[17]  Saroj Biswas,et al.  Simultaneous solution of unit commitment and dispatch problems using artificial neural networks , 1993 .

[18]  R. Sioshansi Welfare Impacts of Electricity Storage and the Implications of Ownership Structure , 2010 .

[19]  Grzegorz Dudek,et al.  Adaptive simulated annealing schedule to the unit commitment problem , 2010 .

[20]  D. P. Kothari,et al.  Optimal thermal generating unit commitment: a review , 1998 .

[21]  A. Conejo,et al.  Decision making under uncertainty in electricity markets , 2010, 2006 IEEE Power Engineering Society General Meeting.

[22]  Amit Jain,et al.  Unit commitment with nature and biologically inspired computing , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[23]  T.O. Ting,et al.  A novel approach for unit commitment problem via an effective hybrid particle swarm optimization , 2006, IEEE Transactions on Power Systems.

[24]  Chun-Lung Chen,et al.  Optimal Wind–Thermal Generating Unit Commitment , 2008, IEEE Transactions on Energy Conversion.

[25]  B. E. Kushare,et al.  Fuzzy logic algorithm for Unit Commitment Problem , 2009, 2009 International Conference on Control, Automation, Communication and Energy Conservation.

[26]  Tomonobu Senjyu,et al.  Emerging solution of large-scale unit commitment problem by Stochastic Priority List , 2006 .

[27]  Kenneth Bruninx,et al.  Endogenous Probabilistic Reserve Sizing and Allocation in Unit Commitment Models: Cost-Effective, Reliable, and Fast , 2017, IEEE Transactions on Power Systems.

[28]  Bohumír Garlík,et al.  Renewable energy unit commitment, with different acceptance of balanced power, solved by simulated annealing , 2013 .

[29]  Prateek Kumar Singhal,et al.  Dynamic programming approach for solving power generating unit commitment problem , 2011, 2011 2nd International Conference on Computer and Communication Technology (ICCCT-2011).

[30]  Tomonobu Senjyu,et al.  Unit commitment computation by fuzzy adaptive particle swarm optimisation , 2007 .

[31]  H. Mori,et al.  Application of hybrid meta-heuristic method to unit commitment in power systems , 2008, 2008 IEEE Canada Electric Power Conference.

[32]  Derek Abbott,et al.  Addressing the Intermittency Challenge: Massive Energy Storage in a Sustainable Future [Scanning the Issue] , 2012, Proc. IEEE.

[33]  Zhengming Zhao,et al.  Grid-connected photovoltaic power systems: Technical and potential problems—A review , 2010 .

[34]  Regine Belhomme,et al.  Optimizing the flexibility of a portfolio of generating plants to deal with wind generation , 2011, 2011 IEEE Power and Energy Society General Meeting.

[35]  Ehab F. El-Saadany,et al.  Overview of wind power intermittency impacts on power systems , 2010 .

[36]  J.P.S. Catalão,et al.  Mixed-integer nonlinear approach for the optimal scheduling of a head-dependent hydro chain , 2010 .

[37]  William D'haeseleer,et al.  Optimization and allocation of spinning reserves in a low-carbon framework , 2016, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[38]  Gerald B. Sheblé,et al.  Unit commitment literature synopsis , 1994 .

[39]  Lion Hirth,et al.  Balancing power and variable renewables: Three links , 2015 .

[40]  A. Rudolf,et al.  A genetic algorithm for solving the unit commitment problem of a hydro-thermal power system , 1999 .

[41]  Javier Contreras,et al.  Unit Commitment With Ideal and Generic Energy Storage Units , 2014, IEEE Transactions on Power Systems.

[42]  Soteris A. Kalogirou,et al.  Applications of artificial neural-networks for energy systems , 2000 .

[43]  Francois Bouffard,et al.  Flexibility Envelopes for Power System Operational Planning , 2014, IEEE Transactions on Sustainable Energy.

[44]  Maurice Clerc,et al.  The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..

[45]  W. Ongsakul,et al.  Ant colony search algorithm for unit commitment , 2003, IEEE International Conference on Industrial Technology, 2003.

[46]  Martin Greiner,et al.  Seasonal optimal mix of wind and solar power in a future, highly renewable Europe , 2010 .

[47]  A. Ebenezer Jeyakumar,et al.  A tabu search based hybrid optimization approach for a fuzzy modelled unit commitment problem , 2006 .

[48]  N.P. Padhy,et al.  Unit commitment-a bibliographical survey , 2004, IEEE Transactions on Power Systems.

[49]  Ramesh C. Bansal,et al.  A review of key power system stability challenges for large-scale PV integration , 2015 .

[50]  Chu Kiong Loo,et al.  Solving Unit Commitment Problem Using Hybrid Particle Swarm Optimization , 2003, J. Heuristics.

[51]  Daniel S. Kirschen,et al.  Toward Cost-Efficient and Reliable Unit Commitment Under Uncertainty , 2016, IEEE Transactions on Power Systems.

[52]  F. Aminifar,et al.  A Novel Straightforward Unit Commitment Method for Large-Scale Power Systems , 2007, IEEE Transactions on Power Systems.

[53]  J. Painuly Barriers to renewable energy penetration; a framework for analysis , 2001 .

[54]  Majid Gandomkar,et al.  Environmental/economic scheduling of a micro-grid with renewable energy resources , 2015 .

[55]  Abraham Ellis,et al.  Understanding Variability and Uncertainty of Photovoltaics for Integration with the Electric Power System , 2009 .

[56]  A. Papalexopoulos,et al.  Optimization based methods for unit commitment: Lagrangian relaxation versus general mixed integer programming , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[57]  Benjamin F. Hobbs,et al.  The Next Generation of Electric Power Unit Commitment Models , 2013 .

[58]  D. P. Kothari,et al.  Unit commitment problem solution using invasive weed optimization algorithm , 2014 .

[59]  Russell C. Eberhart,et al.  A discrete binary version of the particle swarm algorithm , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[60]  Michael Wachendorf,et al.  Review of concepts for a demand-driven biogas supply for flexible power generation , 2014 .

[61]  Divya Ananthan,et al.  Unit Commitment Solution Using Particle Swarm Optimisation (PSO) , 2014 .

[62]  M. Shahidehpour,et al.  Price-based unit commitment: a case of Lagrangian relaxation versus mixed integer programming , 2005, IEEE Transactions on Power Systems.

[63]  A. H. Mantawy,et al.  A simulated annealing algorithm for unit commitment , 1998 .

[64]  W.L. Kling,et al.  Impacts of Wind Power on Thermal Generation Unit Commitment and Dispatch , 2007, IEEE Transactions on Energy Conversion.

[65]  Tomonobu Senjyu,et al.  A fast technique for unit commitment problem by extended priority list , 2003 .

[66]  Panida Jirutitijaroen,et al.  A Stochastic Optimization Formulation of Unit Commitment With Reliability Constraints , 2013, IEEE Transactions on Smart Grid.

[67]  A. Conejo,et al.  Economic Valuation of Reserves in Power Systems With High Penetration of Wind Power , 2009 .

[68]  Andreas Sumper,et al.  A review of energy storage technologies for wind power applications , 2012 .

[69]  Singiresu S. Rao Engineering Optimization : Theory and Practice , 2010 .

[70]  Xu Andy Sun Advances in electric power systems : robustness, adaptability, and fairness , 2011 .

[71]  Emil M. Constantinescu,et al.  Flexible Operation of Batteries in Power System Scheduling With Renewable Energy , 2016, IEEE Transactions on Sustainable Energy.

[72]  Hamidreza Zareipour,et al.  Energy storage for mitigating the variability of renewable electricity sources: An updated review , 2010 .

[73]  Michael Milligan,et al.  Design and operation of power systems with large amounts of wind power : Final report, Phase one 2006-08, IEA WIND Task 25 , 2009 .

[74]  Jing Wu,et al.  Integrating solar PV (photovoltaics) in utility system operations: Analytical framework and Arizona case study , 2015 .

[75]  Soteris A. Kalogirou,et al.  Applications of artificial neural networks in energy systems , 1999 .

[76]  Narayana Prasad Padhy,et al.  Thermal unit commitment using binary/real coded artificial bee colony algorithm , 2012 .

[77]  Kenneth Bruninx,et al.  Improved Modeling of Unit Commitment Decisions under Uncertainty , 2016 .

[78]  Arthur I. Cohen,et al.  A Branch-and-Bound Algorithm for Unit Commitment , 1983, IEEE Transactions on Power Apparatus and Systems.

[79]  Andrea Lodi,et al.  Lagrangian relaxation and Tabu Search approaches for the unit commitment problem , 2001, 2001 IEEE Porto Power Tech Proceedings (Cat. No.01EX502).

[80]  Florian Steinke,et al.  Transmission grid extensions for the integration of variable renewable energies in Europe: Who benefits where? , 2012 .

[81]  E.A. DeMeo,et al.  Utility Wind Integration and Operating Impact State of the Art , 2007, IEEE Transactions on Power Systems.

[82]  H. A. Smolleck,et al.  A fuzzy logic approach to unit commitment , 1997 .

[83]  T. Logenthiran,et al.  Particle Swarm Optimization for unit commitment problem , 2010, 2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems.

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

[85]  S. K. Soonee,et al.  Flexibility in 21st Century Power Systems , 2014 .

[86]  Nouredine Hadjsaid,et al.  Storage as a flexibility option in power systems with high shares of variable renewable energy sources: a POLES-based analysis , 2017 .

[87]  Ramesh C. Bansal,et al.  International Journal of Emerging Electric Power Systems Optimization Methods for Electric Power Systems : An Overview , 2011 .

[88]  F. Galiana,et al.  Stochastic Security for Operations Planning With Significant Wind Power Generation , 2008, IEEE Transactions on Power Systems.

[89]  Anastasios G. Bakirtzis,et al.  A genetic algorithm solution to the unit commitment problem , 1996 .

[90]  Risto Lahdelma,et al.  A variant of the dynamic programming algorithm for unit commitment of combined heat and power systems , 2008, Eur. J. Oper. Res..

[91]  Luis F. Ochoa,et al.  Evaluating and planning flexibility in sustainable power systems , 2013, 2013 IEEE Power & Energy Society General Meeting.

[92]  Ran Quan,et al.  An improved priority list and neighborhood search method for unit commitment , 2015 .

[93]  Marko Čepin,et al.  Multi-objective unit commitment with introduction of a methodology for probabilistic assessment of generating capacities availability , 2015, Eng. Appl. Artif. Intell..

[94]  Machteld van den Broek,et al.  Impacts of large-scale Intermittent Renewable Energy Sources on electricity systems, and how these can be modeled , 2014 .

[95]  Hannele Holttinen,et al.  The impact of large scale wind power production on the Nordic electricity system , 2004 .

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

[97]  Abbas A. Akhil,et al.  Batteries for Large-Scale Stationary Electrical Energy Storage , 2010 .

[98]  V. Miranda,et al.  Wind power forecasting uncertainty and unit commitment , 2011 .

[99]  Seema Singh,et al.  Multi-objective unit commitment with renewable energy using hybrid approach , 2016 .

[100]  V. Selvi,et al.  Comparative Analysis of Ant Colony and Particle Swarm Optimization Techniques , 2010 .