Hydropower bidding in a multi-market setting

We present a literature survey and research gap analysis of mathematical and statistical methods used in the context of optimizing bids in electricity markets. Particularly, we are interested in methods for hydropower producers that participate in multiple, sequential markets for short-term delivery of physical power. As most of the literature focus on day-ahead bidding and thermal energy producers, there are important research gaps for hydropower, which require specialized methods due to the fact that electricity may be stored as water in reservoirs. Our opinion is that multi-market participation, although reportedly having a limited profit potential, can provide gains in flexibility and system stability for hydro producers. We argue that managing uncertainty is of key importance for making good decision support tools for the multi-market bidding problem. Considering uncertainty calls for some form of stochastic programming, and we define a modelling process that consists of three interconnected tasks; mathematical modelling, electricity price forecasting and scenario generation. We survey research investigating these tasks and point out areas that are not covered by existing literature.

[1]  Michel Gendreau,et al.  Optimizing profits from hydroelectricity production , 2009, Comput. Oper. Res..

[2]  Y. Larsson,et al.  Incremental Cost of Water Power , 1961, Transactions of the American Institute of Electrical Engineers. Part III: Power Apparatus and Systems.

[3]  K. Mosler,et al.  Can Markov regime-switching models improve power-price forecasts? Evidence from German daily power prices , 2006 .

[4]  Michal Kaut,et al.  A copula-based heuristic for scenario generation , 2014, Comput. Manag. Sci..

[5]  M. V. F. Pereira,et al.  Multi-stage stochastic optimization applied to energy planning , 1991, Math. Program..

[6]  Florentina Paraschiv,et al.  Econometric Analysis of 15-Minute Intraday Electricity Prices , 2016 .

[7]  Edward J. Anderson,et al.  Using Supply Functions for Offering Generation into an Electricity Market , 2002, Oper. Res..

[8]  G. Dantzig,et al.  Stochastic programming : the state of the art : in honor of George B. Dantzig , 2011 .

[9]  Stein-Erik Fleten,et al.  Stochastic programming for optimizing bidding strategies of a Nordic hydropower producer , 2007, Eur. J. Oper. Res..

[10]  J. Lindqvist,et al.  Operation of a Hydrothermal Electric System: A Multistage Decision Process , 1962, Transactions of the American Institute of Electrical Engineers. Part III: Power Apparatus and Systems.

[11]  Werner Römisch,et al.  Scenario tree modeling for multistage stochastic programs , 2009, Math. Program..

[12]  Izeddine Zorkani,et al.  Valuation of energy storage in energy and regulation markets , 2016 .

[13]  L. Soder,et al.  Modeling Real-Time Balancing Power Market Prices Using Combined SARIMA and Markov Processes , 2008, IEEE Transactions on Power Systems.

[14]  W. Römisch,et al.  Scenario tree modelling for multistage stochastic programs , 2006 .

[15]  Ove Wolfgang,et al.  Hydro reservoir handling in Norway before and after deregulation , 2009 .

[16]  Daniel De Ladurantaye,et al.  Strategic Bidding for Price-Taker Hydroelectricity Producers , 2007, IEEE Transactions on Power Systems.

[17]  Asgeir Tomasgard,et al.  Integration of Wind Power Production in a Conventional Power Production System: Stochastic Models and Performance Measures , 2013 .

[18]  Werner Römisch,et al.  Scenario Tree Generation for Multi-stage Stochastic Programs , 2011 .

[19]  Werner Römisch,et al.  Stability of Multistage Stochastic Programs , 2006, SIAM J. Optim..

[20]  Marco van Akkeren,et al.  A GARCH forecasting model to predict day-ahead electricity prices , 2005, IEEE Transactions on Power Systems.

[21]  Xiuli Qu,et al.  Modeling methods for GenCo bidding strategy optimization in the liberalized electricity spot market , 2011 .

[22]  Charles Audet,et al.  Stochastic short-term hydropower planning with inflow scenario trees , 2017, Eur. J. Oper. Res..

[23]  Nina Juul,et al.  Bidding in sequential electricity markets: The Nordic case , 2014, Eur. J. Oper. Res..

[24]  Georg Ch. Pflug,et al.  From Empirical Observations to Tree Models for Stochastic Optimization: Convergence Properties , 2016, SIAM J. Optim..

[25]  M. Nielsen,et al.  A Regime Switching Long Memory Model for Electricity Prices , 2006 .

[26]  H. Madsen,et al.  Forecasting Electricity Spot Prices Accounting for Wind Power Predictions , 2013, IEEE Transactions on Sustainable Energy.

[27]  Eduardo Faria,et al.  Day-ahead market bidding for a Nordic hydropower producer: taking the Elbas market into account , 2011, Comput. Manag. Sci..

[28]  David P. Morton,et al.  Assessing solution quality in stochastic programs , 2006, Algorithms for Optimization with Incomplete Information.

[29]  Jitka Dupacová,et al.  Scenarios for Multistage Stochastic Programs , 2000, Ann. Oper. Res..

[30]  L. Soder,et al.  Modeling Swedish real-time balancing power prices using nonlinear time series models , 2010, 2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems.

[31]  Philip Gray,et al.  A New Approach to Characterizing and Forecasting Electricity Price Volatility , 2008 .

[32]  Javad Khazaei,et al.  Production inefficiency of electricity markets with hydro generation , 2010 .

[33]  G. Pritchard,et al.  Hydroelectric reservoir optimization in a pool market , 2005, Math. Program..

[34]  Hans Ivar Skjelbred,et al.  Optimizing day-ahead bid curves in hydropower production , 2018 .

[35]  Stein-Erik Fleten,et al.  Bidding hydropower generation: Integrating short- and long-term scheduling , 2011 .

[36]  R. Weron Electricity price forecasting: A review of the state-of-the-art with a look into the future , 2014 .

[37]  Christian Küchler,et al.  On Stability of Multistage Stochastic Programs , 2008, SIAM J. Optim..

[38]  Stefan Minner,et al.  Optimizing Trading Decisions for Hydro Storage Systems Using Approximate Dual Dynamic Programming , 2013, Oper. Res..

[39]  Alan J. King,et al.  Modeling with Stochastic Programming , 2012 .

[40]  Stein-Erik Fleten,et al.  Evaluating a Stochastic-Programming-Based Bidding Model for a Multireservoir System , 2014, IEEE Transactions on Power Systems.

[41]  Michal Kaut,et al.  Evaluation of scenario-generation methods for stochastic programming , 2007 .

[42]  Aidong Yang,et al.  Handbook of Power Systems , 2010 .

[43]  Narayanan Kumarappan,et al.  Day-Ahead Deregulated Electricity Market Price Forecasting Using Recurrent Neural Network , 2013, IEEE Systems Journal.

[44]  David P. Morton,et al.  Simulation-Based Optimality Tests for Stochastic Programs , 2010 .

[45]  M. Kaut Forecast-based scenario-tree generation method , 2017 .

[46]  J. Contreras,et al.  Forecasting electricity prices for a day-ahead pool-based electric energy market , 2005 .

[47]  Olav Bjarte Fosso,et al.  Optimal bidding in sequential physical markets — A literature review and framework discussion , 2013, 2013 IEEE Grenoble Conference.

[48]  Stein-Erik Fleten,et al.  Benchmarking time series based forecasting models for electricity balancing market prices , 2015 .

[49]  A. Tomasgard,et al.  Stochastic model for short-term balancing of supply and consumption of electricity , 2015 .

[50]  Stein-Erik Fleten,et al.  A spot-forward model for electricity prices with regime shifts , 2015 .

[51]  Steffen Rebennack,et al.  Optimal Bidding Strategies for Hydro-Electric Producers: A Literature Survey , 2014, IEEE Transactions on Power Systems.

[52]  A. Gjelsvik,et al.  Long- and Medium-term Operations Planning and Stochastic Modelling in Hydro-dominated Power Systems Based on Stochastic Dual Dynamic Programming , 2010 .

[53]  Peng Wang,et al.  Descriptive Models for Reserve and Regulation Prices in Competitive Electricity Markets , 2014, IEEE Transactions on Smart Grid.

[54]  Magnus Olsson,et al.  On optimal hydropower bidding in systems with wind power , 2009 .

[55]  Michal Kaut,et al.  A Heuristic for Moment-Matching Scenario Generation , 2003, Comput. Optim. Appl..

[56]  W. Ziemba,et al.  The Effect of Errors in Means, Variances, and Covariances on Optimal Portfolio Choice , 1993 .

[57]  Georg Ch. Pflug,et al.  Version-Independence and Nested Distributions in Multistage Stochastic Optimization , 2009, SIAM J. Optim..

[58]  Ning Lu,et al.  Pumped-storage hydro-turbine bidding strategies in a competitive electricity market , 2004, IEEE Transactions on Power Systems.

[59]  Patrizia Beraldi,et al.  Optimal capacity allocation in multi-auction electricity markets under uncertainty , 2005, Comput. Oper. Res..

[60]  T. Kristiansen Forecasting Nord Pool day-ahead prices with an autoregressive model , 2012 .

[61]  S. Yakowitz Dynamic programming applications in water resources , 1982 .

[62]  Georg Ch. Pflug,et al.  Dynamic generation of scenario trees , 2015, Computational Optimization and Applications.

[63]  Michal Kaut,et al.  Multi-horizon stochastic programming , 2014, Comput. Manag. Sci..

[64]  P. Luh,et al.  Improving market clearing price prediction by using a committee machine of neural networks , 2004, IEEE Transactions on Power Systems.