Incorporating unit commitment aspects to the European electricity markets algorithm: An optimization model for the joint clearing of energy and reserve markets

Abstract The European electricity markets’ integration aims at the market coupling among interconnected power systems and the enhancement of market competitive forces. This process is facilitated by the adoption of a common clearing algorithm among European power exchanges, entitled EUPHEMIA (Pan-European Hybrid Electricity Market Integration Algorithm), which however lacks to capture critical technical aspects of power systems, as done by the unit commitment problem including start-up and shut-down decisions, time constraints (minimum on- and off-times), as well as the consideration of ancillary services. This paper presents an optimization-based framework for the optimal joint energy and reserves market clearing algorithm, further utilizing the hourly offers module of the EUPHEMIA algorithm. In particular, through the formulation of a mixed integer linear programming (MILP) model and employing an iterative approach, it determines the optimal energy and reserves mix, the resulting market clearing prices, and it calculates the welfares of the market participants. The model incorporates intra-hourly power reserve constraints, as well as introduces new market products such as the option of forming linked groups of power units, aiming at supplying additional flexibility in the decision-making of the market participants. The model applicability has been assessed in the Greek power system and its interconnections with neighboring power systems in Southeast Europe. The proposed optimization framework can provide useful insights on the determination of the optimal generation and interconnection portfolios that address the new market-based operational challenges of contemporary power systems subject to technical and economic constraints.

[1]  Nikolaos E. Koltsaklis,et al.  A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints , 2015 .

[2]  Muireann Á. Lynch,et al.  Competition and the single electricity market: Which lessons for Ireland? , 2016 .

[3]  Pandelis N. Biskas,et al.  Market coupling feasibility between a power pool and a power exchange , 2013 .

[4]  Goran Strbac,et al.  The benefits of integrating European electricity markets , 2016 .

[5]  D. Newbery Missing Money and Missing Markets: Reliability, Capacity Auctions and Interconnectors , 2015 .

[6]  Fehmi Tanrisever,et al.  Organization and functioning of liberalized electricity markets: An overview of the Dutch market , 2015 .

[7]  Shoki Kosai,et al.  Quantitative analysis on the impact of nuclear energy supply disruption on electricity supply security , 2017 .

[8]  Julio Usaola,et al.  An optimal day-ahead load scheduling approach based on the flexibility of aggregate demands , 2017 .

[9]  Ronnie Belmans,et al.  Block order restrictions in combinatorial electric energy auctions , 2009, Eur. J. Oper. Res..

[10]  Patrícia Pereira da Silva,et al.  Evaluating the market splitting determinants: evidence from the Iberian spot electricity prices , 2015 .

[11]  Grigoris A. Dourbois,et al.  Comparison of two mathematical programming models for the solution of a convex portfolio-based European day-ahead electricity market , 2016 .

[12]  Ross Baldick,et al.  Power-Capacity and Ramp-Capability Reserves for Wind Integration in Power-Based UC , 2016, IEEE Transactions on Sustainable Energy.

[13]  Lilian M. de Menezes,et al.  Germany's nuclear power plant closures and the integration of electricity markets in Europe , 2015 .

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

[15]  Antonio Vicino,et al.  A new approach to electricity market clearing with uniform purchase price and curtailable block orders , 2017, Applied Energy.

[16]  Yi-Ming Wei,et al.  Global transition to low-carbon electricity: A bibliometric analysis , 2017 .

[17]  Alex D. Papalexopoulos,et al.  High-level design for the compliance of the Greek wholesale electricity market with the Target Model provisions in Europe , 2017 .

[18]  David Raisz,et al.  Integrated mathematical model for uniform purchase prices on multi-zonal power exchanges , 2017 .

[19]  T. Jamasb,et al.  Interconnections and market integration in the Irish Single Electricity Market , 2012 .

[20]  Michael C. Georgiadis,et al.  A mid-term, market-based power systems planning model , 2016 .

[21]  David M Newbery,et al.  Tales of two islands – Lessons for EU energy policy from electricity market reforms in Britain and Ireland , 2017 .

[22]  Zita Vale,et al.  Multi-agent simulation of competitive electricity markets: Autonomous systems cooperation for European market modeling , 2015 .

[23]  Ioannis P. Panapakidis,et al.  An integrated model for risk management in electricity trade , 2017 .

[24]  Adam Hawkes,et al.  The value of electricity and reserve services in low carbon electricity systems , 2017 .

[25]  Bart De Schutter,et al.  Forecasting day-ahead electricity prices in Europe: the importance of considering market integration , 2017, ArXiv.

[26]  David Raisz,et al.  Complex supply orders with ramping limitations and shadow pricing on the all-European day-ahead electricity market , 2016 .

[27]  Alexander Martin,et al.  On the long run effects of market splitting: Why more price zones might decrease welfare , 2016 .

[28]  Nikolaos E. Koltsaklis,et al.  A stochastic MILP energy planning model incorporating power market dynamics , 2017 .

[29]  Brian Ó Gallachóir,et al.  An integrated gas and electricity model of the EU energy system to examine supply interruptions , 2017 .

[30]  Ruediger Kiesel,et al.  Structural Models for Coupled Electricity Markets , 2015 .

[31]  Michael C. Georgiadis,et al.  An integrated stochastic multi-regional long-term energy planning model incorporating autonomous power systems and demand response , 2015 .

[32]  Valentin Ilea,et al.  European day-ahead electricity market coupling: Discussion, modeling, and case study , 2018 .

[33]  Mehdi Madani,et al.  Revisiting minimum profit conditions in uniform price day-ahead electricity auctions , 2015, Eur. J. Oper. Res..

[34]  Mehdi Madani,et al.  Computationally efficient MIP formulation and algorithms for European day-ahead electricity market auctions , 2015, Eur. J. Oper. Res..