Multi-area market clearing in wind-integrated interconnected power systems: A fast parallel decentralized method Meysam Doostizadeh a , Farrokh Aminifar a,⇑ , Hamid Lesani a , Hassan Ghasemi b a School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran b Market and System Operations Division, Independent Electricity System Operator (IESO), Toronto, Canada article info Article history: Received 30 September 2015 Accepted 18 January 2016 Keywords: Day-ahead market clearing Distributed optimization Multi-area power system Wind power uncertainty abstract The growing evolution of regional electricity markets and proliferation of wind power penetration under- line the prominence of coordinated operation of interconnected regional power systems. This paper develops a parallel decentralized methodology for multi-area energy and reserve clearance under wind power uncertainty. Preserving the independency of regional markets while fully taking the advantages of interconnection is a salient feature of the new model. Additionally, the parallel procedure simultane- ously clears regional markets for the sake of acceleration particularly in large-scale systems. In order to achieve the optimal solution in a distributed fashion, the augmented Lagrangian relaxation along with alternative direction method of multipliers are applied. The wind power intermittency and uncertainty are tackled through the interval optimization approach. Opposed to the conventional wisdom, adjustable intervals, as subsets of conventional predefined intervals, are introduced here to compromise the cost and conservatism of the solution. The confidence level approach is employed to accommodate the stochastic nature of wind power in a computationally efficient deterministic manner. The effectiveness and robust- ness of the proposed method are evaluated through several case studies on a two-area 6-bus and the modified three-area IEEE 118-bus test systems. Ó 2016 Elsevier Ltd. All rights reserved. 1. Introduction Large-scale power systems typically consist of several intercon- nected areas each of which is an independent system with its own electricity market. Although the areas are linked together via tie- lines, each region is usually operated autonomously with very lim- ited coordination with its neighbors. Along with the integration of regional (e.g. in US) and national (e.g. in Europe) power systems as well as proliferation of intermittent and uncertain renewable ener- gies, the collaboration among electricity markets would undoubt- edly improve the overall electricity market efficiency, and system security and reliability. In order to achieve more efficient inter- changes and better convergence of prices between regions, several interregional trading projects have been carried out among U.S. electricity markets such as Interchange Optimization by PJM and MISO [1], Coordinated Transaction Scheduling between NYISO and PJM [2], and Inter-Regional Interchange Scheduling between NYISO and ISONE [3]. Ideally, coordinated multi-area market clearing problem can be centrally solved by a coordinator who has access to data of the whole system. However, managing such a massive market clearing data as well as political and technical concerns on information pri- vacy render implementation of centralized method undesirable, if possible. Several decoupling algorithms and distributed optimiza- tion methodologies have so far been presented to provide coordi- nation among multi-area interconnected systems. Ref. [4] presented a decentralized Lagrangian relaxation (LR) based algo- rithm to solve multi-area optimal power flow (OPF), in which each tie-line is modeled using two fictitious buses. In [5,6], each tie-line is divided into two lines by adding a fictitious bus at the border between two regions, then an augmented Lagrangian relaxation (ALR) procedure is applied to solve multi-area OPF. In [7], the price of electricity exchange between the areas was used to coordinate the areas and to find the solution of OPF in a decentralized manner. In [8], a hybrid direct search method was developed to solve the problem of joint energy and reserve dispatch in a multi-area com- petitive electricity market. Ref. [9] devised a dynamic multiplier based LR algorithm to solve the multi-area economic dispatch, in http://dx.doi.org/10.1016/j.enconman.2016.01.047 0196-8904/Ó 2016 Elsevier Ltd. All rights reserved. ⇑ Corresponding author at: School of Electrical and Computer Engineering, College of Engineering, University of Tehran, North Kargar Ave., Tehran 11365- 4563, Iran. Tel./fax: +98 21 88011247. E-mail addresses: m.doostizadeh@ut.ac.ir (M. Doostizadeh), faminifar@ut.ac.ir (F. Aminifar), lesani@ut.ac.ir (H. Lesani), hassan.ghasemi@ieee.org (H. Ghasemi). Energy Conversion and Management 113 (2016) 131–142 Contents lists available at ScienceDirect Energy Conversion and Management journal homepage: www.elsevier.com/locate/enconman