Global Solution Strategies for the Network-Constrained Unit Commitment Problem with AC Transmission Constraints

Liu, Jianfeng; Laird, Carl Damon; Scott, Joseph K.; Watson, Jean -Paul; Castillo, Anya

doi:10.1109/TPWRS.2018.2876127

Title: Global Solution Strategies for the Network-Constrained Unit Commitment Problem with AC Transmission Constraints

Abstract

Here, we propose a novel global solution algorithm for the network-constrained unit commitment problem that incorporates a nonlinear alternating current (AC) model of the transmission network, which is a nonconvex mixed-integer nonlinear programming (MINLP) problem. Our algorithm is based on the multi-tree global optimization methodology, which iterates between a mixed-integer lower-bounding problem and a nonlinear upper-bounding problem. We exploit the mathematical structure of the unit commitment problem with AC power flow constraints (UC-AC) and leverage second-order cone relaxations, piecewise outer approximations, and optimization-based bounds tightening to guarantee a globally optimal solution at convergence. Numerical results on four benchmark problems illustrate the effectiveness of our algorithm, both in terms of convergence rate and solution quality.

Authors:

Liu, Jianfeng ^[1]; Laird, Carl Damon ^[2]; Scott, Joseph K. ^[3]; Watson, Jean -Paul ^[2]; Castillo, Anya ^[2]

Purdue Univ., West Lafayette, IN (United States)
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Clemson Univ., Clemson, SC (United States)

Publication Date:: Wed Oct 17 00:00:00 EDT 2018

Research Org.:: Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States)

Sponsoring Org.:: USDOE National Nuclear Security Administration (NNSA)

OSTI Identifier:: 1485467

Report Number(s):: SAND-2018-11995J
Journal ID: ISSN 0885-8950; 668931

Grant/Contract Number:: AC04-94AL85000

Resource Type:: Accepted Manuscript

Journal Name:: IEEE Transactions on Power Systems

Additional Journal Information:: Journal Volume: 34; Journal Issue: 2; Journal ID: ISSN 0885-8950

Publisher:: IEEE

Country of Publication:: United States

Language:: English

Subject:: 24 POWER TRANSMISSION AND DISTRIBUTION; Optimal Power Flow; Unit Commitment; Optimization methods; Power system modeling

Citation Formats


                    Liu, Jianfeng, Laird, Carl Damon, Scott, Joseph K., Watson, Jean -Paul, and Castillo, Anya. Global Solution Strategies for the Network-Constrained Unit Commitment Problem with AC Transmission Constraints.  United States: N. p., 2018. 
Web.  doi:10.1109/TPWRS.2018.2876127.

Copy to clipboard


                    Liu, Jianfeng, Laird, Carl Damon, Scott, Joseph K., Watson, Jean -Paul, & Castillo, Anya. Global Solution Strategies for the Network-Constrained Unit Commitment Problem with AC Transmission Constraints.  United States.  https://doi.org/10.1109/TPWRS.2018.2876127

Copy to clipboard


                    Liu, Jianfeng, Laird, Carl Damon, Scott, Joseph K., Watson, Jean -Paul, and Castillo, Anya. Wed .  
"Global Solution Strategies for the Network-Constrained Unit Commitment Problem with AC Transmission Constraints".  United States.  https://doi.org/10.1109/TPWRS.2018.2876127.  https://www.osti.gov/servlets/purl/1485467.

Copy to clipboard


                    
@article{osti_1485467,

  title        = {Global Solution Strategies for the Network-Constrained Unit Commitment Problem with AC Transmission Constraints},

  author       = {Liu, Jianfeng and Laird, Carl Damon and Scott, Joseph K. and Watson, Jean -Paul and Castillo, Anya},

  abstractNote = {Here, we propose a novel global solution algorithm for the network-constrained unit commitment problem that incorporates a nonlinear alternating current (AC) model of the transmission network, which is a nonconvex mixed-integer nonlinear programming (MINLP) problem. Our algorithm is based on the multi-tree global optimization methodology, which iterates between a mixed-integer lower-bounding problem and a nonlinear upper-bounding problem. We exploit the mathematical structure of the unit commitment problem with AC power flow constraints (UC-AC) and leverage second-order cone relaxations, piecewise outer approximations, and optimization-based bounds tightening to guarantee a globally optimal solution at convergence. Numerical results on four benchmark problems illustrate the effectiveness of our algorithm, both in terms of convergence rate and solution quality.},

  doi          = {10.1109/TPWRS.2018.2876127},

  journal      = {IEEE Transactions on Power Systems},

  number       = 2,

  volume       = 34,

  place        = {United States},

  year         = {Wed Oct 17 00:00:00 EDT 2018},

  month        = {Wed Oct 17 00:00:00 EDT 2018}

}

Copy to clipboard

Journal Article:

Free Publicly Available Full Text

Accepted Manuscript (DOE)

Publisher's Version of Record

https://doi.org/10.1109/TPWRS.2018.2876127

Other availability

Search WorldCat to find libraries that may hold this journal

Citation Metrics:

Cited by: 15 works

Citation information provided by
Web of Science

Figures / Tables:

Fig. 1: High-level description of the multi-tree approach for global solution of the UC-AC MINLP problem.

All figures and tables (9 total)

Save / Share:

Export Metadata

Save to My Library

Works referencing / citing this record:

A joint energy and reserve scheduling framework based on network reliability using smart grids applications
journal, July 2019

Ansari, Javad; Malekshah, Soheil
International Transactions on Electrical Energy Systems, Vol. 29, Issue 11
DOI: 10.1002/2050-7038.12096

A Mixed-Integer Convex Programming Algorithm for Security-Constrained Unit Commitment of Power System with 110-kV Network and Pumped-Storage Hydro Units
journal, September 2019

Lin, Shunjiang; Fan, Guansheng; Lu, Yuan
Energies, Vol. 12, Issue 19
DOI: 10.3390/en12193646

Figures / Tables found in this record:

Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.

Similar Records in DOE PAGES and OSTI.GOV collections:

Mixed Integer Nonlinear Programming Approaches to Enhance Resiliency and Response Strategies in Critical Infrastructure

Technical Report Bynum, M. ; Castillo, A. ; Knueven, B. ; ...

Motivation. Critical infrastructures are large, complex engineered systems that must be operated robustly under abnormal conditions resulting from natural hazards or intentional acts. For example, electric power systems must be robust to line faults, water utilities must rapidly mitigate contamination incidents, and computing networks must adapt to adversarial intrusions to protect critical information. Problem. It is difficult for decision-makers within resiliency analysis in critical infrastructure to optimize designs and develop effective response strategies that can account for uncertainties. Facing incomplete information and the sheer scope that a natural hazard or attack vector may incorporate, response can be ineffective without reliable,more »« less
https://doi.org/10.2172/1763233

Full Text Available
An adaptive, multivariate partitioning algorithm for global optimization of nonconvex programs

Journal Article Nagarajan, Harsha ; Lu, Mowen ; Wang, Site ; ... - Journal of Global Optimization

We develop an adaptive, multivariate partitioning algorithm for solving nonconvex, Mixed-Integer Nonlinear Programs (MINLPs) with polynomial functions to global optimality. In particular, we present an iterative algorithm that exploits piecewise, convex relaxation approaches via disjunctive formulations to solve MINLPs that is different than conventional spatial branch-and-bound approaches. The algorithm partitions the domains of variables in an adaptive and non-uniform manner at every iteration to focus on productive areas of the search space. Furthermore, domain reduction techniques based on sequential, optimization-based bound-tightening and piecewise relaxation techniques, as a part of a presolve step, are integrated into the main algorithm. Finally, wemore »« less
Cited by 27
https://doi.org/10.1007/s10898-018-00734-1

Full Text Available
Security-Constrained Unit Commitment with Linearized AC Optimal Power Flow.

Journal Article Watson, Jean-Paul ; Silva Monroy, Cesar Augusto ; Castillo, Anya ; ...

We propose a mathematical programming-based approach to optimize the security-constrained unit commitment problem with a full AC transmission network representation. Our approach is based on our previously introduced successive linear programming (SLP) approach to solving the non-linear, nonconvex AC optimal power flow (ACOPF) problem. By linearizing the ACOPF, we are able to leverage powerful commercial mixed-integer solvers to iteratively optimize the combined unit commitment plus ACOPF model. We demonstrate our approach on six-bus, IEEE RTS-96, and IEEE 118-bus test systems. We perform a comparative analysis of the relative impacts of singlebus, DC, and AC transmission network models on the unitmore »« less
Full Text Available
Average Incremental Cost Pricing for the AC Unit Commitment Problem [Rev. 1]

Technical Report Garcia, Manuel Joseph ; O'Neill, Richard P.

Unit Commitment (UC) problems that consider the Alternating Current (AC) model of the transmission network have long been considered intractable to solve at scale by the power system community. Recently, the Grid-Optimization (GO) Competition held by the Advanced Research Project Agency-Energy (ARPA-E) has facilitated the development of the first algorithms to solve large-scale ACUC problems. This new capability opens a path towards the explicit consideration of the AC transmission network model in UC problems used to clear day-ahead electricity markets. This calls for the analysis of electricity market structures that accommodate both the continuous non-linearity of the AC transmission networkmore »« less
https://doi.org/10.2172/2282521

Full Text Available
The allocation of a variable series reactor considering AC constraints and contingencies

Journal Article Zhang, Xiaohu ; Xu, Chunlei ; Shi, Di ; ... - CSEE Journal of Power and Energy Systems

The Variable Series Reactors (VSRs) can efficiently control the power flow through the adjustment of the line reactance. When they are appropriately allocated in the power network, the transmission congestion and generation cost can be reduced. Our work proposes a planning model to optimally allocate VSRs considering AC constraints and multi-scenarios including base case and contingencies. The planning model is originally a non-convex large scale mixed integer nonlinear program (MINLP), which is generally intractable. The proposed Benders approach decomposes the MINLP model into a mixed integer linear program (MILP) master problem and a number of nonlinear subproblems. Numerical case studiesmore »« less
Cited by 3
https://doi.org/10.17775/CSEEJPES.2017.00400

Full Text Available

Similar Records

Title: Global Solution Strategies for the Network-Constrained Unit Commitment Problem with AC Transmission Constraints

Abstract

Citation Formats

Figures / Tables:

A joint energy and reserve scheduling framework based on network reliability using smart grids applications journal, July 2019

A Mixed-Integer Convex Programming Algorithm for Security-Constrained Unit Commitment of Power System with 110-kV Network and Pumped-Storage Hydro Units journal, September 2019

A joint energy and reserve scheduling framework based on network reliability using smart grids applications
journal, July 2019

A Mixed-Integer Convex Programming Algorithm for Security-Constrained Unit Commitment of Power System with 110-kV Network and Pumped-Storage Hydro Units
journal, September 2019