A Mixed-Integer Linear Programming Approach to Security-Constrained Co-Optimization Expansion Planning of Natural Gas and Electricity Transmission Systems

As the rapid development of natural-gas fired units (NGUs), power systems begin to rely more on a natural gas system to supply the primary fuel. On the other hand, natural gas system contingency might cause the nonavailability of NGUs and inevitably jeopardize power system security. To address this...

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Bibliographic Details
Published in:IEEE transactions on power systems Vol. 33; no. 6; pp. 6368 - 6378
Main Authors: Zhang, Yao, Hu, Yuan, Ma, Jin, Bie, Zhaohong
Format: Journal Article
Language:English
Published: New York IEEE 01.11.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Combinatorial analysis
Compressors
Computational modeling
Constraints
Contingency
Continuity (mathematics)
Electric power systems
Electric power transmission
Electricity
Expansion joints
Integer programming
Integrated energy systems
Linear programming
Linearization
Mathematical models
Mixed integer linear programming
mixed-integer linear programming (MILP)
N-1 criterion
Natural gas
natural gas system
Optimization
Pipelines
Power system planning
reduced disjunctive model
Security
transmission expansion planning (TEP)
ISSN:0885-8950, 1558-0679
Online Access:Get full text
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Summary:As the rapid development of natural-gas fired units (NGUs), power systems begin to rely more on a natural gas system to supply the primary fuel. On the other hand, natural gas system contingency might cause the nonavailability of NGUs and inevitably jeopardize power system security. To address this issue, this paper studies security-constrained joint expansion planning problems for this combined energy system. We develop a computationally efficient mixed-integer linear programming (MILP) approach that simultaneously considers N-1 contingency in both natural gas system and electricity power system. To reduce the combinatorial search space of MILP models, an extension of a reduced disjunctive model is proposed to decrease the numbers of binary and continuous variables as well as constraints. The involving nonlinear terms in N-1 constraints are exactly linearized without sacrificing any optimality. Numerical results on two typical integrated energy systems demonstrate the necessity of extending N-1 criterion to the whole network of a combined energy system. Experimental results also show that compared with the conventional approach, our proposed MILP approach achieves a great computational performance improvement in solving security-constrained co-optimization expansion planning problems.
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ISSN:0885-8950
1558-0679
DOI:10.1109/TPWRS.2018.2832192