scholarly journals A Long-Term Evaluation on Transmission Line Expansion Planning with Multistage Stochastic Programming

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 1899 ◽  
Author(s):  
Sini Han ◽  
Hyeon-Jin Kim ◽  
Duehee Lee
Keyword(s):  
Stochastic Programming ◽  
Transmission Line ◽  
Transmission Lines ◽  
Mixed Integer ◽  
Planning Problem ◽  
Multistage Stochastic Programming ◽  
Dual Decomposition ◽  
Expansion Planning ◽  
Integer Variables ◽  
Progressive Hedging

The purpose of this paper is to apply multistage stochastic programming to the transmission line expansion planning problem, especially when uncertain demand scenarios exist. Since the problem of transmission line expansion planning requires an intensive computational load, dual decomposition is used to decompose the problem into smaller problems. Following this, progressive hedging and proximal bundle methods are used to restore the decomposed solutions to the original problems. Mixed-integer linear programming is involved in the problem to decide where new transmission lines should be constructed or reinforced. However, integer variables in multistage stochastic programming (MSSP) are intractable since integer variables are not restored. Therefore, the branch-and-bound algorithm is applied to multistage stochastic programming methods to force convergence of integer variables.In addition, this paper suggests combining progressive hedging and dual decomposition in stochastic integer programming by sharing penalty parameters. The simulation results tested on the IEEE 30-bus system verify that our combined model sped up the computation and achieved higher accuracy by achieving the minimised cost.

scholarly journals Transmission Network Expansion Planning Considering Phase-Shifter Transformers

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Celso T. Miasaki ◽  
Edgar M. C. Franco ◽  
Ruben A. Romero
Keyword(s):  
Mathematical Model ◽  
Transmission Lines ◽  
Phase Shifter ◽  
Planning Process ◽  
Main Idea ◽  
Mixed Integer ◽  
Planning Problem ◽  
Transmission Network ◽  
Network Expansion ◽  
Expansion Planning

This paper presents a novel mathematical model for the transmission network expansion planning problem. Main idea is to consider phase-shifter (PS) transformers as a new element of the transmission system expansion together with other traditional components such as transmission lines and conventional transformers. In this way, PS are added in order to redistribute active power flows in the system and, consequently, to diminish the total investment costs due to new transmission lines. Proposed mathematical model presents the structure of a mixed-integer nonlinear programming (MINLP) problem and is based on the standard DC model. In this paper, there is also applied a specialized genetic algorithm aimed at optimizing the allocation of candidate components in the network. Results obtained from computational simulations carried out with IEEE-24 bus system show an outstanding performance of the proposed methodology and model, indicating the technical viability of using these nonconventional devices during the planning process.

Transmission Network Expansion Planning Considering Optimal Allocation of Series Capacitive Compensation and Active Power Losses

2021 ◽  
Vol 12 (1) ◽  
pp. 388
Author(s):  
Dany H. Huanca ◽  
Luis A. Gallego ◽  
Jesús M. López-Lezama
Keyword(s):  
Genetic Algorithm ◽  
Test System ◽  
Active Power ◽  
Mixed Integer ◽  
Planning Problem ◽  
Transmission Network ◽  
Power Losses ◽  
Network Expansion ◽  
Expansion Planning ◽  
Active Power Losses

This paper presents a modeling and solution approach to the static and multistage transmission network expansion planning problem considering series capacitive compensation and active power losses. The transmission network expansion planning is formulated as a mixed integer nonlinear programming problem and solved through a highly efficient genetic algorithm. Furthermore, the Villasana Garver’s constructive heuristic algorithm is implemented to render the configurations of the genetic algorithm feasible. The installation of series capacitive compensation devices is carried out with the aim of modifying the reactance of the original circuit. The linearization of active power losses is done through piecewise linear functions. The proposed model was implemented in C++ language programming. To show the applicability and effectiveness of the proposed methodology several tests are performed on the 6-bus Garver system, the IEEE 24-bus test system, and the South Brazilian 46-bus test system, presenting costs reductions in their multi-stage expansion planning of 7.4%, 4.65% and 1.74%, respectively.

scholarly journals Co-Optimized Analysis and Design of Electric and Natural Gas Infrastructures

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 2012 ◽  
Author(s):  
Santiago Lemos-Cano ◽  
James McCalley
Keyword(s):  
Natural Gas ◽  
Transmission Lines ◽  
Power Flow ◽  
Planning Process ◽  
The United States ◽  
Integrated System ◽  
Mixed Integer ◽  
Eastern Region ◽  
Analysis And Design ◽  
Expansion Planning

This paper proposes and implements a long-term deterministic capacity expansion model for the co-optimization of electric and natural gas infrastructures. It determines the required investments in generation units, transmission lines and pipelines for meeting future demands, while representing electricity and natural gas flows using DC Power Flow and Weymouth equations, respectively. A Mixed Integer Nonlinear Programming (MINLP) problem is developed, from which a linearized version is derived. A 26 node integrated gas-electric system for the Eastern Region of the United States is used to demonstrate the model’s capabilities. Results show that the model provides an accurate operational representation of the integrated system, and, therefore, enhances the expansion planning process.

Security Constrained Economic Dispatch

2012 ◽  
pp. 306-321
Author(s):  
Lizhi Wang ◽  
Nan Kong
Keyword(s):  
Power System ◽  
Transmission Line ◽  
Electric Power ◽  
Transmission Lines ◽  
High Reliability ◽  
Low Cost ◽  
Load Shedding ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Markov Decision

The main objective of electric power dispatch is to provide electricity to the customers at low cost and high reliability. Transmission line failures constitute a great threat to the electric power system security. We use a Markov decision process (MDP) approach to model the sequential dispatch decision making process where demand level and transmission line availability change from hour to hour. The action space is defined by the electricity network constraints. Risk of the power system is the loss of transmission lines, which could cause involuntary load shedding or cascading failures. The objective of the model is to minimize the expected long-term discounted cost (including generation, load shedding, and cascading failure costs). Policy iteration can be used to solve this model. At the policy improvement step, a stochastic mixed integer linear program is solved to obtain the optimal action. We use a PJM network example to demonstrate the effectiveness of our approach.

scholarly journals An Extreme Scenario Method for Robust Transmission Expansion Planning with Wind Power Uncertainty

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2116 ◽  
Author(s):  
Zipeng Liang ◽  
Haoyong Chen ◽  
Xiaojuan Wang ◽  
Idris Ibn Idris ◽  
Bifei Tan ◽  
...  
Keyword(s):  
Wind Power ◽  
Transmission Lines ◽  
Benders Decomposition ◽  
Electrical Power ◽  
Mixed Integer ◽  
Two Stage ◽  
Operating Variables ◽  
Expansion Planning ◽  
Power Resources ◽  
Bus System

The rapid incorporation of wind power resources in electrical power networks has significantly increased the volatility of transmission systems due to the inherent uncertainty associated with wind power. This paper addresses this issue by proposing a transmission network expansion planning (TEP) model that integrates wind power resources, and that seeks to minimize the sum of investment costs and operation costs while accounting for the costs associated with the pollution emissions of generator infrastructure. Auxiliary relaxation variables are introduced to transform the established model into a mixed integer linear programming problem. Furthermore, the novel concept of extreme wind power scenarios is defined, theoretically justified, and then employed to establish a two-stage robust TEP method. The decision-making variables of prospective transmission lines are determined in the first stage, so as to ensure that the operating variables in the second stage can adapt to wind power fluctuations. A Benders’ decomposition algorithm is developed to solve the proposed two-stage model. Finally, extensive numerical studies are conducted with Garver’s 6-bus system, a modified IEEE RTS79 system and IEEE 118-bus system, and the computational results demonstrate the effectiveness and practicability of the proposed method.

Optimal capacity utilisation of transmission lines network in power flow operations: a survey

2019 ◽  
Vol 17 (5) ◽  
pp. 1056-1076
Author(s):  
Daniel Esene Okojie ◽  
Adisa Abdul-Ganiyu Jimoh ◽  
Yskandar Hamam ◽  
Adebayo Ademola Yusuff
Keyword(s):  
Transmission Line ◽  
Transmission Lines ◽  
Power Flow ◽  
Network Capacity ◽  
Mixed Integer ◽  
Reserve Capacity ◽  
Capacity Utilisation ◽  
Content Type ◽  
Optimal Capacity ◽  
Line Switching

Purpose This paper aims to survey the need for full capacity utilisation of transmission lines in power systems network operations. It proposes a review of the N-1 security criterion that does not ensure reliable dispatch of optimum power flow during outage contingency. The survey aims to enlarge the network capacity utilisation to rely on the entire transmission lines network operation. Design/methodology/approach The paper suggests transmission line switching (TLS) approach as a viable corrective mechanism for power dispatch. The TLS process is incorporated into a constraint programming language extension optimisation solver that selects the switchable line candidates as integer variables in the mixed integer programming problem. Findings The paper provides a practical awareness of reserve capacity in the lines that provide network security in outage contingency. At optimum power flow dispatch, the TLS is extended to optimal transmission line switching (OTLS) that indicates optimal capacity utilisation (OCU) of the available reserve capacity (ARC) in the network lines. Practical implications Computational efficiency influenced the extension of the OTLS to optimal transmission switching of power flow (OTSPF). The application of OTSPF helps reduce the use of flexible AC transmission systems (FACTS) and construction of new transmission lines.. Originality/value The paper surveys TLS efforts in network capacity utilisation. The suggested ARC fulfils the need for an index with which the dispatchable lines may be identified for the optimal capacity utilisation of transmission lines network.

scholarly journals Multiaircraft Optimal 4D Trajectory Planning Using Logical Constraints

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Dinesh B. Seenivasan ◽  
Alberto Olivares ◽  
Ernesto Staffetti
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Control Problem ◽  
Obstacle Avoidance ◽  
Trajectory Planning ◽  
Model Complexity ◽  
Mixed Integer ◽  
Planning Problem ◽  
Integer Variables ◽  
Logical Constraints

This paper studies the trajectory planning problem for multiple aircraft with logical constraints in disjunctive form which arise in modeling passage through waypoints, distance-based and time-based separation constraints, decision-making processes, conflict resolution policies, no-fly zones, or obstacle or storm avoidance. Enforcing separation between aircraft, passage through waypoints, and obstacle avoidance is especially demanding in terms of modeling efforts. Indeed, in general, separation constraints require the introduction of auxiliary integer variables in the model; for passage constraints, a multiphase optimal control approach is used, and for obstacle avoidance constraints, geometric approximations of the obstacles are introduced. Multiple phases increase model complexity, and the presence of integer variables in the model has the drawback of combinatorial complexity of the corresponding mixed-integer optimal control problem. In this paper, an embedding approach is employed to transform logical constraints in disjunctive form into inequality and equality constraints which involve only continuous auxiliary variables. In this way, the optimal control problem with logical constraints is converted into a smooth optimal control problem which is solved using traditional techniques, thereby reducing the computational complexity of finding the solution. The effectiveness of the approach is demonstrated through several numerical experiments by computing the optimal trajectories of multiple aircraft in converging and intersecting arrival routes with time-based separation constraints, distance-based separation constraints, and operational constraints.

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