Constructive heuristic algorithm for the DC model in network transmission expansion planning

Romero, Rubén; Rocha, Caroline; Mantovani, José Roberto Sanches; Sánchez, Ismael

doi:10.1049/ip-gtd:20041196

Cited by 110 publications

(101 citation statements)

References 8 publications

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“…288 , 2 3 ≈ . Finally, these results also compare favorably with the ones reported in [23,24] namely considering the investment cost reported in these papers for similar running conditions.…”

Section: Single Period Analysissupporting

confidence: 79%

Transmission Expansion Planning – A Multiyear Dynamic Approach Using a Discrete Evolutionary Particle Swarm Optimization Algorithm

Rocha

Saraiva

2012

EPJ Web of Conferences

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Abstract. The basic objective of Transmission Expansion Planning (TEP) is to schedule a number of transmission projects along an extended planning horizon minimizing the network construction and operational costs while satisfying the requirement of delivering power safely and reliably to load centres along the horizon. This principle is quite simple, but the complexity of the problem and the impact on society transforms TEP on a challenging issue. This paper describes a new approach to solve the dynamic TEP problem, based on an improved discrete integer version of the Evolutionary Particle Swarm Optimization (EPSO) meta-heuristic algorithm. The paper includes sections describing in detail the EPSO enhanced approach, the mathematical formulation of the TEP problem, including the objective function and the constraints, and a section devoted to the application of the developed approach to this problem. Finally, the use of the developed approach is illustrated using a case study based on the IEEE 24 bus 38 branch test system.

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Section: Single Period Analysissupporting

confidence: 79%

Transmission Expansion Planning – A Multiyear Dynamic Approach Using a Discrete Evolutionary Particle Swarm Optimization Algorithm

Rocha

Saraiva

2012

EPJ Web of Conferences

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“…4 Even in commercial optimization softwares with mixed integer linear programming (MILP) capability, termination of the algorithm is not automatic; rather, it is controlled by a user-defined parameter. 5 The solution process terminates when the best known feasible solution is within a specified range from the bound on the optimal. This bound on the optimal is also internally evaluated by the solver.…”

Section: A Implication Of Tep Problem Being Np-hardmentioning

confidence: 99%

“…The termination criteria is controlled by parameter . The program terminates when cost of the feasible solution satisfies the following criterion: (5) where is the best bound calculated by the solver on the cost of optimal solution. As can be seen from the results, as is reduced, the computational effort increases rapidly, illustrating the intractability of the optimization version of TEP problem.…”

Section: A Implication Of Tep Problem Being Np-hardmentioning

confidence: 99%

An Expert System Approach for Multi-Year Short-Term Transmission System Expansion Planning: An Indian Experience

Gajbhiye

Naik

Dambhare

et al. 2008

IEEE Trans. Power Syst.

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Abstract-This paper proposes an expert system approach to short-term expansion planning (STEP). The rules which drive STEP can be classified into MW, MVAR, and ampacity management rules. MW and ampacity management rules are for alleviating transmission line congestion. Reactive power management is required for voltage control at load busses, conformity to the capacity curve of the generators, and containing the MW losses within acceptable limits. Embedding reactive power management in STEP is a challenging task since ac load flow may not converge in absence of proper reactive power planning and load modeling. Therefore, we also propose enhancements to the fast decoupled load flow algorithm for on-the-fly reactive power management. The enhanced algorithm not only can detect divergent load flow scenarios but also self-correct it by restarting the whole process with greater degree of freedom in reactive power controls. The proposed approach leads to development of an automated tool for STEP which has the capability to work, even with incomplete information. A simple method for evaluating location and requirement of shunt reactor is also proposed. By analysis and comparative evaluation, we show that the proposed system can arrive at a solution which is close to optimal. Results on the Western Regional Grid of India with an approximate load of 28 000 MW and 1200 nodes are presented to demonstrate effectiveness of the proposed approach.Index Terms-Congestion, contingency, fast decoupled load flow (FDLF), reactive power compensation (RPC), short-term transmission expansion planning (STEP).

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“…As long as the problem is convex, the methods can return a global optimal plan, however with high computational time, especially in case of large-scale problems. On the other hand, the heuristic based methods [3,4,5] utilize some guidelines for searching solutions. For the TEP problem, they are usually derived from sensitivity indices regarding potential of candidates to alleviate the violation of operating limits.…”

Section: Introductionmentioning

confidence: 99%

Multistage Transmission Expansion Planning Using Local Branching Method

Asadamongkol

Eua‐arporn

2010

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This paper proposes a method for solving a large-scale multistage transmission expansion planning problem. The formulated problem is of a large-scale mixed integer linear programming which is difficult to handle by general mathematical optimization techniques. A disjunctive model for a single stage transmission expansion planning is extended for solving the multistage model. In addition, a local branching method is employed with an initial solution obtained from the single stage transmission expansion planning problem. The proposed method has been tested with IEEE 24-bus and a northeastern Thailand power system to show it is efficient to implement for actual power system planning. KEYWORDSdisjunctive model, local branching method, mixed integer linear programming, multistage transmission expansion planning.

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Constructive heuristic algorithm for the DC model in network transmission expansion planning

Cited by 110 publications

References 8 publications

Transmission Expansion Planning – A Multiyear Dynamic Approach Using a Discrete Evolutionary Particle Swarm Optimization Algorithm

Transmission Expansion Planning – A Multiyear Dynamic Approach Using a Discrete Evolutionary Particle Swarm Optimization Algorithm

An Expert System Approach for Multi-Year Short-Term Transmission System Expansion Planning: An Indian Experience

Multistage Transmission Expansion Planning Using Local Branching Method

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