Application of computer software in transmission expansion planning using variable load structure

Chanda, Rupsa; Bhattacharjee, Prasun

doi:10.1016/0378-7796(94)90024-8

Cited by 20 publications

(5 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Constraints in (13) guarantee the power flow at each line do not exceed the maximum allowed level. Constraints in (14) represent the generating units operating capacity and constraints in (15) and (16) indicate the fictitious generation limit and the maximum allowed number of circuits from bus i to bus j, respectively.…”

Section: Multiyear Tep Problem Formulationmentioning

confidence: 99%

See 1 more Smart Citation

Transmission expansion planning using multivariate interpolation

Mortaz

Fuerte-Ledezma

Gutiérrez-Alcaraz

et al. 2015

Electric Power Systems Research

View full text Add to dashboard Cite

Section: Multiyear Tep Problem Formulationmentioning

confidence: 99%

“…Several mathematical methods such as linear programming [15][16][17], dynamic programming [18], nonlinear programming [19], and mixed integer programming [20] have been used to obtain the optimal solution for the TEP problem. Optimization techniques such as Benders [21,22] and hierarchical [23] decompositions have also been utilized.…”

Section: Introductionmentioning

confidence: 99%

Transmission expansion planning using multivariate interpolation

Mortaz

Fuerte-Ledezma

Gutiérrez-Alcaraz

et al. 2015

Electric Power Systems Research

View full text Add to dashboard Cite

“…The methodology to calculate P M P IC and ∆ M P IC are provided in appendix A. K is the maximum allowable capacity of a single line dictated by reliability concerns. As indicated in the expansion (5), the ":" operator in (5) and (6) is the sum over an elementwise product or Frobenius product, while "•" denotes a regular matrix multiplication or inner product and ⊗ the outer product. Constraint (6) states that the sum of power ratings of interconnecting branches has to be more than or equal to the total interconnection power.…”

Section: Milp Optimization Of Topology and Ratingmentioning

confidence: 99%

Technology and Topology Optimization for Multizonal Transmission Systems

Ergun

Rawn

Belmans

et al. 2014

IEEE Trans. Power Syst.

View full text Add to dashboard Cite

This paper presents a method to optimize equipment investments in multizonal transmission systems, considering spatial properties of the areas of focus. Together with a probabilistic technique for assessing nodal injection capability, the method in the paper completes the methodology of a long term transmission system planning tool. Transmission topology, line route and technology are optimized through iterative application of linear integer programming and Dijkstra's shortest path algorithm. By optimizing the transmission route, the spatial properties of the area of focus are taken into account, which in turn can significantly influence the installation costs of transmission equipment. The optimization method considers both AC and DC technology and takes the N-1 security criterion into account.

show abstract

“…From the review of TNEP, TNEP methods can be classified into three methods consisting of mathematical method, heuristic method and meta‐heuristic method [9]. For the mathematical method, optimisation techniques such as bender decomposition [10], linear programming [11], dynamic programming [12], non‐linear programming (NLP) [13] and mixed integer programming [14] are mostly used. For the heuristic method, a sensitivity analysis is used to allocate the additional transmission lines [15].…”

Section: Introductionmentioning

confidence: 99%

Improving method of robust transmission network expansion planning considering intermittent renewable energy generation and loads

Chatthaworn

Chaitusaney

2015

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

This study presents a novel method for robust transmission network expansion planning (RTNEP) considering intermittent renewable energy generation and loads. The investment cost of transmission line and operating cost are considered as the objective function of the planning. This study proposes to select the suitable scenarios to make the robust expansion plan for all possible scenarios based on intermittent renewable energy generation and loads data in a year. Meta-heuristic algorithm called adaptive tabu search (ATS) is employed in the proposed RTNEP. ATS iterates between the main problem, which minimises the investment cost and operation cost and the subproblem, which minimises the total power generation of conventional generators and curtailments of renewable energy generation and loads. This study uses AC load flow based on Newton-Raphson method and non-linear programming (NLP) based on interior point method for solving the main problem and the subproblem, respectively. IEEE Reliability Test System 79 (RTS 79) is used for testing the proposed method. The results show that the proposed expansion plan is more robust than the solutions from other research works.

show abstract

Application of computer software in transmission expansion planning using variable load structure

Cited by 20 publications

References 7 publications

Transmission expansion planning using multivariate interpolation

Transmission expansion planning using multivariate interpolation

Technology and Topology Optimization for Multizonal Transmission Systems

Improving method of robust transmission network expansion planning considering intermittent renewable energy generation and loads

Contact Info

Product

Resources

About