Multistage transmission expansion planning considering fixed series compensation allocation

Rahmani, Mostafa; Vinasco, Guillermo; Rider, Marcos J.; Romero, Rubén; Pardalos, Pãnos M.

doi:10.1109/pesgm.2014.6938959

Cited by 4 publications

(4 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…To locate the FSC in the TEP problem, one can approximate the investment ratio of FSC with regards to the transmission line, as presented by Equation :

C_{s} = \frac{FSC investment cost per km}{line investment cost per km} = \frac{K_{s} Q_{s}}{{normalK}_{normall}}

where K s , K l , and Q s are global prices for the compensation project (US$/Mvar), the transmission line investment cost (US$/km), and the Mvar transfer capacity, respectively. Q s is a percentage (P s ) of the maximum transfer capacity of a transmission line (Q max ):

Q_{s} = P_{s} Q_{\max} = 3 P_{s} I_{\max}^{2} X_{l}

where I max and X l are the maximum line current (kA) and the transmission line reactance (ohm/km), respectively.…”

Section: Modelingmentioning

confidence: 99%

Application of grey wolf algorithm for multi-year transmission expansion planning from the viewpoint of private investor considering fixed series compensation and uncertainties

Moradi

Alinejad‐Beromi

Kiani

2018

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary The uncertainties caused by restructuring in power systems make transmission investment less attractive for the private investors and increase the risk level. In this paper, a merchant‐based stochastic method is presented for multi‐year transmission expansion planning from the viewpoint of private investors with allocation of fixed series compensation under wind, bids of generators, and load uncertainties. This proposed method maximizes absorption of private investment and eliminates monopolies in restructured environments. The grey wolf optimizer algorithm and point estimation method are applied as the optimization tool and for management of the uncertainties, respectively. In order to demonstrate the dependability of the proposed approach, the planning methodology has been illustrated on the IEEE 24‐bus and 118‐bus test systems. The results of this research show that adding fixed series compensation, besides the reduction of investment cost, will provide a good vision for private investors in order to get suitable transmission projects for investing.

show abstract

“…To locate the FSC in the TEP problem, one can approximate the investment ratio of FSC with regards to the transmission line, as presented by Equation :

C_{s} = \frac{FSC investment cost per km}{line investment cost per km} = \frac{K_{s} Q_{s}}{{normalK}_{normall}}

Q_{s} = P_{s} Q_{\max} = 3 P_{s} I_{\max}^{2} X_{l}

where I max and X l are the maximum line current (kA) and the transmission line reactance (ohm/km), respectively.…”

Section: Modelingmentioning

confidence: 99%

Application of grey wolf algorithm for multi-year transmission expansion planning from the viewpoint of private investor considering fixed series compensation and uncertainties

Moradi

Alinejad‐Beromi

Kiani

2018

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

“… Q s is a percentage ( P s ) of the maximum transfer capacity of a transmission line ( Q max ):

Q_{s} = P_{s} Q_{\max} = 3 P_{s} I_{\max}^{2} X_{l}

where I max is the maximum line current in kA and X l is the transmission line reactance in ohm/km. To locate the FSC in the TEP problem, one can approximate the investment ratio of FSC with regards to the transmission line, as presented by Equation :

C_{s} = \frac{italicFSC italicinvestment cost italicper italickm}{italicline investment cost italicper italickm} = \frac{K_{s} Q_{s}}{K_{l}} = \frac{3 K_{s} P_{s} I_{\max}^{2} X_{l}}{K_{l}}

…”

Section: Modelingmentioning

confidence: 99%

Multi-objective transmission expansion planning with allocation of fixed series compensation under uncertainties

Moradi

Alinejad‐Beromi

Kiani

2017

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary Integration of wind resources into the power systems has increased the technical and financial concerns in transmission expansion planning. In this paper, a stochastic structure is demonstrated for transmission expansion planning with allocation of fixed series compensation under wind and load uncertainties. Fixed series compensations have the ability to increase the transfer capacity of transmission lines. However, their significance benefit for transmission expansion planning is their higher effectiveness in power dispatching, which results in lower investment costs, compared with planning without fixed series compensations. The proposed planning model simultaneously optimizes targets such as the investment cost, the congestion cost, and the expected energy not supplied in each stage. The presented planning model is a complicated nonlinear optimizing problem. For introducing group of nondominated optimal solutions, multi‐objective gray wolf optimizer algorithm based on probabilistic optimal power flow is used. Then, fuzzy approach is used to lead to the best response. For demonstrating the feasibility and susceptibilities of the proposed algorithm, the planning methodology has been illustrated on the IEEE 24‐bus and Colombian test systems. The results acquired from the simulations monitor capability of the proposed structure in order to satisfy various planning indices.

show abstract

“…Sin embargo, existen trabajos en los que se considera la inclusión de compensación serie en circuitos existentes o el cambio de nivel de tensión en ciertos circuitos para el PERT, como se propone en [17]- [19].…”

Section: Introductionunclassified

Planeamiento AC de la expansión de la red de transmisión considerando repotenciación de circuitos y ubicación de capacitores

López-López¹,

Tejada-Arango

López-Lezama

2016

TecnoL.

View full text Add to dashboard Cite

En este artículo se aborda el problema de Planeamiento de la Expansión de la Red de Transmisión (PERT). El PERT consiste en determinar el conjunto de nuevos circuitos necesarios en un sistema de potencia, para atender una demanda futura. En su versión clásica, el PERT considera como candidatos de solución únicamente la adición de nuevas líneas y transformadores. La principal contribución de este artículo consiste en la inclusión de candidatos de solución no convencionales en el PERT. Dichos candidatos de solución son la repotenciación de circuitos existentes y la ubicación de bancos de capacitores. Para tener en cuenta estos últimos se considera un modelo AC de la red de transmisión. La solución al modelo propuesto es llevada a cabo mediante un Algoritmo Genético Híbrido. Los resultados obtenidos son contrastados y validados con publicaciones previas de la literatura técnica. Los sistemas de prueba utilizados son el sistema Garver y el sistema IEEE de 24 barras. Los resultados obtenidos en ambos sistemas muestran que la inclusión de los candidatos no convencionales propuestos en este artículo permite disminuir los costos de la expansión de la red. Este hecho puede servir como indicador para que el planeador del sistema contemple nuevas posibilidades en los estudios de expansión.

show abstract

Multistage transmission expansion planning considering fixed series compensation allocation

Cited by 4 publications

References 0 publications

Application of grey wolf algorithm for multi-year transmission expansion planning from the viewpoint of private investor considering fixed series compensation and uncertainties

Application of grey wolf algorithm for multi-year transmission expansion planning from the viewpoint of private investor considering fixed series compensation and uncertainties

Multi-objective transmission expansion planning with allocation of fixed series compensation under uncertainties

Planeamiento AC de la expansión de la red de transmisión considerando repotenciación de circuitos y ubicación de capacitores

Contact Info

Product

Resources

About