The multi-scale generation and transmission expansion model

Sarid, A.; Tzur, Michal

doi:10.1016/j.energy.2018.01.091

Cited by 15 publications

(3 citation statements)

References 26 publications

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“…The main theme of this study is to examine the deferral effect of DGs on transmission investments (see also [17] for deferral effect of energy storage on transmission upgrades). A similar study is published by Sarid and Tzur [18]. They design a power network with generation and transmission expansions as well as DG presences modeled through varying penetration levels.…”

Section: Literature Reviewmentioning

confidence: 85%

A lattice method for jump-diffusion process applied to transmission expansion investments under demand and distributed generation uncertainties

Kucuksayacigil

Min

2020

Energy Syst

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Strategic decision making for rare events is considered to be an arduous course of actions as their impacts cannot accurately be modeled. Transmission of electrical power is a major challenge in this day and age due to the prevalent of rare events. Decision makers of generation units, distribution utilities, and transmission networks do not often cooperate, which creates severe uncertainties for all players. Growth of demand for electricity and installation or removal of distributed generation (DG), considered to be a rare event, are among uncertainties encountered by transmission network owners. Expansion decisions for transmission lines should be strategically executed because installations of DGs may create a stranded cost for transmission owners. In this study, we propose a real options framework that quantifies the values of transmission investments under demand and DG uncertainties to guide decision makers of transmission companies regarding how to adapt their expansions decisions. We model demand uncertainty as a geometric Brownian motion process and DG uncertainty as a Poisson arrival process. We devise a computationally-efficient lattice diagram to discretize both processes in a single grid, which can also be employed to model other types of rare events in various sectors. The proposed framework is demonstrated on a realistic transmission network. Numerical study shows that our proposed lattice model is computationally superior over existing diagrams. As for managerial insights, it shows that depending on the locations of DG installations, DG penetration may not reduce the value of a transmission network. If the center at which a DG is installed has a large-capacity local generator, the installation may not undervalue the transmission network.

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Section: Literature Reviewmentioning

confidence: 85%

A lattice method for jump-diffusion process applied to transmission expansion investments under demand and distributed generation uncertainties

Kucuksayacigil

Min

2020

Energy Syst

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“…The transmission system has a vital role in power systems, especially in deregulated environments, where it intervenes to make an adoption between generation and distribution sections [1]. The main objective of transmission expansion planning (TEP) problem is to determine where, how many, and when to construct new lines while satisfying several technoeconomic constraints, which allows the power system planners to spot the optimal facilities to be retrofitted in the transmission system aiming at enhancing the power transfer between the generation side and load points [2].…”

Section: Background Definitions and Motivationsmentioning

confidence: 99%

Transmission expansion planning integrated with wind farms: A review, comparative study, and a novel profound search approach

Naderi

Pourakbari‐Kasmaei²,

Lehtonen³

2020

International Journal of Electrical Power & Energy Systems

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This paper develops a novel hybrid algorithm for solving transmission expansion planning (TEP) problems in electric power networks. Raising the awareness about immense contaminants produced by fossil fuels as well as depleting these resources, have pushed energy companies toward considering more renewable energy resources (RERs). The RESs are beneficial for the society and the power system utility, however, taking into account the uncertainties, which are inherent in RERs, increase the complexity of the optimization problems. In this work, a Monte-Carlo simulation (MCS) is used to address the intermittent nature of wind energy. To handle the resulted model, by modifying and combining three wellknown evolutionary algorithms such as shuffled frog leaping algorithm (SFLA), particle swarm optimization (PSO), and teaching learning-based optimization (TLBO), a potent hybrid MSFLA-MPSO-MTLBO, namely combinatorial heuristic-based profound-search algorithm (CHPSA), is proposed. A self-adaptive probabilistic mutation operator (SAPMO) is employed to enhance the effectiveness and computational efficiency of the CHPSA. Ten commonly-used benchmark problems are introduced to corroborate the performance of the CHPSA, while the IEEE RTS 24-bus test system is used to validate the model. Results show that the proposed CHPSA is capable of obtaining better solutions than other algorithms, either implemented in this paper or borrowed from the literature.

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“…In [7], a generation and storage capacity expansion model that considers power ramps, minimum power output and minimum up and down times is presented. The authors of [8] propose a mixed-integer linear formulation for modeling a generation and transmission ex-pansion problem considering different time scales.…”

Section: Introductionmentioning

confidence: 99%

Influence of the controllability of electric vehicles on generation and storage capacity expansion decisions

Carrión

Domínguez

Zárate-Miñano

2019

Energy

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This paper proposes a capacity investment model to analyze the influence of the controllability of the charge of plug-in electric vehicles (PEVs) in generation and storage expansion decisions. The proposed model provides the financial incentives that should be offered to PEV users in order to implement the optimal expansion decisions. Considering that the decision-making process faced by the power system planner must simultaneously consider long-and short-term uncertainties, a three-stage stochastic programming problem is formulated. In this model, capacity investments and financial incentives for PEV users are decided in the first stage, whereas operating decisions regarding the day-ahead and real-time markets are made in the second and third stages, respectively. Numerical results are provided from a realistic case study based on the isolated power system comprising Lanzarote and Fuerteventura islands in Spain.

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The multi-scale generation and transmission expansion model

Cited by 15 publications

References 26 publications

A lattice method for jump-diffusion process applied to transmission expansion investments under demand and distributed generation uncertainties

A lattice method for jump-diffusion process applied to transmission expansion investments under demand and distributed generation uncertainties

Transmission expansion planning integrated with wind farms: A review, comparative study, and a novel profound search approach

Influence of the controllability of electric vehicles on generation and storage capacity expansion decisions

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