Review on generation and transmission expansion co‐planning models under a market environment

Gonzalez-Romero, Isaac Camilo; Wogrin, Sonja; Gómez, Tomás

doi:10.1049/iet-gtd.2019.0123

Cited by 36 publications

(14 citation statements)

References 102 publications

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“…To the best of our knowledge, there are few studies on joint investment in candidate assets to maximize profits in deregulated markets. The vast majority of power systems today are transitioning from centralized to deregulated [22]. The preferential use of renewable energy with zero marginal cost leads to transmission congestion or variation of the locational marginal price (LMP).…”

Section: Indices Of Nodesmentioning

confidence: 99%

Strategic Investment in Transmission and Energy Storage in Electricity Markets

Tian

Sun

Han

2022

Journal of Modern Power Systems and Clean Energy

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The variability of renewable energy and transmission congestion provide opportunities for arbitrage by merchants in deregulated electricity markets. Merchants strategically invest to maximize their profits. This paper proposes a joint investment framework for renewable energy, transmission lines, and energy storage using the Stackelberg game model. At the upper level, merchants implement investment and operation strategies for deregulated transmission and energy storage to maximize profits. At the middle level, central planners seek to maximize social welfare through investments in centralized renewable energy and energy storage. At the lower level, independent system operators jointly optimize the energy and reserve markets to minimize the total operating costs. Merchants are remunerated through financial rights, which are a settlement method based on locational marginal price. The trilevel optimization problem is reformulated as a tractable single-level one using Karush-Kuhn-Tucker (KKT) conditions and strong duality theory. The interaction between merchants and central planners is studied with an example based on the IEEE 30-bus test system. The assignment of weight coefficients to the corresponding stochastic scenarios can help merchants avoid investment risk, and their effectiveness is verified with the IEEE 118-bus test system.

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Section: Indices Of Nodesmentioning

confidence: 99%

Strategic Investment in Transmission and Energy Storage in Electricity Markets

Tian

Sun

Han

2022

Journal of Modern Power Systems and Clean Energy

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“…TEP is one of the key decisions in power-systems design, with deep and long-lasting consequences on system performance. Transmission network planners must consider potential feedback from Energies 2019, 12, 4427 3 of 17 strategic market players [8] and decide whether to adopt a proactive or a reactive planning approach, which could lead to complicated hierarchical optimization and equilibrium problems (for an overview of TEP models under a liberalized market environment please refer to [9]). In general, transmission network planners must select which new lines to add to the network.…”

Section: Power Transmission Planningmentioning

confidence: 99%

A Decentralized Solution for Transmission Expansion Planning: Getting Inspiration from Nature

et al. 2019

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Transmission expansion planning is a problem of considerable complexity where classical optimization techniques are unable to handle large case studies. Decomposition and divide-and-conquer strategies have been applied to this problem. We propose an alternative approach based on agent-based modeling (ABM) and inspired by the behavior of the Plasmodium mold, which builds efficient transportation networks as result of its search for food sources. Algorithms inspired by this mold have already been applied to road-network design. We modify an existing ABM for road-network design to include the idiosyncratic features of power systems and their related physics, and test it over an array of case studies. Our results show that the ABM can provide near-optimal designs in all the instances studied, possibly with some further interesting properties with respect to the robustness of the developed design. In addition, the model works in a decentralized manner, using mostly local information. This means that computational time will scale with size in a more benign way than global optimization approaches. Our work shows promise in applying ABMs to solve similarly complex global optimization problems in the energy landscape.Energies 2019, 12, 4427 2 of 17 local, because they refer to agents and those they encounter in their proximity [3]. However, their interactions might lead to globally optimal design, such as in the cases of ant-colony behavior and slime mold growth, which have been shown to develop optimal networks [2]. In these biological systems, network development involves two phases: exploration and consolidation. The exploratory phase is characterized by the over-production of links between the core organism and the possible food sources. The consolidation phase, in turn, leads to the selection and positive reinforcement of the links that are used the most, while destroying or recycling the rest. The final network structure is likely to represent a context-specific balance between the need for efficient transport, low cost, and robustness.The inspiration for our algorithm comes from reference [2]. In their article, which is based on biological experiments, the authors argue that the slime mold Physarum polycephalum creates a network that is efficient enough to compete with the real design of the railway system around Tokyo. The molds Plasmodium and Physarum have been shown to be able to solve many computational problems, such as finding the shortest path between two points [4], constructing hierarchies of planar proximity graphs [5], or executing basic logical computing schemes [5,6]. The molds are also capable of sketching a mathematical model of an adaptive network that solves a convoluted maze [2]. The key underlying mechanism supporting its success, in all these instances, is always this cycle of over-production of links and consolidation. This is precisely what we will imitate in our algorithm: the transmission lines that are used the most will be reinforced, while those that are not used will be discarded. Some s...

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“…Numerous studies in the field of power grid development planning in traditional and restructuring the power system using meta-innovative methods such as Genetic Algorithm [21][22][23], Simulated Annealing [24], Tabu Search [25], Particle Swarm Optimization Algorithm [26] and a Shuffled Frog Leaping Algorithm [27]. However, no research has been done on the GTD in the presence of the NPP, with the purpose of supplying electricity to auxiliary loads after the power plant trip.…”

Section: Introductionmentioning

confidence: 99%

Presenting new approach for optimal placement of nuclear power plant connected to the grid after the trip

et al. 2021

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This study presents a combination of optimal placement and power system development with the aim of supplying electricity for Nuclear Power Plant after the trip of power plant. Power supply to the internal loads of power plant by the off-site power system is one of the main fields of research in achieving the safety Nuclear Power Plant. One of the main purposes in this article is to introduce a suitable and safe place for the construction and connection of a Nuclear Power Plant to the power system. These locations are identified by the power plants on-site loads and the average of the lowest number of relay protection after the Nuclear Power Plant trip, based on electricity considerations. Along with the optimal placement in this paper, the power system development, including the generation and transmission development in order to provide electricity with higher reliability to the Nuclear Power Plant after the trip is also presented. Monte Carlo and Latin Hypercube Sampling probabilistic methods are proposed for locating the site of a Nuclear Power Plant and algorithms of Genetic and Particle Swarm Optimization for locating and developing power generation and transmission systems. The simulation results are implemented on the IEEE RTS 24-bus system, and finally suitable locations for the construction of the Nuclear Power Plant and the generation and transmission development with the aim of feeding the power plant from the off-site power system and sufficient assurance that the reactor core does not melt after the trip, are determined.

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Review on generation and transmission expansion co‐planning models under a market environment

Cited by 36 publications

References 102 publications

Strategic Investment in Transmission and Energy Storage in Electricity Markets

Strategic Investment in Transmission and Energy Storage in Electricity Markets

A Decentralized Solution for Transmission Expansion Planning: Getting Inspiration from Nature

Presenting new approach for optimal placement of nuclear power plant connected to the grid after the trip

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