Investment in electricity networks with transmission switching

Villumsen, Jonas Christoffer; Philpott, Andy

doi:10.1016/j.ejor.2012.05.002

Cited by 35 publications

(18 citation statements)

References 19 publications

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“…When the underlying configuration of facilities are dynamic and discrete the Dantzig‐Wolfe reformulation is often particularly strong. This is shown for investments into power distribution networks in and for transmission switching in power networks in . In particular, both papers show that the LP‐gap of the Dantzig‐Wolfe reformulation is often zero which is also observed in the computational results (Section 4.3) of this paper.…”

Section: Dantzig‐wolfe Reformulationsupporting

confidence: 71%

Column generation for stochastic green telecommunication network planning with switchable base stations

Villumsen

Naoum-Sawaya²

2016

Naval Research Logistics

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We present the green telecommunication network planning problem with switchable base stations, where the location and configuration of the base stations are optimized, while taking into account uncertainty and variability of demand. The problem is formulated as a two‐stage stochastic program under demand uncertainty with integers in both stages. Since solving the presented problem is computationally challenging, we develop the corresponding Dantzig‐Wolfe reformulation and propose a solution approach based on column generation. Comprehensive computational results are provided for instances of varying characteristics. The results show that the joint location and dynamic switching of base stations leads to significant savings in terms of energy cost. Up to 30% reduction in power consumption cost is achieved while still serving all users. In certain cases, allowing dynamic configurations leads to more installed base stations and higher user coverage, while having lower total energy consumption. The Dantzig‐Wolfe reformulation provides solutions with a tight LP‐gap eliminating the need for a full branch‐and‐price scheme. Furthermore, the proposed column generation solution approach is computationally efficient and outperforms CPLEX on the majority of the tested instances. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 351–366, 2016

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Section: Dantzig‐wolfe Reformulationsupporting

confidence: 71%

Column generation for stochastic green telecommunication network planning with switchable base stations

Villumsen

Naoum-Sawaya²

2016

Naval Research Logistics

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“…The results are summarized in Table II, where the rows are sorted in ascending order of total cost in the season. The results show that switching one of the lines 3,4,5,8,9,15,16, or 17 out of service can decrease total generation costs. Switching line 4 out of service results in the lowest generation cost of $20 061 606, which is $194 752 or 0.96% saving.…”

Section: Experimental Results On the 14-bus Systemmentioning

confidence: 93%

“…In [7], the authors developed a disjunctive programming model to enhance the static security of transmission switching operations. Transmission switching has also been applied in capacity expansion planning ( [8], [9]) and in security constrained unit commitment ( [10], [11]). …”

Section: Introductionmentioning

confidence: 99%

A Decomposition Approach for Solving Seasonal Transmission Switching

Jabarnejad

Wang

Valenzuela

2015

IEEE Trans. Power Syst.

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Economic transmission switching has been proposed as a new control paradigm to improve the economics of electric power systems. In practice, the transmission switching operation itself is a disruptive action to the system. Frequently switching lines into or out of service can create undesirable effects on the security and reliability of power systems and may require new investments in the automation and control systems. In this paper, we formulate an economic seasonal transmission switching model where transmission switching occurs once at the beginning of a time period (season) and then the transmission topology remains unchanged during that period. The proposed seasonal transmission switching model is a large-scale mixed integer programming problem. The objective of the optimization model is to minimize the total energy generation cost over the season subject to loads and N-1 reliability requirements. We develop a novel decomposition method that decomposes the seasonal problem into one-hour problems which are then solved efficiently. We demonstrate our model and the decomposition approach on the 14-bus, 39-bus, and 118-bus power systems and show potential cost savings in each case.Index Terms-Decomposition, mixed integer programming, power generation dispatch and economics, seasonal transmission switching (STS).

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“…Villumsen and Philpott [32] propose a column generation approach to solving the transmission expansion and switching equipment investment problem when transmission switching is allowed and demands, generator capacities and generator costs are stochastic. Villumsen et al [31] propose a model of the transmission expansion problem when transmission switching is used in response to high wind penetration scenarios.…”

Section: Literature Reviewmentioning

confidence: 99%

Transmission expansion with smart switching under demand uncertainty and line failures

2016

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One of the major challenges in deciding where to build new transmission lines is that there is uncertainty regarding future loads, renewal generation output and equipment failures. We propose a robust optimization model whose transmission expansion solutions ensure that demand can be met over a wide range of conditions. Specifically, we require feasible operation for all loads and renewable generation levels within given ranges, and for all single transmission line failures. Furthermore, we consider transmission switching as an allowable recovery action. This relatively inexpensive method of redirecting power flows improves resiliency, but introduces computational challenges. We present a novel algorithm to solve this model. Computational results are discussed.

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Investment in electricity networks with transmission switching

Cited by 35 publications

References 19 publications

Column generation for stochastic green telecommunication network planning with switchable base stations

Column generation for stochastic green telecommunication network planning with switchable base stations

A Decomposition Approach for Solving Seasonal Transmission Switching

Transmission expansion with smart switching under demand uncertainty and line failures

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