Analysis of voltage profile to determine energy demand using Monte Carlo algorithms and Markov Chains (MCMC)

García, Edwin Mauricio López; Águila, Alexander; Isaac, Idi A.; González, Jorge W.; López, Gabriel

doi:10.1109/upec.2016.8114092

Cited by 13 publications

(7 citation statements)

References 24 publications

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“…For this purpose, an average power representing the energy consumption in one hour is determined. With the hourly historical data, at the time The customer's The average power factor is calculated by relating the average power and the maximum power (Caracterización de la Carga en Sistemas Eléctricos de Distribución, n.d.;Grainger & Stevenson, 1996; E. M. ; E. M. García Torres, Águila, Isaac, González, & López, 2016; E. M. ; E. M. García Torres & Isaac, 2017;Guerrón, García Torres, & Montero, 2014;Meza Cartagena & García Torres, 2018), as shown in equation 17. 17Where:…”

Section: Economical Officementioning

confidence: 99%

Estimated cost of electricity with time horizon for micro grids based on the policy response of demand for real price of energy

Torres

2020

Enfoque UTE

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The intelligent microgrids are an efficient alternative, which allows to supply the demand decreasing the losses of the electrical system and at the same time; the environment and the consumers are the main beneficiaries. This article develops a heuristic based on an energy management model based on the real price of electricity, which will allow end users to encourage the implementation of a policy of response to demand, in order to optimize their consumption, for which a micro smart grid is analyzed, with conventional and non-conventional renewable generation, In addition, a mechanism of "real energy price" will be implemented as a policy of response to demand, with the aim of optimizing the costs of energy that will be transferred to users depending on the stratum to which it belongs, these costs will have a short-term horizon with hourly intervals, achieving a reduction in the purchase of energy from the system

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Section: Economical Officementioning

confidence: 99%

Estimated cost of electricity with time horizon for micro grids based on the policy response of demand for real price of energy

Torres

2020

Enfoque UTE

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“…Transmission and distribution networks are in theory considered a monopoly, however it is questionable because not all those networks must be owned by the same company, but instead for example expansions to serve unattended demand (11) can be built and administrated by another company.…”

Section: Electricity Markets Main Structurementioning

confidence: 99%

Review of Electricity Markets for Smart Nano-Grids

Robalino

Torres

2019

inycomp

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Este artícul o se enfoca en revisar los mode los de mercados eléctricos y las característic as de las nano redes inteligentes, realizando un estudio de los aspectos principales, estructura e integración. Investigaciones previas son discutidas e ideas fundamentales son desarrolladas y explicadas, y finalmente variables y restricciones son expuestas para modelar un mercado eléctrico incluyendo las consideraciones para nano redes inteligentes

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“…But even knowing current data does not guarantee to know them in the future, which is why this is a problem with high uncertainty and depends on a probabilistic analysis. Among the probabilistic (stochastic) methods used in reliability evaluations, the most robust and most frequently used are the Markov chain and the Montecarlo method [6]. Energy distribution companies have often decided the location of the switching devices empirically in electric distribution systems since there is no clear methodology that defines verified steps that should be followed and that responds to probabilistic criteria of the data giving special importance to the topology of the distribution network.…”

Section: Introductionmentioning

confidence: 99%

“…Suppose this experiment is repeated "many" times (scenarios). In that case, it is possible to have the probabilities of occurrence of all reliability indicators in different scenarios of the analysis variables, but for the same distribution network, a concept that responds to the Montecarlo method [6]. The proposed methodology is iterative, and each scenario is analyzed using the multicriteria method; the method processes extended to the number of reclosers desired to connect according to a cost criterion (availability of investment).…”

Section: Introductionmentioning

confidence: 99%

Optimal Location of Reclosers in Electrical Distribution Systems Considering Multicriteria Decision Through the Generation of Scenarios Using the Montecarlo Method

et al. 2023

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This work presents a novel methodology for the optimal location of reclosers in electric distribution systems. The proposal uses a multicriteria analysis to evaluate the reliability indicators for this level 3 (distribution) by generating scenarios from pseudo-random variables. The reliability indicators considered in the study are the System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI), Customer Average Interruption Duration Index (CAIDI), and Average Energy Not Supplied (AENS). It is employed a deterministic random generation in a defined range associated with each analysis variable (failure rate by elements and loads, failure duration, number of customers per load point, mean power consumed at each load point, etc.) The reliability indicators (criteria) are calculated for every possible location of a recloser in the candidate primary sections, thus obtaining the decision matrix, normalized and weighted by the CRITIC method to find the optimal location according to a minimum criterion. This analysis is repeated N times through the generation of scenarios using the Montecarlo method, establishing the probability of occurrence of each winning alternative and choosing the final optimal location of the first recloser within the distribution system. The methodology also proposes the switching coordination repeating the previously described analysis for locating a second recloser considering that the first was already a winning alternative within the generation of "many" scenarios. The scope of the proposed methodology is the number of reclosers that it is desired to analyze considering cost constraints and is general for any distribution system. The analysis is carried out with comprehensive programming in the Matlab software environment. The results successfully respond to the maneuver and switching tests with the joint criterion of minimizing all reliability indicators for level 3 (distribution). With this proposal, knowledge gaps in reliability studies are solved. The absence of data is completed with generations of pseudo-random variables, and the optimal location of the reclosers responds to all reliability criteria in distribution with weighting alternatives. The novel proposed methodology is validated with an exhaustive search analysis where all possible single or multiple reconnection scenarios are analyzed. The winning location alternative found coincides with the one determined by the proposed methodology in more than 90% of the generated random scenarios.

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Analysis of voltage profile to determine energy demand using Monte Carlo algorithms and Markov Chains (MCMC)

Cited by 13 publications

References 24 publications

Estimated cost of electricity with time horizon for micro grids based on the policy response of demand for real price of energy

Estimated cost of electricity with time horizon for micro grids based on the policy response of demand for real price of energy

Review of Electricity Markets for Smart Nano-Grids

Optimal Location of Reclosers in Electrical Distribution Systems Considering Multicriteria Decision Through the Generation of Scenarios Using the Montecarlo Method

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