Review of Electricity Markets for Smart Nano-Grids

Robalino, Willyam Marcelo Viñán; Torres, Edwin Marcelo García

doi:10.25100/iyc.v21i2.7462

Cited by 3 publications

(1 citation statement)

References 20 publications

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“…The electricity market must employ suitable incentives and enough technology across the network to improve and promote the elasticity of the demand side needed for the optimal and manageable operation of the electricity market itself [27]. This involves a cost-benefit analysis of how much the market wants to invest in these indicated expenses and the goal it intends for its participants.…”

Section: Electricity Markets For Microgridsmentioning

confidence: 99%

Optimum Stochastic Allocation for Demand Response for Power Markets in Microgrids

Garcia,

Águila,

Ortiz

et al. 2024

Energies

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This research incorporates an electricity market model based on a stochastic allocation of distributed resources and the analysis of an optimal demand response for a smart microgrid. This research develops a methodology that allows the application and comparison of various demand-response mechanisms and the analysis of the differences between them and the case of no-demand response, emphasizing economics, environmental care, demand curves, and other factors. By enabling more active participation by residential users of the smart microgrid, these demand-response methods help to flatten the demand curve and support the goals set by the electricity market model. Both conventional and non-conventional generators compete in the electricity market, with renewable energy sources preferred to encourage green generation. Conventional generators are required to supply electricity gradually, starting with the lowest pollution level. In addition, conventional generators are compensated for dispatch, system reliability, and availability. In addition, random variables are used in this study to predict initial load, solar radiation analysis, and biomass input before resources are optimized to meet demand.

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Section: Electricity Markets For Microgridsmentioning

confidence: 99%

Optimum Stochastic Allocation for Demand Response for Power Markets in Microgrids

Garcia,

Águila,

Ortiz

et al. 2024

Energies

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ANN based optimization of price-based demand response management for solar powered nanogrids

Amjad

Javeed

Umar

et al. 2020

2020 IEEE 23rd International Multitopic Conference (INMIC)

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Optimization of the implementation design of distributed energy resources in micro-grids

Robalino

Andrade

2021

inycomp

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This article develops a study about the energy resources available in microgrids, extracting and analyzing data form satellite databases, in order to apply it to the technologies available. On the other hand, a demand estimation is carried out based on measurements, and finally an optimization is performed to determine the most economically profitable option with the correspondent graphs and analysis.

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Review of Electricity Markets for Smart Nano-Grids

Cited by 3 publications

References 20 publications

Optimum Stochastic Allocation for Demand Response for Power Markets in Microgrids

Optimum Stochastic Allocation for Demand Response for Power Markets in Microgrids

ANN based optimization of price-based demand response management for solar powered nanogrids

Optimization of the implementation design of distributed energy resources in micro-grids

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