Energy Management in Micro Grids Based on the Optima Demand Response by Real Price of Energy

Torres, Edwin Marcelo García; Millán, Idi Amin Isaac

doi:10.1109/inciscos49368.2019.00028

Cited by 3 publications

(3 citation statements)

References 15 publications

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“…MGs facilitate enhanced energy circulation in distribution networks and diminish transmission line losses. Many academic papers have investigated MGs using various methods, such as the dynamic modeling of linear and nonlinear dynamics, benchmarks, creating more advanced fault-tolerant control systems, and optimization techniques [23,24].…”

Section: Electricity Markets For Microgridsmentioning

confidence: 99%

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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%

“…Electricity markets have been researched from several points of view, starting from the economics approach [6,9,16,17], in which the recovery of smart-grid investments is addressed through an electricity market model. Electricity markets have also been researched to merge them with gas and heating markets [18].…”

Section: Introductionmentioning

confidence: 99%

Optimum Stochastic Allocation for Demand Response for Power Markets in Microgrids

Garcia,

Águila,

Ortiz

et al. 2024

Energies

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“…The DOE (U.S. Department of Energy) defines the microgrid as interconnected generators with site-connected electrical loads that have two connection modes: (1) grid-connected and (2) isolated mode; it can also be a low-voltage distribution network that has interconnected distributed energy resources (DER), feeding controllable loads and critical loads [18,26,27].…”

Section: Microgridmentioning

confidence: 99%

Optimal Resource Assignment in Hybrid Microgrids Based on Demand Response Proposals

Garcia,

Águila,

Ortiz

et al. 2024

Sustainability

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The energy consumption of buildings has been affected by the increase in new loads, which is where emerging technologies have become important. In this sense, microgrids have become a solution that has reduced the loadability of power systems. Thus, the Salesian Polytechnic University in Quito has implemented a hybrid microgrid with three photovoltaic plants (PV), two battery storage systems (BESS), and a connection to the public grid. This research shows a methodology to minimize the energy consumption of the public grid by taking advantage of the existing resources in the microgrid through the allocation of resources and demand management, for which a domotic system based on a z-wave protocol was implemented to monitor and control the loads. The initial state and the state after the implementation of the management equipment were compared, and the reduction of electricity consumption in the public grid was quantified, which was around 63%.

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Optimal Energy Management of a Residential Microgrid Considering the Range Anxiety Factor, Uncertainties, and Time-of-Use Tariff Schemes

Akbari

Shadlu

2023

2023 8th International Conference on Technology and Energy Management (ICTEM)

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Energy Management in Micro Grids Based on the Optima Demand Response by Real Price of Energy

Cited by 3 publications

References 15 publications

Optimum Stochastic Allocation for Demand Response for Power Markets in Microgrids

Optimum Stochastic Allocation for Demand Response for Power Markets in Microgrids

Optimal Resource Assignment in Hybrid Microgrids Based on Demand Response Proposals

Optimal Energy Management of a Residential Microgrid Considering the Range Anxiety Factor, Uncertainties, and Time-of-Use Tariff Schemes

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