Energy Management Strategy of the DC Distribution System in Buildings Using the EV Service Model

Byeon, Gilsung; Yoon, Tae-Myung; Oh, Seaseung; Jang, Gilsoo

doi:10.1109/tpel.2012.2210911

Cited by 132 publications

(54 citation statements)

References 25 publications

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“…Most prediction models have several inputs, such as the position of the day (weekday/weekend/holyday, month and/or season), temperatures, and load databases [24].…”

Section: Main Inputs To Build the Prediction Modelmentioning

confidence: 99%

The Fuzzy Logic Method to Efficiently Optimize Electricity Consumption in Individual Housing

2017

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Electricity demand shifting and reduction still raise a huge interest for end-users at the household level, especially because of the ongoing design of a dynamic pricing approach. In particular, end-users must act as the starting point for decreasing their consumption during peak hours to prevent the need to extend the grid and thus save considerable costs. This article points out the relevance of a fuzzy logic algorithm to efficiently predict short term load consumption (STLC). This approach is the cornerstone of a new home energy management (HEM) algorithm which is able to optimize the cost of electricity consumption, while smoothing the peak demand. The fuzzy logic modeling involves a strong reliance on a complete database of real consumption data from many instrumented show houses. The proposed HEM algorithm enables any end-user to manage his electricity consumption with a high degree of flexibility and transparency, and "reshape" the load profile. For example, this can be mainly achieved using smart control of a storage system coupled with remote management of the electric appliances. The simulation results demonstrate that an accurate prediction of STLC gives the possibility of achieving optimal planning and operation of the HEM system.

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“…Most prediction models have several inputs, such as the position of the day (weekday/weekend/holyday, month and/or season), temperatures, and load databases [24].…”

Section: Main Inputs To Build the Prediction Modelmentioning

confidence: 99%

The Fuzzy Logic Method to Efficiently Optimize Electricity Consumption in Individual Housing

2017

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“…Los sistemas híbridos se los recomienda instalar como si fuesen sistemas aislados a la red, de tal manera que toda la energía generada, sin importar su cantidad, es aprovechada [16].…”

Section: Sistema De Generación Por Medio De Bicicletas Estáticasunclassified

Generación distribuida a partir de bicicletas estáticas y sistemas híbridos

Carrion

Ortiz

2013

ings

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El presente artículo hace referencia a las diferentes maneras de generar electricidad en los sistemas de generación distribuida, creando microredes eléctricas las cuales necesitan sistemas de gestión de electricidad.La generación distribuida se ha convertido en la mejor alternativa para reducir el consumo de energía en las edificaciones y también para generar ingresos económicos adicionales. La importancia de generar electricidad desde las propias edificaciones ha hecho que el ser humano vaya elaborando distintos dispositivos para aprovechar las diferentes y variadas energías, siendo las más usuales: la solar y eólica. El aprovechamiento del movimiento de las máquinas estáticas para hacer ejercicio es una nueva fuente para generar electricidad, muy poco aprovechada y por ello es necesario verificar como es su comportamiento asociada a una microred eléctrica y al sistema de gestión energética. Al finalizar este proyecto, se tendrá un enfoque como punto de partida para futuras investigaciones en lo referente a generación distribuida usando máquinas estáticas para ejercicio.

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“…A fast charger for this technology is presented in [16]; the proposed bidirectional AC/DC converter allows a maximum of 25 kWh charging in one hour. PEV charging stations based on PV sources with optimal energy management are presented in several studies [17][18][19][20][21], however, the proposed systems do not take into account either storage ageing or grid power limitations for injection mode. Related to optimal charging and considering the public grid tariffs to buy or sell energy, a day-ahead scheduling method is studied in [22], in which, according to vehicle-to-grid strategy, a long term cost minimization model is proposed.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Simulation of DC Microgrids for Electric Vehicle Charging Stations

Locment

Sechilariu

2015

Energies

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This paper focuses on the evaluation of theoretical and numerical aspects related to an original DC microgrid power architecture for efficient charging of plug-in electric vehicles (PEVs). The proposed DC microgrid is based on photovoltaic array (PVA) generation, electrochemical storage, and grid connection; it is assumed that PEVs have a direct access to their DC charger input. As opposed to conventional power architecture designs, the PVA is coupled directly on the DC link without a static converter, which implies no DC voltage stabilization, increasing energy efficiency, and reducing control complexity. Based on a real-time rule-based algorithm, the proposed power management allows self-consumption according to PVA power production and storage constraints, and the public grid is seen only as back-up. The first phase of modeling aims to evaluate the main energy flows within the proposed DC microgrid architecture and to identify the control structure and the power management strategies. For this, an original model is obtained by applying the Energetic Macroscopic Representation formalism, which allows deducing the control design using Maximum Control Structure. The second phase of simulation is based on the numerical characterization of the DC microgrid components and the energy management strategies, which consider the power source requirements, charging times of different PEVs, electrochemical storage ageing, and grid power limitations for injection mode. The simulation results show the validity of the model and the feasibility of the proposed DC microgrid power architecture which presents good performance in terms of total efficiency and simplified control. OPEN ACCESSEnergies 2015, 8 4336

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Energy Management Strategy of the DC Distribution System in Buildings Using the EV Service Model

Cited by 132 publications

References 25 publications

The Fuzzy Logic Method to Efficiently Optimize Electricity Consumption in Individual Housing

The Fuzzy Logic Method to Efficiently Optimize Electricity Consumption in Individual Housing

Generación distribuida a partir de bicicletas estáticas y sistemas híbridos

Modeling and Simulation of DC Microgrids for Electric Vehicle Charging Stations

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