DC Micro-Grid Operational Analysis with a Detailed Simulation Model for Distributed Generation

Lee, Ji-Heon; Kim, Hyun-Jun; Han, Byung-Moon; Jeong, Yoon-Su; Yang, Hyo-Sik; Cha, Hanju

doi:10.6113/jpe.2011.11.3.350

Cited by 27 publications

(5 citation statements)

References 10 publications

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“…Inductors, capacitors, and Metal Oxide Semiconductor Field Effect Transistor (MOSFET) devices with switching functions make up the converter, which controls the voltage flow according to the energy needs. Finally, the energy storage components are charged and discharged using the bi-directional converter (Lee et al, 2011).…”

Section: Dc-dc Boost Convertermentioning

confidence: 99%

Modelling and optimizing microgrid systems with the utilization of real-time residential data: a case study for Palapye, Botswana

Seane,

Samikannu,

Oladiran

et al. 2024

Front. Energy Res.

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Microgrids are becoming a realistic choice for residential buildings due to the increasing need for affordable and sustainable energy solutions in developing nations. Through modeling and simulation, the main goal is to evaluate the viability and performance of a solar microgrid system. Residential load modeling is used, which is vital to developing an effective Energy Management System (EMS) for the microgrid. A residential household’s load metering data is examined using statistical methods, including time series and regression analysis. For the residential community load in this research, Proportional-Integral-Derivative (PID) controllers and Fuzzy Logic Controllers (FLC) are used to generate the necessary Direct Current (DC) microgrid voltage. The simulation research shows that FLC have benefits over PID controllers. The FLC technique performs better at reducing total harmonic distortion, which improves the microgrid system’s overall power quality. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model was found to be the most appropriate and reliable model for the dataset after the performance of the models was evaluated using the metrics. The optimization results also showed that FLC optimization improves the microgrid system’s stability. The exponential Gaussian process regression (GPR) produced the highest R-squared measure of 0.49 and RSME measure of 7.9646, making it the best goodness fit for modeling the total daily energy usage and the peak daily usage.

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Section: Dc-dc Boost Convertermentioning

confidence: 99%

Modelling and optimizing microgrid systems with the utilization of real-time residential data: a case study for Palapye, Botswana

Seane,

Samikannu,

Oladiran

et al. 2024

Front. Energy Res.

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“…Micro-grids are notable as they operate mostly while connected to the distribution network. In addition, Micro-grids can be automatically relocated to isled mode in case of errors in the upstream network [7,8]. After resolving the error and restoring the upstream network operation, Micro-grids can be resynchronized to the rest of the system.…”

Section: Introductionmentioning

confidence: 99%

“…A micro-grid is defined by the [7,17] as short voltage networks with DG resources, jointly with local storage devices and controllable loads. Micro-grids are notable as they operate mostly while connected to the distribution network.…”

Section: Introductionmentioning

confidence: 99%

Local area grid: Power distribution and sharing within neighboring households

Issa

Shubita

Arqoub

et al. 2013

2013 1st International Conference &Amp; Exhibition on the Applications of Information Technology to Renewable Energy Processes

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The Cost of installing a photovoltaic solar system for household remains high and exceeds the budget of most residential homes. Such an issue becomes even more serious in a country such a Jordan with a relatively low income per capita, and where 96% of required oil and gas is imported. This paper presents a project which gives the opportunity for low income households to share the cost photovoltaic solar systems, thus reducing the cost of installation, while at the same time reducing their electric bill considerably. The solution, called LAG, is based on resource sharing and power distribution. The solution is intended to be used in households existing within close proximity such as residential buildings or complexes. The LAG System works on and off the National Grid. The Core of the LAG system is an operating system that works on managing power resources in the most efficient manner.

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“…Recent years have witnessed extensive research on the issue of generated power distribution and Smart Grids. Large-scale Distributed Generation (DG) and Distributed Energy Resources (DER) have raised new challenges that must be dealt with including fault tolerance, security, stability, and bi-directional communications (Lee, 2011). In Active Distribution Networks (ADN), Power distribution should be active and no longer passive (Cheng, 2006).…”

Section: Introductionmentioning

confidence: 99%

“…Micro-grids are notable as they operate mostly while connected to the distribution network. In addition, Micro-grids can be automatically relocated to isled mode in case of errors in the upstream network (Lee, 2011). After resolving the error and restoring the upstream network operation, Micro-grids can be resynchronized to the rest of the system.…”

Section: Introductionmentioning

confidence: 99%

Demand-Driven Algorithm for Sharing and Distribution of Photovoltaic Power in a Small Local Area Grid

Abu-Arqoub

Issa

Shubita

et al. 2014

International Journal of Information Technology and Web Engineering

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The objective of installing a residential photovoltaic system is to cut the cost of the monthly electric bill. However, many homeowners, especially those with low-income, finds it difficult to invest in such systems because require substantial upfront investment. This paper presents a project called PSD-LAG("Sharing and Distribution of Power-Local Area Grid") which attempts to solve the issue of installation cost relying on the concept of power sharing and distribution. Thus two or more neighboring households can share the cost of installation, and accordingly share the generated electric power. A Demand-Driven algorithm is implemented and is embedded in a micro-processor based control unit, called "Intelligent Power Distribution and Control Unit (IPDC Unit)", over sees the operation of the PSD-LAG system. It reads the status of generated power, power requirements for each home, power quota for each home, and accordingly controls a set of hardware devices to distribute the power in a most efficient manner based on usage and quota. At the core of the PSD-LAG is an Intelligent Power Distribution and Control Unit (IPDC Unit) that provides instantaneous monitoring, protection and control. It is an embedded Operating System that reads the status of generated power, power requirements for each home, power quota for each home, and accordingly controls a set of hardware devices to distribute the power in a most efficient manner based on usage and quota.

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DC Micro-Grid Operational Analysis with a Detailed Simulation Model for Distributed Generation

Cited by 27 publications

References 10 publications

Modelling and optimizing microgrid systems with the utilization of real-time residential data: a case study for Palapye, Botswana

Modelling and optimizing microgrid systems with the utilization of real-time residential data: a case study for Palapye, Botswana

Local area grid: Power distribution and sharing within neighboring households

Demand-Driven Algorithm for Sharing and Distribution of Photovoltaic Power in a Small Local Area Grid

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