Assessment of technical and financial benefits of AC and DC microgrids based on solar photovoltaic

Ullah, Shahid; Haidar, Ahmed M. A.; Zen, Hushairi

doi:10.1007/s00202-020-00950-7

Cited by 44 publications

(13 citation statements)

References 27 publications

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“…The conversion losses at various stages are reduced in DC microgrid compared to AC microgrid. 15 The comparison on line losses, power, and efficiency at three different microgrid configurations is illustrated, and the simulated results for DC source and DC load proved to be promising.…”

Section: Literature Reviewmentioning

confidence: 99%

Internet of things‐based smart residential building energy management system for a grid‐connected solar photovoltaic‐powered DC residential building

Chinnathambi

Kamaraj²,

Samuel³

et al. 2021

Intl J of Energy Research

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The intermittent nature of photovoltaic (PV), energy conversion losses, appliance compatibility, and load dynamics pose serious challenges to PVbased DC power distribution system in residential buildings. This article proposes a holistic approach to develop a new smart residential building energy management system using internet of things (IoT)-based multifunction compatible relaying system. The proposed system monitors the loads and provides uninterruptible power supply with minimum energy conversion losses. It achieves best operating load configuration, load prioritization in various modes, and demand-side management (DSM). IoT-based multifunction compatible relaying dystem is embedded with Information and Communication Technology-enabled PZEM module, smart relays, and appliance status monitoring devices. The proposed scheme has been implemented in a DC residential building located at Madurai, Tamil Nadu, India, with 1.5 kW PV system. The results are compared in four scenarios.The experimental results prove that the losses are minimized by 18% ensuring uninterrupted power supply. The implementation of DSM further reduces the losses by 5%. The appliances can be monitored through Grafana based in home touch screen.

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Section: Literature Reviewmentioning

confidence: 99%

Internet of things‐based smart residential building energy management system for a grid‐connected solar photovoltaic‐powered DC residential building

Chinnathambi

Kamaraj²,

Samuel³

et al. 2021

Intl J of Energy Research

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“…Increased Solar Photovoltaic Generation System (SPVGS) installations have enabled many residential, commercial, and industrial facilities to operate as stand-alone microgrids [1] [2]. In such systems, SPVGS will deliver energy to demand throughout the day, with a portion of it being stored in battery systems [3].…”

Section: A Backgroundmentioning

confidence: 99%

Adaptive Demand Response Management System using Polymorphic Bayesian Inference Supported Multilayer Analytics

Sarin¹,

Mani²

2021

IJACSA

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The most significant limitation of stand-alone microgrid systems is the challenge of meeting unexpected additional demands. If demand exceeds the capacity of a standalone system, the system may be unable to satisfy demand. This issue is alleviated in grid-connected technology since the utility system will provide more power if it is demanded. As a result, load scheduling is an integral element of the demand response of a standalone system. There are two components to this problem. If the capacity of a battery-supported power system is restricted, for the period of time that the source is available, it will not be able to meet the entire demand. Appropriately the demand is dispersed across a period of time until the next charge becomes available. Some demands may be disregarded in order to accomplish peak load trimming or if the system is incapable of meeting demand without compromising other important technical and consumer objectives. This is a challenging assignment. This article aims to develop an Adaptive Demand Response Management System (ADRMS) capable of load scheduling and load shedding using an interwoven multidimensional Bayesian inference supported by multiple mathematical models. A two-stage hardware architecture is being developed, with the first hardware measuring demand and source capacity before sending the data to the second hardware via LPWAN for mathematical analysis. In the first phase, two approaches are used to forecast demand: Gaussian Naive Bayes Model (GNBM) and Bayesian Structural Time Series analysis. GNBM is rapid but fails to properly forecast the output when there is zero frequency error whereas BSTS can offer more precise results than GNBM but is slower. Hence two approaches are employed in tandem. The next stage is to assign demand source integration. This is accomplished using Bayesian Reinforcement Learning (BRL), which is based on a number of incentives, including anomaly, cost factors, usefulness, reliability, and size. All Bayesian models are subjected to much of the common Bayes rule, resulting in the formulation of a blended polymorphism model that reduces computing time and memory allocation, and improves processing reliability. The Isolation Forest (IF) method is used to identify and avoid vulnerable loads by determining demand anomalies. The last step employs a Dynamic Preemptive Priority Round Robin (DPPRR) algorithm for preemptive priority based load scheduling based on forecasted data to allocate the next loads to be added.

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“…[18][19][20] Along with technical specifications, the implementation and maintenance cost of any designated scheme should be estimated cautiously before use in realtime scenarios. 21 The preliminary literature review in this subject unearths some of the critical yet undiscovered areas. Researches propose methods for integration of conventional schemes with signal processing or advance ML (Machine Learning) techniques but failed to explain the challenges in a comprehensive manner.…”

Section: Introductionmentioning

confidence: 99%

Review of distributed generator integratedACmicrogrid protection: issues, strategies, and future trends

Sarangi

Sahu

Rout

2021

Intl J of Energy Research

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In the recent power system scenario, the concept of microgrid is evolving rapidly. The architecture should be robust enough to cater the complexity of integration of distributed generation sources, demand-side management, and storage. The fast growth of embedded generation with other advanced power electronic interfaces and components along with energy storage devices change the operating pattern of the integrated power system scenario. In this context, protection is the vital aspect for qualitative uninterrupted power and making the system resilient to adverse, and faulty conditions. Many associated issues, particularly related to AC microgrid systems like the large difference in the short-circuit level between integrated and isolated mode of operation, bidirectional power flow, unsynchronized reclosing, the blindness of protection, lack of natural zero-crossing current, and false tripping are needed to be focused. In light of the above factors, it motivates us to survey the previous research works on the existing protection strategies to redesign and present the critical analysis of the predicted protection issues of microgrid protection with upcoming advanced technology and methodology. This article presents a critical review of the issues and protection schemes for the DG integrated AC microgrid extensively. Here, the merits, and demerits of each protection scheme, and visible possibilities for any advancement in protection strategies to enhance the reliability, selectivity, and security of AC microgrid is emphasized keeping in mind the different connections and configurations. In addition, this work also focuses on integrating the intelligent approaches/devices that help to elevate the current protection schemes to be smarter and efficient.

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Assessment of technical and financial benefits of AC and DC microgrids based on solar photovoltaic

Cited by 44 publications

References 27 publications

Internet of things‐based smart residential building energy management system for a grid‐connected solar photovoltaic‐powered DC residential building

Internet of things‐based smart residential building energy management system for a grid‐connected solar photovoltaic‐powered DC residential building

Adaptive Demand Response Management System using Polymorphic Bayesian Inference Supported Multilayer Analytics

Review of distributed generator integratedACmicrogrid protection: issues, strategies, and future trends

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