Implementation of a decentralized real-time management system for electrical distribution networks using the internet of things in smart grids

Lekbich, Anass; Belfqih, Abdelaziz; Zedak, Chaimae; Boukherouaa, Jamal; Elmariami, Faissal

doi:10.11591/eei.v10i3.2436

Cited by 5 publications

(3 citation statements)

References 31 publications

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“…This is to show that the proposed system's development costs are the lowest compare to others. In comparison to the other controllers, the Raspberry Pi [10] and BeagleBone Black [9] have the most efficient computational efficiency, but they are also the most costly and complex to programme. The cheapest controller is the PIC 16F877 [20], but it has the lowest computational efficiency and requires an external WiFi module to connect to the internet.…”

Section: Resultsmentioning

confidence: 99%

Internet of things-based photovoltaics parameter monitoring system using NodeMCU ESP8266

Sutikno

Purnama

Pamungkas

et al. 2021

IJECE

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<span>The use of the internet of things (IoT) in solar photovoltaic (PV) systems is a critical feature for remote monitoring, supervising, and performance evaluation. Furthermore, it improves the long-term viability, consistency, efficiency, and system maintenance of energy production. However, previous researchers' proposed PV monitoring systems are relatively complex and expensive. Furthermore, the existing systems do not have any backup data, which means that the acquired data could be lost if the network connection fails. This paper presents a simple and low-cost IoT-based PV parameter monitoring system, with additional backup data stored on a microSD card. A NodeMCU ESP8266 development board is chosen as the main controller because it is a system-on-chip (SOC) microcontroller with integrated Wi-Fi and low-power support, all in one chip to reduce the cost of the proposed system. The solar irradiance, ambient temperature, PV output voltage and PV output current, are measured with photo-diodes, DHT22, impedance dividers and ACS712. While, the PV output power is a product of the PV voltage and PV current. ThingSpeak, an open-source software, is used as a cloud database and data monitoring tool in the form of interactive graphics. The results showed that the system was designed to be highly accurate, reliable, simple to use, and low-cost.</span>

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Section: Resultsmentioning

confidence: 99%

Internet of things-based photovoltaics parameter monitoring system using NodeMCU ESP8266

Sutikno

Purnama

Pamungkas

et al. 2021

IJECE

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“…Additionally, in buildings, when the load energy demand is unmatched to the available renewable energy, the user can have one of the possible situations, the surplus or deficit situation. This mismatch may force the system to request the energy needed from the main grid [16], [17]. The use of renewable energy to save and reduce electricity consumption in buildings is becoming one of the necessary solutions of such problematics.…”

Section: Introductionmentioning

confidence: 99%

A new modular nanogrid energy management system based on multi-agent architecture

Hamidi

Raihani

Youssfi

et al. 2022

IJPEDS

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The emergence of renewable energy sources with controllable loads gave the opportunity to the consumers to build their own Microgrids. However, the intermittence of renewable energy sources such as wind and photovoltaic leads to some challenges in terms of balancing generation and consumption. This paper aims to present a novel multi-agent model based intelligent control scheme to balance the home/building alternative current (AC)-direct current (DC) load demands and renewable energy sources. The new proposed scheme consists of a three-level hierarchical multi agent system based on cooperation, communication and interaction between intelligent agents to fulfill the load's requirements. Then, the proposed multi agent framework is simulated using four different nanogrids to prove its effectiveness using different temporal profiles for loads and generators. The proposed model is designed to be modular, so that it can be considered as a sample from a set of similar modules, assigned to different buildings to allow efficient energy sharing and balancing. The used approach in this concept is inspired from auto-similar systems, which is well suited and easy to implement on multi agent systems. A co-simulation in MATLAB and JAVA/JADE platforms has been performed regarding the production-consumption of the 24 hours baseline period.

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“…It is for this reason that test 7 does not appear in Figures 4 and 5. In this case, network reconfiguration is the ideal solution to avoid the violation of voltage limits, as it is a powerful tool that helps manage the network in the event of anomalies [48], [49]. The system therefore switches directly from module 2 (EMS) to module 4 (DMS), as represented in Figure 1, in order to change the topology of the electrical network and find its optimal reconfiguration.…”

mentioning

confidence: 99%

Energy management system for distribution networks integrating photovoltaic and storage units

Zedak¹,

Belfqih²,

Boukherouaa³

et al. 2022

IJECE

Self Cite

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<span>The concept of the optimization energy management system, developed in this work, is to determine the optimal combination of energy from several generation sources and to schedule their commitment, while optimizing the cost of energy, power losses and voltage drops. In order to achieve these objectives, the non-dominated sorting genetic Algorithm II (NSGA-II) was modified and applied to an IEEE 33-bus test network containing 10 photovoltaic power plants and 4 battery energy storage systems placed at optimal points in the network. To evaluate the system performance, the resolution was performed under several test conditions. Optimal Pareto solutions were classified using three decision-making methods, namely analytic hierarchy process (AHP), TOPSIS and entropy-TOPSIS, compared to each other for more accurate results. The simulation results obtained by NSGA-II and classified using entropy-TOPSIS showed a significant and considerable reduction in terms of energy cost, power losses and voltage drops while successfully meeting all constraints. In addition, the diversity of the results proved once again the robustness and effectiveness of the algorithm. A graphical interface was also developed to display all the decisions made by the algorithm, and all other information such as the states of power systems, voltage profiles, alarms, and history.</span>

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Implementation of a decentralized real-time management system for electrical distribution networks using the internet of things in smart grids

Cited by 5 publications

References 31 publications

Internet of things-based photovoltaics parameter monitoring system using NodeMCU ESP8266

Internet of things-based photovoltaics parameter monitoring system using NodeMCU ESP8266

A new modular nanogrid energy management system based on multi-agent architecture

Energy management system for distribution networks integrating photovoltaic and storage units

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