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Intelligent Decentralized Energy Management in Microgrids II

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 5065

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Prof. Dr. Anastasios Dounis

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Faculty of Engineering, University of West Attica, 12243 Athens, Greece
Interests: computational intelligence and evolutionary computation; fuzzy systems; fuzzy control and modelling; fuzzy cognitive maps and petri nets in decision support systems; intelligent control; time series prediction; automation systems in renewable energy resources; intelligent energy management systems and smart buildings; design and management of autonomous smart micro grids; power electronics in photovoltaic systems; control electrochromic devices; modelling and control of reverse osmosis desalination
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Dear Colleagues,

Future energy microgrids will be characterized by an increasing decentralization of generation and storage. Energy management is an essential factor in the operation of a decentralized energy system. An Energy Management System (EMS) is responsible for optimizing the balance of supply and demand in the microgrid. Recent advances in Computational Intelligent (CI) techniques have become the center of attention in the research topic of Distributed Energy Management (DEM). EMSs have been developed based on CI to ensure that the energy generation patterns of distributed renewable resources match the energy consumption patterns. The main advantages of a DEM approach are the increased reliability of the microgrid, modularity, and scalability. There has been significant research progress in CI-DEM software/hardware techniques.

This Special Issue (SI) focuses on the emerging synergy between CI and DEM in microgrids. The SI seeks to contribute to intelligent DEM to improve the energy efficiency of microgrids in order to satisfy technical, socio-economic, and environmental goals. We invite papers on innovative technical developments, reviews, case studies, and papers from different scientific disciplines relevant to intelligent DEM in microgrids.

You could find the first successful volume of our special issue at the following link:
https://www.mdpi.com/journal/energies/special_issues/Intelligent_Decentralized_Energy_Management

Prof. Dr. Anastasios Dounis
Guest Editor

Manuscript Submission Information

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Keywords

buildings and microgrids
transactive energy management system
neural networks
evolutionary computation
fuzzy logic systems
fuzzy cognitive maps
machine learning algorithms
multi-agent systems
reinforcement learning
distributed intelligence
autonomous polygeneration microgrids
game theory
distributed optimization
embedded system for energy management demand
fault detection and diagnosis in energy management systems
decentrilized microgrid control and management

Published Papers (5 papers)

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Research

10 pages, 17532 KiB

Open AccessArticle

Monitoring Energy and Power Quality of the Loads in a Microgrid Laboratory Using Smart Meters

by Viktor Isanbaev, Raúl Baños, Fernando Martínez, Alfredo Alcayde and Consolación Gil

Energies 2024, 17(5), 1251; https://doi.org/10.3390/en17051251 - 6 Mar 2024

Cited by 1 | Viewed by 727

Abstract

Microgrids are local energy production and distribution networks that can operate independently when disconnected from the main power grid thanks to the integration of power generation systems, energy storage units and intelligent control systems. However, despite their advantages, the optimal energy management of real microgrids remains a subject that requires further investigation. Specifically, an effective management of microgrids requires managing a large number of electrical variables related to the power generated by the microgrid’s power supplies, the power consumed by the loads and the aspects of power quality. This study analyzes how we can monitor different variables, such as the active power, reactive power, power factor, total harmonic distortion and frequency in the loads of a microgrid, using high-precision power meters. Our empirical study, conducted using a functional microgrid comprising a hybrid wind–solar power system and several household appliances, demonstrates the feasibility of using low-cost and high-performance power meters with IoT functionality to collect valuable power quality and energy consumption data that can be used to control the microgrid operation. Full article

(This article belongs to the Special Issue Intelligent Decentralized Energy Management in Microgrids II)

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23 pages, 8888 KiB

Open AccessArticle

A New Digital Twins-Based Overcurrent Protection Scheme for Distributed Energy Resources Integrated Distribution Networks

by Eduardo Gómez-Luna, John E. Candelo-Becerra and Juan C. Vasquez

Energies 2023, 16(14), 5545; https://doi.org/10.3390/en16145545 - 22 Jul 2023

Cited by 3 | Viewed by 1153

Abstract

This paper presents a novel overcurrent protection scheme based on digital twins for a distribution network with distributed energy resources. A coordination protection standard is employed to perform settings and coordinate intelligent electronic devices, evaluating the effects of distributed energy resources. In addition, some integration criteria for distributed energy resources are proposed to identify the impact on overcurrent protections. The power hardware-in-the-loop (PHIL) scheme is designed to develop digital twins (DT) that connect the real relays to the simulated network. Moreover, a standard for substation automation is employed to define the communication protocol for reading Generic Object-Oriented Substation Events (GOOSE) messages. Furthermore, the IEEE 13-node test feeder is employed to validate the method and model in the real-time simulation software. The results show a miscoordination of the overcurrent protection scheme installed in the distribution network with the action of different distributed energy resources. Full article

(This article belongs to the Special Issue Intelligent Decentralized Energy Management in Microgrids II)

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19 pages, 703 KiB

Open AccessArticle

A Homotopy-Based Approach to Solve the Power Flow Problem in Islanded Microgrid with Droop-Controlled Distributed Generation Units

by Alisson Lima-Silva, Francisco Damasceno Freitas and Luis Filomeno de Jesus Fernandes

Energies 2023, 16(14), 5323; https://doi.org/10.3390/en16145323 - 12 Jul 2023

Cited by 1 | Viewed by 871

Abstract

This paper proposes a homotopy-based approach to solve the power flow problem (PFP) in islanded microgrid networks with droop-controlled distributed generation (DG) units. The technique is based on modifying an “easy” problem solution that evolves with the computation of intermediate results to the PFP solution of interest. These intermediate results require the solution of nonlinear equations through Newton–Raphson (NR) method. In favor of convergence, the intermediate solutions are close to each other, strengthening the convergence qualities of the technique for the solution of interest. The DG units are modeled with operational power limits and three types of droop-control strategies, while the loads are both magnitude voltage- and frequency-dependent. To evaluate the method performance, simulations are performed considering the proposed and classical NR methods, both departing from a flat start estimation. Tests are carried out in three test systems. Different load and DG unit scenarios are implemented for a 6-, 38-, and 69-bus test system. A base case is studied for all systems, while for the two larger models, a loading factor is used to simulate the load augmenting up to the maximum value. The results demonstrated that for the largest-size model system, only the homotopy-based approach could solve the PFP for stringent requirements such as the diversification of the load profile and hard loading operation point. Full article

(This article belongs to the Special Issue Intelligent Decentralized Energy Management in Microgrids II)

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18 pages, 2165 KiB

Open AccessArticle

Hybrid Driving Training and Particle Swarm Optimization Algorithm-Based Optimal Control for Performance Improvement of Microgrids

by Dina A. Zaki, Hany M. Hasanien, Mohammed Alharbi, Zia Ullah and Mariam A. Sameh

Energies 2023, 16(11), 4355; https://doi.org/10.3390/en16114355 - 26 May 2023

Cited by 3 | Viewed by 981

Abstract

This paper discusses the importance of microgrids in power systems and introduces a new method for enhancing their performance by improving the transient voltage response in the face of disturbances. The method involves using a hybrid optimization approach that combines driving training-based and particle swarm optimization techniques (HDTPS). This hybrid approach is used to fine-tune the system’s cascaded control scheme parameters, based on proportional–integral–accelerator (PIA) and proportional–integral controllers. The optimization problem is formulated using a central composite response surface methodology (CCRSM) to create an objective function. To validate the suggested control methodology, PSCAD/EMTDC software is used to carry out the simulations. The simulations explore various scenarios wherein the microgrid is transformed into an islanded system and is subjected to various types of faults and load changes. A comparison was made between the two proposed optimized controllers. The simulation results demonstrate the effectiveness of using a PIA-optimized controller; it improved the microgrid performance and greatly enhanced the voltage profile. In addition, the two controllers’ gains were optimized using only PSO to ensure that the outcomes of the HDTPS model demonstrated the same results. Finally, a comparison was made between the two optimization techniques (HDTPS and PSO); the results show a better impact when using the HDTPS model for controller optimization. Full article

(This article belongs to the Special Issue Intelligent Decentralized Energy Management in Microgrids II)

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17 pages, 2121 KiB

Open AccessArticle

Towards Digital Twins of Small Productive Processes in Microgrids

by Danny Espín-Sarzosa, Rodrigo Palma-Behnke and Felipe Valencia-Arroyave

Energies 2023, 16(11), 4324; https://doi.org/10.3390/en16114324 - 25 May 2023

Viewed by 934

Abstract

In microgrids (MGs), energy management systems (EMSs) have been using increasingly detailed models of generation units, loads, and networks to make decisions on the power/energy contribution of each available unit to meet the electrical energy demand. This work aims to investigate the use of digital twins (DT) of small productive processes (SPPs) to regulate endogenous process variables to ensure final product quality, while the expected power consumption is estimated and communicated to the EMS so that it can make its decisions on the participation of each power source in meeting the electrical energy demand. The literature review reveals that this is one of the first attempts, in the context of MGs, to generate DT for SPPs that combine not only the electrical energy consumption, but also link it with the energy/mass balances taking place in the SPPs, highlighting the complexity that SPPs have as electrical loads. The results demonstrate that environmental conditions significantly influence the final electrical consumption of the SPPs. Additionally, the MG exhibits better economic performance when the SPP DT supports EMS decision-making, which is of great importance in MGs due to the special conditions they have for electric power generation, being more challenging in isolated MGs. Full article

(This article belongs to the Special Issue Intelligent Decentralized Energy Management in Microgrids II)

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