An interdisciplinary approach on efficient virtual microgrid to virtual microgrid energy balancing incorporating data preprocessing techniques

Koukaras, Paraskevas; Tjortjis, Christos; Gkaidatzis, Paschalis A.; Bezas, Napoleon; Ioannidis, Dimosthenis; Tzovaras, Dimitrios

doi:10.1007/s00607-021-00929-7

Cited by 17 publications

(11 citation statements)

References 47 publications

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“…PsM seeks to prevent particular types of failure completely. This paper investigates the state of the art in PsM reporting on multi-domain use cases and conceives a theoretical framework that enables PsM for proactive buildings that may also be considered as microgrids [21].…”

Section: Discussionmentioning

confidence: 99%

Proactive Buildings: A Prescriptive Maintenance Approach

Koukaras

Dimara

Gonzalez

et al. 2022

IFIP Advances in Information and Communication Technology

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Prescriptive maintenance has recently attracted a lot of scientific attention. It integrates the advantages of descriptive and predictive analytics to automate the process of detecting non nominal device functionality. Implementing such proactive measures in home or industrial settings may improve equipment dependability and minimize operational expenses. There are several techniques for prescriptive maintenance in diverse use cases, but none elaborates on a general methodology that permits successful prescriptive analysis for small size industrial or residential settings. This study reports on prescriptive analytics, while assessing recent research efforts on multi-domain prescriptive maintenance. Given the existing state of the art, the main contribution of this work is to propose a broad framework for prescriptive maintenance that may be interpreted as a high-level approach for enabling proactive buildings.

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Section: Discussionmentioning

confidence: 99%

Proactive Buildings: A Prescriptive Maintenance Approach

Koukaras

Dimara

Gonzalez

et al. 2022

IFIP Advances in Information and Communication Technology

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“…This approach generates new options to relax the energy contract (between consumer and aggregator) and introduce elasticity on DR signal acceptance. It also increases the prospects for autonomous peer-to-peer (P2P) level energy optimization [3]. The proposed framework's validation on real-world pilots, showcases optimization minimizing the cost, while keeping occupant discomfort at acceptable levels, through a flexible DR scheme enforcement.…”

Section: Introductionmentioning

confidence: 98%

A Tri-Layer Optimization Framework for Day-Ahead Energy Scheduling Based on Cost and Discomfort Minimization

et al. 2021

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Over the past few decades, industry and academia have made great strides to improve aspects related with optimal energy management. These include better ways for efficient energy asset management, generating great opportunities for optimization of energy distribution, discomfort minimization, energy production, cost reduction and more. This paper proposes a framework for a multi-objective analysis, acting as a novel tool that offers responses for optimal energy management through a decision support system. The novelty is in the structure of the methodology, since it considers two distinct optimization problems for two actors, consumers and aggregators, with solution being able to completely or partly interact with the other one is in the form of a demand response signal exchange. The overall optimization is formulated by a bi-objective optimization problem for the consumer side, aiming at cost minimization and discomfort reduction, and a single objective optimization problem for the aggregator side aiming at cost minimization. The framework consists of three architectural layers, namely, the consumer, aggregator and decision support system (DSS), forming a tri-layer optimization framework with multiple interacting objects, such as objective functions, variables, constants and constraints. The DSS layer is responsible for decision support by forecasting the day-ahead energy management requirements. The main purpose of this study is to achieve optimal management of energy resources, considering both aggregator and consumer preferences and goals, whilst abiding with real-world system constraints. This is conducted through detailed simulations using real data from a pilot, that is part of Terni Distribution System portfolio.

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“…Extractability is to extract useful information from raw data for further calculation and analysis. Feature extraction methods include principal component analysis, Linear discriminant analysis and independent component analysis [8][9]. By selecting a function, the source data can be converted into a format that is easy to analyze and calculate.…”

Section: Introductionmentioning

confidence: 99%

Recursive calculation of space multi body system dynamics based on data analysis

Huang

2023

International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023)

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An interdisciplinary approach on efficient virtual microgrid to virtual microgrid energy balancing incorporating data preprocessing techniques

Cited by 17 publications

References 47 publications

Proactive Buildings: A Prescriptive Maintenance Approach

Proactive Buildings: A Prescriptive Maintenance Approach

A Tri-Layer Optimization Framework for Day-Ahead Energy Scheduling Based on Cost and Discomfort Minimization

Recursive calculation of space multi body system dynamics based on data analysis

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