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Multi Objective Based Framework for Energy Management of Smart Micro-Grid

إطار قائم على أهداف متعددة لإدارة الطاقة للشبكة الدقيقة الذكية
Authors: Muhammad Haseeb; Syed Ali Abbas Kazmi; Mehar Ali Malik; Saqib Ali; Syed Basit Ali Bukhari; Dong Ryeol Shin;

Multi Objective Based Framework for Energy Management of Smart Micro-Grid

Abstract

La demande croissante d'énergie dans les réseaux traditionnels devient de plus en plus complexe, moins faisable, nuisible, non économique et élevée en pertes de puissance. Ce document présente une approche de gestion de l'énergie efficace pour atténuer ces problèmes avec le micro-réseau intelligent (SMG) et vise une solution à la fois rentable et écologique, dans le cadre du paradigme du marché de l'énergie. Les objectifs sont atteints avec l'aide du contrôleur de gestion de l'énergie domestique (HEMC), du contrôleur de gestion du marché de l'énergie (EMMC) et de l'agent de contrôle (CA). La charge individuelle est gérée en présence de la production locale, du système de stockage, du confort de l'utilisateur, du SGD et des services publics au sein du paradigme du marché de l'énergie. Une approche de gestion de l'énergie à deux niveaux est proposée pour atteindre les objectifs concernés. La première consiste à gérer la charge et à planifier le stockage en ce qui concerne la production locale individuelle et la tarification du marché. La deuxième consiste à gérer le marché de l'énergie à l'aide de quatre types différents de priorités et d'entrée d'agent de contrôle. Le problème est résolu avec une variante de la méthode méta-heuristique, l'optimisation multi-objectif du loup gris (MOGWO), qui offre une solution plus complète en la comparant à l'optimisation de l'essaim de particules (PSO). La méthodologie proposée est mis en œuvre sur un système de test communautaire basé sur SMG. Les foyers au sein de cette communauté ont des conditions économiques et des priorités personnelles différentes. Les résultats de la simulation démontrent l'atteinte des objectifs visés dans le travail présenté.

La creciente demanda de energía en las redes tradicionales se está volviendo más compleja, menos factible, dañina, antieconómica y con altas pérdidas de energía. Este documento presenta un enfoque de gestión energética eficiente para mitigar estos problemas con una microrred inteligente (SMG) y apunta a una solución que sea rentable y ecológica, dentro del paradigma del mercado energético. Los objetivos se logran con la ayuda de Home Energy Management Controller (HEMC), Energy Market Management Controller (EMMC) y Control Agent (CA). La carga individual se gestiona en presencia. de generación local, sistema de almacenamiento, comodidad del usuario, DGS y Utilidad dentro del paradigma del mercado de la energía. Se propone un enfoque de gestión de energía de dos niveles para lograr los objetivos en cuestión. En primer lugar, es gestionar la carga y programar el almacenamiento con respecto a la generación local individual y los precios del mercado. En segundo lugar, es gestionar el mercado de la energía con la ayuda de cuatro tipos diferentes de prioridades y entrada de agentes de control. El problema se resuelve con una variante del método metaheurístico, la optimización multiobjetivo del lobo gris (MOGWO), que ofrece una solución más completa al compararlo con la optimización del enjambre de partículas (PSO). La metodología propuesta es implementado en un sistema de prueba comunitario basado en SMG. Los hogares dentro de esa comunidad tienen diferentes condiciones económicas y prioridades personales. Los resultados de la simulación demuestran el logro de los objetivos previstos en el trabajo presentado.

The increasing demand of energy in the traditional grids is getting more complex, less feasible, harmful, uneconomical and high in power losses.This paper presents an efficient energy management approach to mitigate such issues with smart micro grid (SMG) and aims at a solution that is both cost effective and ecofriendly, within energy market paradigm.Goals are achieved with the help of Home Energy Management Controller (HEMC), Energy Market Management Controller (EMMC) and Control Agent (CA).The individual load is managed in the presence of local generation, storage system, user comfort, DGs and Utility within energy market paradigm.Two level energy management approach is proposed to achieve concerned goals.First is to manage load and schedule storage with respect to individual local generation and market pricing.Second is to manage energy market with the help of four different types of priorities and control agent input.The problem is solved with a variant of meta-heuristic method, Multi Objective Grey Wolf Optimization (MOGWO), which gives more comprehensive solution by comparing with Particle Swarm Optimization (PSO).The proposed methodology is implemented on a SMG based-community test system.Homes within that community have different economic conditions and personal priorities.Simulation results demonstrates achievement of aimed goals in presented work.

يزداد الطلب المتزايد على الطاقة في الشبكات التقليدية تعقيدًا وأقل جدوى وضارة وغير اقتصادية ومرتفعة في فقدان الطاقة. تقدم هذه الورقة نهجًا فعالًا لإدارة الطاقة للتخفيف من هذه المشكلات باستخدام الشبكة الذكية الصغيرة (SMG) وتهدف إلى حل فعال من حيث التكلفة وصديق للبيئة، ضمن نموذج سوق الطاقة. يتم تحقيق الأهداف بمساعدة وحدة التحكم في إدارة الطاقة المنزلية (HEMC) ووحدة التحكم في إدارة سوق الطاقة (EMMC) ووكيل التحكم (CA). تتم إدارة الحمل الفردي في وجود من التوليد المحلي، ونظام التخزين، وراحة المستخدم، و DGS والمنفعة داخل نموذج سوق الطاقة. يقترح نهجان لإدارة الطاقة على مستوى واحد لتحقيق الأهداف المعنية. الأول هو إدارة الحمل وجدولة التخزين فيما يتعلق بالتوليد المحلي الفردي وتسعير السوق. الثاني هو إدارة سوق الطاقة بمساعدة أربعة أنواع مختلفة من الأولويات ومدخلات عامل التحكم. يتم حل المشكلة باستخدام متغير من الطريقة الاستدلالية، تحسين الذئب الرمادي متعدد الأهداف (MOGWO)، والذي يعطي حلاً أكثر شمولاً من خلال المقارنة مع تحسين سرب الجسيمات (PSO). المنهجية المقترحة هي يتم تنفيذها على نظام اختبار مجتمعي قائم على SMG. تتمتع المنازل داخل هذا المجتمع بظروف اقتصادية وأولويات شخصية مختلفة. توضح نتائج المحاكاة تحقيق الأهداف المستهدفة في العمل المقدم.

Keywords

Renewable energy, Artificial intelligence, Control agent, Energy storage, Economics, Heuristic, Operations research, Engineering, Electricity, Microgrid Control, Energy management system, Particle swarm optimization, Physics, Statistics, Energy management, Power (physics), Schedule, Energy Management, Physical Sciences, energy market management controller, Control and Synchronization in Microgrid Systems, Electrical engineering. Electronics. Nuclear engineering, Smart Grid Applications, Environmental economics, multi objective grey wolf optimization, Geometry, Smart grid, Quantum mechanics, market management, Electricity market, home energy management controller, Machine learning, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Mathematics, local generation, Demand Response in Smart Grids, Electrical and Electronic Engineering, Microgrids, Grid, Biology, Home Energy, Controller (irrigation), Computer science, Agronomy, TK1-9971, Integration of Distributed Generation in Power Systems, Operating system, Control and Systems Engineering, Electrical engineering, Distributed generation, Energy (signal processing), Mathematics

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
30
Top 10%
Top 10%
Top 10%
gold