• Energy Research

This research paper deals with failures and faults in power smart grids. We propose an original multi-agent approach for power system recovery based on fault classification. For that, we propose the classification of faults as dominant or equivalent ones. This classification has the advantage of optimizing the task of power system recovery. To test and validate our approach, we develop a simulator, named FDIRSY (Fault Detection, Isolation and Recovery SYstem). The experimental study showed that our approach ensures the search for the best solution from the existing ones thanks to the use of mobile agents. These agents have the advantage of evaluating all the existing alternatives while reducing the communication cost (in terms of exchanged messages). We demonstrate that our approach is gainful in terms of required times, actions to be performed as well as the faults to be resolved thanks to the proposed fault classification.

Unified Modeling Language (UML) is currently accepted as the standard for modeling software and control systems since it allows to concentrate on different aspects of the system under design. However, UML lacks formal semantics and, hence, it is not possible to apply, directly, mathematical techniques on UML models to verify them. UML does not feature explicit semantics to model flexible control systems sharing adaptive shared resources either. Thus, this paper proposes a new UML profile, baptized R-UML (Reconfigurable UML), to model such reconfigurable systems. The profile is enriched with a PCP-based solution for the management of resource sharing. The paper also presents an automatic translation of R-UML into R-TNCES, a Petri Net-based formalism, to support model checking.

Power transmission lines of traditional power transmission systems (PTSs) may suffer from some faults that can lead to blackouts. This work proposes a methodology to construct hierarchical distributed control systems (DCSs) for the automatic fault detection and restoration of PTSs using colored Petri nets (CPNs). If faults occur in power transmission lines, they can be detected by supervisors, and local solutions can be computed to restore the faults. Each supervisor is coordinated by a coordination protocol to perform the computation of local solutions. The structures of traditional PTSs are simplified and defined by CPNs, and the derivation processes of fault detection and restoration based on the proposed coordination protocol are verified by the mathematical methods of CPNs. Finally, the complexity of the proposed hierarchical DCS and coordination protocol is discussed and an example is given to illustrate the proposed method. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Cet article traite de la planification de tâches périodiques en temps réel exécutées sur des plateformes multicœurs hétérogènes. Chaque processeur est composé d'un ensemble de cœurs à plusieurs vitesses avec des ressources énergétiques limitées. Un système reconfigurable est sensible aux événements de reconfiguration imprévisibles provenant d'un environnement connexe, tels que l'activation, la suppression ou la mise à jour de tâches. Le problème est de gérer des scénarios de reconfiguration réalisables sous contraintes énergétiques. Étant donné que toute tâche peut terminer l'exécution avant d'atteindre son pire temps d'exécution (WCET), l'idée est de distribuer cette exécution sur différents cœurs de processeur pour respecter les délais connexes et réduire la consommation d'énergie. La méthodologie consiste à utiliser d'abord des vitesses de processeur plus faibles pour consommer moins d'énergie. Si le système n'est toujours pas réalisable après la reconfiguration, nous ajustons les périodes de tâche en tant que solution flexible ou migrons certaines d'entre elles vers les processeurs les moins chargés. En conséquence, un programme linéaire entier (ILP) est formulé pour coder le modèle d'exécution qui attribue des tâches à différents cœurs avec une consommation d'énergie optimale, réalisant ainsi un calcul économe en énergie/calcul vert. La puissance et l'efficacité de l'approche proposée sont évaluées par des études de simulation. En mesurant le coût de la consommation d'énergie, notre solution offre plus de 11 % de gain que les méthodes publiées récemment et améliore de 85 % le nombre total de périodes ajustées. Este documento trata sobre la programación de tareas periódicas en tiempo real ejecutadas en plataformas multinúcleo heterogéneas. Cada procesador se compone de un conjunto de núcleos de varias velocidades con recursos energéticos limitados. Un sistema reconfigurable es sensible a eventos de reconfiguración impredecibles del entorno relacionado, como la activación, eliminación o actualización de tareas. El problema es manejar escenarios de reconfiguración factibles bajo restricciones energéticas. Dado que cualquier tarea puede terminar de ejecutarse antes de alcanzar su peor tiempo de ejecución (WCET), la idea es distribuir esta ejecución en diferentes núcleos de procesador para cumplir con los plazos relacionados y reducir el consumo de energía. La metodología consiste en utilizar primero velocidades de procesador más bajas para consumir menos energía. Si el sistema sigue siendo inviable después de la reconfiguración, ajustamos los períodos de tarea como una solución flexible o migramos algunos de ellos a los procesadores menos cargados. En consecuencia, se formula un programa lineal entero (ILP) para codificar el modelo de ejecución que asigna tareas a diferentes núcleos con un consumo de energía óptimo, realizando así una computación energéticamente eficiente/computación verde. La potencia y eficacia del enfoque propuesto se califican a través de estudios de simulación. Al medir el costo de consumo de energía, nuestra solución ofrece una ganancia superior al 11% que los métodos publicados recientemente y mejora en un 85% el número total de períodos ajustados. This paper deals with the scheduling of real-time periodic tasks executed on heterogeneous multicore platforms. Each processor is composed of a set of multi-speed cores with limited energy resources. A reconfigurable system is sensible to unpredictable reconfiguration events from related environment, such as the activation, removal or update of tasks. The problem is to handle feasible reconfiguration scenarios under energy constraints. Since any task can finish execution before achieving its worst-case execution time (WCET), the idea is to distribute this execution on different processor cores for meeting related deadlines and reducing energy consumption. The methodology consists in using lower processor speeds first to consume less energy. If the system is still non-feasible after reconfiguration, then we adjust the task periods as a flexible solution or migrate some of them to the least loaded processors. Accordingly, an integer linear program (ILP) is formulated to encode the execution model that assigns tasks to different cores with optimal energy consumption, thereby realizing energy-efficient computing/green computing. The potency and effectiveness of the proposed approach are rated through simulation studies. By measuring the energy consumption cost, our solution offers better than 11% of gain than recently published methods and improves by 85% the overall number of adjusted periods. تتناول هذه الورقة جدولة المهام الدورية في الوقت الفعلي المنفذة على منصات متعددة النوى غير متجانسة. يتكون كل معالج من مجموعة من النوى متعددة السرعات مع موارد طاقة محدودة. يكون النظام القابل لإعادة التشكيل معقولاً لأحداث إعادة التشكيل غير المتوقعة من البيئة ذات الصلة، مثل تنشيط المهام أو إزالتها أو تحديثها. تكمن المشكلة في التعامل مع سيناريوهات إعادة التشكيل الممكنة في ظل قيود الطاقة. نظرًا لأن أي مهمة يمكن أن تنتهي من التنفيذ قبل تحقيق أسوأ وقت للتنفيذ (WCET)، فإن الفكرة هي توزيع هذا التنفيذ على نوى المعالج المختلفة للوفاء بالمواعيد النهائية ذات الصلة وتقليل استهلاك الطاقة. تتمثل المنهجية في استخدام سرعات معالج أقل أولاً لاستهلاك طاقة أقل. إذا كان النظام لا يزال غير ممكن بعد إعادة التكوين، فإننا نقوم بتعديل فترات المهمة كحل مرن أو ترحيل بعضها إلى المعالجات الأقل تحميلًا. وفقًا لذلك، تتم صياغة برنامج خطي صحيح (ILP) لتشفير نموذج التنفيذ الذي يعين المهام لنوى مختلفة مع الاستهلاك الأمثل للطاقة، وبالتالي تحقيق الحوسبة الموفرة للطاقة/الحوسبة الخضراء. يتم تقييم قوة وفعالية النهج المقترح من خلال دراسات المحاكاة. من خلال قياس تكلفة استهلاك الطاقة، يقدم حلنا أفضل من 11 ٪ من المكاسب مقارنة بالطرق المنشورة مؤخرًا ويحسن بنسبة 85 ٪ العدد الإجمالي للفترات المعدلة.

This paper presents a new control strategy for optimal energy consumption in microgrids based on forecasting and load shedding method. In islanded mode, only local generation resources are usable. In this mode, the availability of resources is very influenced by meteorological factors. In order to achieve a high availability of energy, microgrid has to satisfy high requirements on intelligent power management. The main objective of this study is to develop a control based on the forecast of production and the priority of loads to ensure high availability of electrical power for critical loads. A mathematical model for the proposed strategy is developed. The simulation of this model on Matlab Simulink for different cases of microgrid topology (sources and loads) shows clearly a high improvement of degree of availability of electrical power supply distribution in microgrid.

This research paper deals with fault detections and dynamic recoveries of electrical smart grids that should be flexible and automatically adapted at run-time when faults occur on lines or devices. These grids are composed of three levels of power lines: High Voltage Lines (44KV), Medium Voltage Lines (11KV), and Low Voltage Lines (380V). In order to control the complexity of detection and deduction, we propose new relations between faults. We define also a multi-agent architecture to allow dynamic recoveries where two types of agents are defined: static agents and mobile agents. Static agents have as a task the detection of local faults on power lines and the recovery of their normal behaviors by using a local knowledge-base. The mobile agents are created to dynamically move on lines and to find new solutions when no local solution is found. To validate and test our approach, we present experimental results showing the originality of the paper's contribution by assuming a case study.

This paper deals with the medium between two reconfigurable sensor nodes characterized by radio interfaces that support multiple channels for exchanging real-time messages under energy constraints. These constraints are violated if the consumed energy in transmission is higher than the remaining quantity of energy. A reconfiguration, i.e., any addition or removal of tasks in devices and consequently of messages on the medium, can cause the violation of real-time or energy constraints at run time. To achieve a feasible scheduling in time (i.e., message deadlines will be respected) and energy (i.e., there is available energy) on the medium, we propose new dynamic solutions: Balance, Dilute, and a Combination of them to manage any addition or removal of messages. The proposed approach utilizes the energy harvesting techniques and the PowerControl algorithm to reduce the nonharvested consumed energy. The proposed strategies achieve significant improvement over existing methods and provide the highest percentage of adding messages, with a lower average in response time and energy consumption. They reach a percentage of success in adding the highest priority messages while meeting deadlines up to 85%.

This paper presents new challenges for the real-time scheduling of distributed reconfigurable embedded systems powered by a renewable energy. Reconfigurable computing systems have to deal with unpredictable events from the environment, such as activation of new tasks and hardware or software failures, by adapting the task allocation and scheduling in order to maintain the system feasibility and performance. The proposed approach is based on an intelligent multiagent distributed architecture composed of: 1) a global agent “coordinator”associated with the whole distributed system and 2) four local agents, such as supervisor, scheduler, battery manager, and reconfiguration manager, belong to each subsystem. The efficiency and completeness of the reconfiguration adaptative strategy is proved as all possible reconfiguration forms are considered to guarantee a feasible system with a graceful quality of service. Two communication protocols, such as an intra-subsystem communication protocol and an inter-subsystem communication protocol, are proposed to ensure the effectiveness of the proposed reconfiguration strategy. Extensive simulations show the effectiveness of the proposed intelligent multiagent distributed architecture in terms of the number of exchanged messages, deadline success ratio, and the energy consumption.

A microgrid is a small-scale smart network that contains distributed resources and loads and serves several technical, economic, and environmental aims. In this kind of power system, the energy generated by different sources is often collected in an adequate bus system (ac or dc busses) and transported to loads across a distribution system. In case of islanding operation of a microgrid, each production insufficiency or distribution system fault can cause a partial or total interruption of power supply required by loads of the microgrid. This unavailability can last longer because of the randomness and intermittent behavior of renewable sources and the importance of the maintenance actions of the distribution system. To guarantee high availability of power supply, microgrid must be able to produce and to transfer the power energy requested by loads. The sizing of distributed sources and the design of the distribution system present an important challenge to achieve this goal. This paper offers a new global methodology carried out in two steps: in the first, it aims to optimize the source sizing by adding some microsources for ensuring the balance between sources production and loads requirement, then, in a second step, it aims to enhance the distribution system design by the creation of new paths of power transmission for transferring the produced energy from sources to loads. The proposed optimization methodology aims to achieve the requested availability rate requested by each load (considering their priorities) by taking into account some technical and economic factors. In this methodology based on genetic algorithms, objective functions are defined, and several electrical and economic constraints are formulated. The graph theory is used to represent the architecture of the microgrid distribution system, and Matpower tool of MATLAB is used to model it. An application and implementation of the proposed optimization methodology in a Tunisian petroleum platform indicate that the proposed solution is efficient in optimizing of power supply availability in its microgrid.