Abdelilah Maach

An intelligent islanding selection algorithm for optimizing the distribution network based on emergency classification

Smart islanding in outage context is one of smart grid advantages based on integration of distributed generations and evolution of communication infrastructure. Outages are caused in major cases by weather and affect an important population in the word. Renewable resource can be a solution to supply demands in islanded region and can have the role of main utility duration outage period. This paper present an efficient power management and a smart dynamic distribution network based on some decisive parameters like geographic position, uninterrupted loads, interrupted load and classification of entities that depends on the priority, like hospitals that need continuously electricity to save peoples lives. The best way to have a smart distribution system is to break the grid into clusters or micro grids. In our approach we start with searching an independent layered trees based on parameters and we define some selection concept to define covered entities and some optimization strategy to decrease number of islanded micro grids. All information are collected from sensors/meters and transmitted to the regional data center for analyzing and making decision. Decisions are executed by controllers and switchers installed in each entity. We present in this paper the approach steps based on an IEEE43 bus model. A simulation is done with some hypothesis to describe more the concept with a discussion of the distribution model simulation results. The Objective is to propose a solution to power shortages problem and define a strategy to operate in an intentional-islanding context to improve public access to power and provide consumer power during emergencies and grid outage.

A Smart Approach for Intentional Islanding based on Dynamic Selection Algorithm in Microgrid with distributed generation

The electricity distribution system provides major opportunities for smart grid because of its important role of distributing electrical power from the main grid to users, it has the potential to supply electricity during grid outages. An outage or intentional islanding is one of distribution system problems and we should rethink our concept to include autonomous micro-grid and dynamic distribution concepts with distributed generations. In this condition, it is important for the micro-grid to continue to provide a constant power to the islanded zone load. This paper presents a new approach to power shortages problem and specifies the goals of strategy can be in an intentional-islanding operation to improve public access to power and provide consumer power during emergencies and grid outage, we explain in this paper a potential outage management approach and determine the best way to distribute the planned outages among the consumers, the planning should cover all entities in the islanded zone but our goal is to have the minimum loss and the maximum consumer covered. We build our smart distribution network based on consumer parameters like geographic coordinates, energy produced, emergency load, optional load, energy produced and category. When the micro-grid is cut off from the main grid the system detect the most emergency entity and take this entity as start point to build a dynamic planning, each entity near of the entity reference will be is added to the network tree if his emergency load is covered by the local distributed generator. As result of emergency strategy we obtain an outage distribution network for the intentional islanding. An intelligent algorithm is developed to solve the problem. We also discuss some results of the different distribution model.

Dynamic balancing of powers in islanded microgrid using distributed energy resources and prosumers for efficient energy management

In recent years, Most of countries think to combine between existing electrical grid and a smart grid using renewable resources as solution with the intention of achieving 100% of green power in the future, The objective is to decrease costs of production and importation of energy, protecting environment and citizens health by closing all power plants like nuclear plant. The process of delivering energy is production, transmission and distribution; we focus on distribution process in this paper because in default transmission or in outage case we have to response to majority of demand in the islanded region during outage. The problem is to how optimize energy distribution and distribute smartly the exiting energy produced or stored in the local region with integration of prosumers for an efficient power management. We propose in this paper a smart approach for an advanced balancing of powers based on dynamic selection algorithm to collect real time information and select entities that will be powered. The selection is based on some parameters like geographic position, obligatory load, optional load, level of priority, and local self-production if exist. The selection is dynamic because parameters can be changed and the information is detected by controller installed in each entity all connected to the regional data center to analyze and make decisions to manage and improve reliability of power supply by supplying load during power outage. As result of emergency strategy we obtain a smart outage distribution network for the intentional islanding. An intelligent algorithm is developed as proposition of solution to the problem with discussion results of the distribution model simulation.

Load Signatures Identification Based on Real Power Fluctuations

Identification of individual sources of energy consumption is one new research area that contributes to reduce electricity consumption in buildings, generate energy awareness and improve efficiency of available energy resources usage. This paper proposes a solution based on Multilayer Perceptron and the change of real power to distinguish and identify appliances from the raw load signatures directly without features extraction. Our simulation indicates that these raw load signatures can offer a quick and accurate identification.

Energy Efficiency Approach for Smart Building in Islanding Mode Based on Distributed Energy Resources

Smart buildings represent a prototypical cyber-physical system with deeply coupled embedded sensing and networked information processing that has increasingly become part of our daily lives. The notion of cyber physical is very important because the cyber word collects information from the various physical parameters through sensors and smart devices and on the basis of this information the main controller makes decisions and an energy distribution plan during outage period. Through context-aware sensing and computation the cyber-physical systems will be able to acquire contextual awareness information from the physical world and use this information in an intelligent way to build an effective energy management system based on smart distribution of power produced from renewable resources. The proposed approach allow a dynamic selection based on real time consumption measurement and information collected by different controllers installed in different entities inside building to decide the entities that will be powered during outage, the idea presents a way for optimization of restored energy and a intelligent strategy to response to customer demands based on their classification and their needing priority. An algorithm is developed to implement our approach with a simulation in Java environment to validate our efficiency management system through on-site distributed generators within buildings to operate in islanding mode. Finally, The objective of this paper is to propose a solution for new building generation that represent future smart cities concept and to have an self-supply based on distributed generation without needing to be connected to the main power grid.

A Novel Smart Distribution System for an Islanded Region

Region outage is one of distribution system and most of time caused by weather or a fault in transmission lines. Smart grid is a new concept that can be a solution for few people existing in a far region to avoid islanded problem. Thanks to IT evolution and the integration of the renewable resources in the existing electrical grid and the bi-directional communication ensured in distribution network, we can distribute power smartly to response all demands or response the emergencies demands. In this paper we propose a potential outage management and a new approach of distribution based on some collected region parameters and based on the potential of distributed generation like solar panel, wind turbine and storage batteries. Islanding region can be detected with some existing islanding detection methods. Smart loads selection is done through an intelligent controller who collects information from different controllers and sensors. The regional data center analyzes and decides a layered tree that contains consumers who will be covered by the outage operation. An algorithm is developed to implement our approach with some distribution simulation to discuss and analyze results.

Discrete Wavelet Transform and Classifiers for Appliances Recognition

Recognition of appliances’ signatures is an important task in energy disaggregation applications. To save and manage energy, load signatures provided by appliances can be used to detect which appliance is used. In this study, we use a low frequency database to identify appliances based on discrete wavelet transform for features extraction and data dimensionality reduction. Further that, the accuracy of several classifiers is investigated. This paper aims to prove the effectiveness of DWT in load signatures recognition. Then, the best classifier for this studied task is selected.

Human Daily Activity Recognition Using Neural Networks and Ontology-Based Activity Representation

In real-life people live together in the same place, recognize their activities is challenging than activities of one single resident, but essential to collect information about real life activities inside home, then ease the assisted living in the real environment. This paper presents a multilayer perceptron model and a supervised learning technique called backpropagation to train a neural network in order to recognize multi-users activities inside smart home, and select useful features according to minimum redundancy maximum relevance. The results show that different feature datasets and different number of neurons of hidden layer of neural network yield different activity recognition accuracy. The selection of suitable feature datasets increases the activity recognition accuracy and reduces the time of execution. Our experimental results show that we achieve an accuracy of 99% with the winner method and 96% with the threshold method, respectively, for recognizing multi-user activities.

A Cyber-Physical Power Distribution Management System for Smart Buildings

Cyber-physical systems can collect information from different physical parameters through smart sensors and process this information in the cyber-world for best actuators control and energy efficiency. A smart building is such a good scope of application and presents a prototypical cyber-physical energy system because through sensing and computing, the system can analyze and make decisions based on contextual awareness information from the physical world and use this information in an intelligent way for smart distribution and smart balancing between power resources in outage mode. A new smart building architecture is proposed in this paper based on cyber physical manager for a dynamic selection of powered houses in an islanded building. The cyber physical manager control exchange with the main grid and also manage the power distribution into building based on analyzing of some parameters like real time consumption measurements collected by smart sensors/meters and batteries level charge. Prosumers production is also very important to be including in the building self powering in outage period. A simulation is done with results discussion for more optimization and to check the effectiveness and superiority of our autonomous power management system through on-site distributed generators within buildings to operate in islanding mode. Finally, This paper present a solution for new building generation that can have a self-supply based on distributed renewable energy and thereafter reduce costs for both government and costumers and create smart living space that becomes an important trend of future.

Towards a new adaptive E-learning framework for adapting content to presentation

E-learning system (E-LS) has become one of the most important tools in the education system (ES) in recent years. This is due to significant improvements in the use of the Adaptive Learning System (ALS). In this paper, we introduce a new framework that appropriately adapts content to presentation to solve many problems that learners suffer at the elementary level. Our approach takes into account the background of learners in many sides; the geographical side, the cultural side, the social side, their knowledge, preferences, interests besides their physical disability for achieving high levels of reliability and the adaptivity required in E-LS. In this sense, we have established the first brick of ALS in the Dynamic Adaptive Hypermedia Systems (DAHS), which we call Adaptive E-Learning System for Generation Presentation (AELS-GP).