Open Africa Power 2019

Name: Hamani Kamal

Bio/Personal Statement: In September 2014 I graduated with Master Degree in Electrical Engineering at the Mouloud Mammeri University in Algeria. During this degree period I was in touch with materials as the electromagnetic modelling, the electric machines and drive design, the signal treatment, the applied math, especially the numerical method as the Finite Element Method, etc. Since October 2014 I have been a first stage researcher at the Electrical Engineering department of The Mouloud Mammeri University, where I am working on the electromagnetic modelling topic. My current work seeks to find correlation between environmental condition and electrical devices; it is based upon building electromagnetic models, by using a hybrid method, between numerical and semi-analytical approach.

Thanks to this experience I got skills in the physic modelling systems, the several research protocols, theoretical and experimental; this part of my professional pathway allows me getting great communication command in both French and English languages, good abilities in the data analysis and the capacity to work as a team or autonomously. Recently I have the chance to work as a consultant with an industrial cabinet, and then I find out about my new skills in the client relations, situation and condition analysis and the problem solving.

Title of Capstone Project: Power systems control using the Learning machine technique – Case of small rural village in Algeria

Abstract: The electricity transmission and distribution are important in the power sector as it is the production step; they allow the bringing of electricity to the end user. The electricity transmission and distribution are distinct by two methods. The fist and the oldest one is a linear grid figuration, where the energy flow is running in one sense from the electricity plane until the end user. But these last years a new electricity distribution way is rising, because of transformation occurred in the power grid configuration, due to the penetration of the grid with the renewable energies.  The second method to transit and to distribute electricity is the called smart grid, organized as an ecosystem. In the new power grid generation is not easy to define the upstream either the downstream, then the energy flow is not running in one direction. Such transformation demand new devices and tools. Due to the both energy consumption and associated building operation costs are increasing rapidly around the world, the need for flexible and cost-effective management of the energy used by buildings in a smart grid environment is increasing.

To answer the double challenge of reduce the carbon emission and keep the electricity available and accessible for all. We need to innovate in the production, transport, and distribution of electricity. In the Algeria case, two main issues must be addressed, the first goal is to launch an energy changeover; by passing gradually from the current production electricity mode rely on the fossil resources to renewable resources. The second aim will be the digitalization of the power grid, which can improve, the way with which the electricity is used, by consequence reduce the electricity consumption. Then the digitalization might be a manner to reduce the carbon emission. The challenge is well addressed and there are strategies and visions to solve it, due to the rarefaction of fossil energies resources, nevertheless the digitalization is not taken seriously under consideration in the in public policy. This paper deals with the method recommended driving Algeria from the current grid configuration to and smart grid technology.

As a pilot project we would work in a case of a rural village in the Mountainair region of Kabylie in Algeria. We consider the problem of minimizing the difference in the demand and the supply of power using microgrid. We setup a microgrid that provides electricity to a village. They have access to the batteries that can store renewable power and also the electrical lines from the main grid. During each time period, these microgrids need to take decision on the amount of renewable power to be used from the batteries as well as the amount of power needed from the main grid. In the first stage of our work, we will collect several kinds of data indispensable of our project. In the second time will build a grid model that helps us to predict the grid comportment. Finally we will explore how a computational approach to learning from interactions, called Machine Learning (ML) can be applied to control power systems. We describe some challenges in power system control and discuss how some of those challenges could be met by using these ML methods. The difficulties associated with their application to control power systems are described and discussed as well as strategies that can be adopted to overcome them.