Nacer K. M'Sirdi

Smart home energy management systems survey

Different kinds of system components including hardware elements, software algorithms, network connections, and sensors are required to cooperate with each other to provide various services in smart home. With the development of smart grid providing a two-way communication infrastructure, residents have the opportunity to schedule their electricity usage pattern to reduce their electricity cost. The energy management of a household level must take into consideration how to reduce the environmental burden, while supporting humans life style. The incentive and motivation to manage energy at the household level is influenced by commercial and technical reasons. Commercially, it offers the passive residential customer to be active in the energy market. The technical aspects include peak shaving, valley filling, load shifting, flexible load curve, strategic conservation and strategic load growth. Another important aspect of energy management systems is the socio-economic impact of such system. This paper reviews the concept of energy management systems for residential customers and looks into the background of smart home energy management system technologies. It highlights the major components, and comparatively analyzes various technological approaches. It also discusses some of the concerns and challenges such as cost, implementation and privacy issues of smart technologies.

Subspace technique for identification of hybrid complex systems.

Switched and piecewise affine models are interesting when modeling a nonlinear and non stationary complex system. Identification of these models is a challenging problem that involves estimation of both the parameters of the submodels, and the partitioning of state and input space. In this paper, we introduce a subspace technique for identification of the class of multi-variable hybrid complex system with unknown switching. Observability and Identifiability problems are discussed. The verification will be done for an experimental greenhouse.

The best MPPT algorithms by VSAS approach for Renewable Energy Sources (RES)

VSAS (Variable Structure Automatic Systems) control methodology is applied to clarify the rationale behind Maximum Power Point Tracking and get the best optimization algorithm. Two algorithms are developed the Modified and Enhanced Perturb and Observe Algorithm (MEPO) the Robust Unified Control Algorithm (RUCA). The maximum power is computed online using a very simple algorithm. Compared to the other algorithms like Perturb and Observe (PO), Hill Climbing, Incremental Encoder (InCod) and and SMC approach it is proven more efficient and faster despite using low frequency commutation. The proposed MPPT has several advantages: simplicity, high convergence speed and is independent on PV array characteristics. The obtained results have proven that the MPPT is tracked even under sudden change of irradiation level.

A hardware algorithm for PAR reduction in smart home

High quality demand side management has become indispensable in the smart grid infrastructure for enhanced energy reduction and system control. Most of the demand side management systems that existed were focusing on the interaction between utility company and its customers. So as a reason the Home Energy Management (HEM) systems plays a crucial role in realizing residential Demand Response (DR) programs in the smart environment. It provides a homeowner the ability to automatically perform smart load controls based on utility programs, customers preference and load priority. This paper presents the hardware demonstration of the proposed HEM system for managing the end-use appliances. The proposed algorithm manages the household loads according to their preset priority and fixed the total household power consumption under certain limit. This work achieves the purpose of reducing electricity expense and clipping the peak-to-average ratio (PAR).

State estimation for MIMO hybrid dynamical model

It is well-known that the parameter estimation is difficult in many real-world application where continuous nonlinear dynamics interact with discrete-event ones. In this paper, we address the problem of state estimation in hybrid systems exhibited by a mix of continuous time dynamics, discrete-time and discrete-event dynamics. We also demonstrate that a set of parameters is identifiable if the operating modes are detectable and observable. An application will illustrate the results proposed.

Estimation of longitudinal and lateral velocity of vehicle

In this paper, we compare three observers and methods for estimation of the longitudinal and latéral velocity of the vehicle. These methods are based on the First Order Sliding Mode (FOSM), Second Order Sliding Mode (SOSM) and on the use of algebraic approach ALIEN. Their performance are studied using a 16 DoF dynamic simulator.

Comparative study of different MPPT techniques for a stand-alone PV system

The (P-V) photovoltaic panels characteristic is nonlinear and highly depended on solar irradiation and temperature cell variations. For that reason, a Maximum Power Point Tracking (MPPT) algorithm is essential so that it is possible to draw peak power from the photovoltaic panel to obtain the maximized produced energy. The main purpose of MPPT technique is to make sure that the solar panel is producing the maximum power. This extracts the maximum amount of power at any given time. To figure out which MPPT technique has the best performances, this paper introduces six different MPPT algorithms existing in literature. In particular, these techniques are tested while the temperature cell was randomly varied. The simulation results are evaluated using Matlab-Simulink.

Micro-climate optimal control for an experimental greenhouse automation

The goal of a greenhouse process culture is to give plants a suitable environment so they can develop properly. On the other hand, this kind of culture allows minimizing emissions and production costs. To reach these objectives, the need an optimal control arises. However, it is well known that agricultural greenhouse is a very complex system, composed of elements that can interact and exchange of energy between them and with their environment. So, the setting and tuning of greenhouse climate controllers is by no means an easy or standard procedure. In this paper, we develop one practical approach to design an optimal controller for this kind of system. The design strategies are based on stated stability and stability theorems for hybrid systems. The questions related to control techniques are discussed to show in this way the complexity of the controller design of a class of the studied system.

Modular Modelling of an Embedded Mobile CPU-GPU Chip for Feature Estimation.

This paper deals with the modelling of a CPU-GPUchip embedded in an Android phone. The model is used for the estimation of variables that characterise the operating state of System on Chip (SoC). The proposed model is built to demonstrate the causal relationships between the variables, through its interconnected structure of subsystems. This structure allows the extension of other components or the easy exchange of subsystems in the case of a change in components or operating mode. The model developed here requires no additional instrumentation—other than the one present on the phone—which facilitates its implementation. It is used for the estimation of the state of the system and can also be used for monitoring and behaviour prediction. The model is validated and the results are promising for further implementation.

Partial vehicle state estimation using Hight Order Sliding Mode Observers

Sometimes, the use of the global vehicle dynamic model is not needed to analyse and develop some applications in vehicle. For example, for the passenger comfort only the sub-model of the suspension is needed. In this context, this paper deals with a splitting of dynamic model for vehicle into five sub-models each one describing a subsystems regrouped in three blocks. The novelty of this idea consists in exploiting the splitting dynamic model of vehicle to develop a partial state observers. For the estimation we use the High Order Sliding Mode Observers. The simulation results are achieved by a car simulator.