metric (RC) and convolutional coding (CC) schemes with orthogonal frequency di- vision multiplexing (OFDM). Based on the proposed approach and the performance results, we have implemented this solution on devices to compare the results for a future deployment.
• Chapter 5 also present another solution for deploying SG applications in substations.
However, the existing cooperative techniques have been first reviewed and analyzed. Since the previously proposed technique concerns single input single output (SISO) communication, this second method is based on multiple antenna communications. In this chapter, we propose a closed-loop coded-multiple input multiple output (MIMO) transmission system. The approach combines the RC coding scheme with CC and max−dmin precoder to reduce both errors of transmission and save energy. The
results presented in this chapter will help to understand how the optimized criterion affects the performance of MIMO systems.
1.3
Contributions
The field of sensor networks is a very dynamic research sector at national and interna- tional level. The application fields are incredibly varied regarding operating environments, measured physical quantities, robustness and latency constraints, and energy constraints. This research topic is mainly in the field of SG. Its principal objective is to develop a com- munication protocol for high-performance sensor networks adapted to highly disturbed environments for diagnostic and maintenance purposes to know the state of the electrical network and interact with essential equipment in HV substations or their neighborhoods. In this thesis, a comparison between the existing models of impulsive noise such as Mid- dleton Class A, Symmetric α Stable, and a recent model (Au model) is made to validate the model for use in our test of efficiency. The performance of existing communication protocol for WSN such as ZigBee is analyzed when the channel is impaired by impulsive noise.
Given the poor results obtained, we proposed a first robust technique to reduce the effects of impulse noise while meeting the requirements of smart grid applications. This approach is based on the concatenation of two error-correcting codes: the RC and the CC combined with the OFDM modulation technique. The benefits of OFDM are very well known in the field of digital communications and its robustness against frequency-selective channels. The RC scheme is a particular coding technique that is widely used in the field of cryp- tography but has proven recently in the field of digital communications. It allows us to correct burst errors while having low complexity.
The importance of synergy with the industry lies in the possibility of experimental val- idation of the work research results. With software defined radio (SDR) platforms, it is possible to implement a physical layer and to have tests with hardware in a real environ- ment. We have investigated the validation of the proposed approach. We fully design and implement a new block namely RC Encoder + W if i M apper in GNU Radio which acts as
a forward error correcting code to mitigate impulsive noise occurring in substations. After showing that using this coding scheme is very efficient in mitigating the bursty nature of impulsive noise by simulations, we now confirm that the same performance are maintained even with various impulsive voltages and experimental scenarios, which confirms the high performance of the proposed approach.
Given the extent of certain Hydro-Quebec HV substations, the first solution may be dif- ficult to exploit. The energy constraints linked to the sensors must always be taken into account. For this purpose, we propose a second solution based on multi-antenna tech- niques (MIMO). MIMO systems achieve both very high spectral efficiency and effectively combat signal fading. The general idea is to take advantage of the spatial dimension of the channel and exploit multiple paths rather than deleting them. MIMO systems are very efficient because they can use all the techniques of SISO transmissions, in addition to their techniques. MIMO systems have several advantages that can be employed to reduce the transmission energy in the sensor networks for the same transmission reliability and rate. However, because of the limited size of the sensor, the direct application of MIMO is difficult. Given the constraint above, the solution is to consider the principle of sen- sors cooperation (or cooperative MIMO) to achieve MIMO transmission. The principle is to form virtual antennas in order to transmit using a MIMO technique. This solution is particularly attractive when very simple nodes are spatially distributed in a multi-path environment. Our contribution is the proposal of a closed-loop coded cooperative MIMO system based on the concatenation of rank metric and convolutional code with max−dmin precoder. The results obtained show not only that the performance concerning BER are improved but also the energy consumption has been reduced.
This work has led to the following publications:
Peer Reviewed Conference Papers
1. N. B. Sarr, H. Boeglen, B. L. Agba, F. Gagnon, R. Vauzelle, “Partial Discharge Impulsive Noise in 735 kV Electricity Substations and its Impacts on 2.4 GHz ZigBee Communications,” International Conference on Selected Topics in Mobile & Wireless
Networking (MoWNeT), Cairo, Egypt, pp. 1-7, April 2016.
2. N. B. Sarr, A. K. Yazbek, H. Boeglen, J. P. Cances, R. Vauzelle, F. Gagnon, “An impulsive noise resistant physical layer for smart grid communications,” IEEE Inter-
national Conference on Communications (ICC), Paris, pp. 1-7, May 2017.
List of Journal Articles
1. A. K. Yazbek, N. B. Sarr, I. El-Qachchach, J. P. Cances, V. Meghdadi, H. Boeglen, R. Vauzelle, “Performance of rank metric codes for interference constrained wireless sensor networks,” IET Wireless Sensor Systems, May 2018.
2. N. B. Sarr, B. L. Agba, F. Gagnon, H. Boeglen, R. Vauzelle, “Analysis and Exper- imental Validation of Efficient Coded OFDM for an Impulsive Noise Environment,”
1.3 Contributions 7
3. N. B. Sarr, Olufemi J. Oyedapo, B. L. Agba, F. Gagnon, H. Boeglen, R. Vauzelle, “Cooperative Closed-Loop Coded-MIMO Transmissions for Smart Grid Wireless Ap- plications,” Submitted to Wireless Communications and Mobile Computing Journal
Chapter
2
Smart Grid (SG) and Wireless Sensors
Networks (WSN)
Contents
2.1 Introduction . . . . 11 2.2 The Smart Grid . . . . 11 2.2.1 Smart Grid Concept and Characteristics . . . 11 2.2.2 Description of the NIST Conceptual Model . . . 13 2.2.3 Conclusion . . . 14 2.3 Wireless Sensor Networks . . . . 15 2.3.1 Description . . . 15 2.3.2 Characteristics . . . 16 2.3.3 Design of WSN: Influencing Parameters . . . 17 2.3.4 Conclusion . . . 18 2.4 The Principle of Transmission System . . . . 18 2.4.1 The Transmitter . . . 18 2.4.2 The Channel . . . 19 2.4.3 The Receiver . . . 19 2.5 Wireless Propagation Channel . . . . 19 2.5.1 Physical Phenomena . . . 20 2.5.2 Coherence vs. Selectivity . . . 22 2.5.3 Diversity Techniques . . . 22 2.5.4 Wireless Channel Modeling . . . 23 2.6 Conclusion . . . . 26
2.1 Introduction 11
2.1
Introduction
Power grids are facing new energy needs, including the development of air conditioning, audio, and video appliances or electric heating. Consumer uses, such as electric cars or heat pumps should amplify this increase, and energy demand is also rising putting pressure on global energy systems. To avoid the constraints mentioned above, energy companies resorted to the use of SG. SG improves the safety of electrical networks. By balancing supply and demand, it avoids over-equipment of the means of production and allows the more appropriate use of electricity storage facilities, available in a limited way. The SG also increases the overall energy efficiency: it reduces consumption peaks, which mitigates the risk of blackouts. The use of this new technology is the best solution because it allows more efficient energy management. To reduce deployment costs and complexity of wiring, the option of WSN seems the most obvious solution. Wireless technologies represent a convenient means of achieving the necessary communication connectivity in substations with significant flexibility and cost advantages over fiber and copper cabling. However, deploying a WSN requires a thorough knowledge of the environment. This chapter aims at reviewing the background of the SG concept, WSNs, and the propagation channel. Section 2 details the SG definition and characteristics. The conceptual model as defined by NIST (National Institute of Standards and Technology) is then overviewed. Section 3 describes the WSNs. It first gives a general definition of the WSN. The characteristics are then detailed. Finally, the parameters which are meaningful for the design of a WSN are reviewed. The principle of a digital transmission system is reviewed in section 4. Section 5 deals with the propagation channel aspects. It first details the physical phenomena. Secondly, a comparison is made between selectivity and coherence aspects. After that, we review the diversity techniques before studying the wireless channel modeling. Section 6 concludes this chapter.