By CasamanScience
To improve the reliability and to widespread rural electrification in emerging countries, it is mandatory to improve the financial profitability and to solve the energy losses of the networks – which represent up to 30% of the energy produced. Technical and non-technical losses are often very high in emerging countries. The technical losses are dissipated energy in the networks, via Joule heating of the conductors (iron losses, copper), in transformers (shunt losses) and via corona effect (ionization of the air under certain atmospheric conditions intensified by the ambient humidity or rainfall). Non-technical losses are financial losses: problems of counting, recovery, billing, bad recovery, tampering, corruption, uncollected debt, inadequate costs and tariffs, illegal connections, theft of electricity, etc…
These result in a significant loss of revenue for electrification companies, that jeopardizes investment and access to energy in the most isolated areas. New cognitive and numerical technologies can play a key role in improving networks [1]. Another solution is the use of renewable energies directly installed in the user or for a group of users forming “smart-grid”. These intelligent networks must indeed take into account a crucial change, the customer is consumer and producer. Thus infrastructures are less expensive, but the management of a dispersed set of facilities is more complex. This article presents the advantages of using networks dedicated to connected objects to optimize the management of a renewable energy station and thus promote such an approach for the electrification of the 21st century.
In the case of electrification by renewable energy stations installed locally at the user’s place, the plant to be managed by the operator is dispersed. The economic models are: a) a purchase of the station with maintenance contract and b) a subscription paid to an energy operator. In these two cases, significant additional costs are attributed to travel for the maintenance of installations and the consumption record due to the dispersion of the stations over a given geographical area.However, in order to optimize such a structure, the use of a radio-frequency (RF) network associated to a communication protocol allowing telemetry is indispensable. Low bandwidth is not a problem because of the low variability of the data over time. Transmission times are minimal, based on “no change, no transmission” for the final mesh and on cyclic interrogation for the central server. The physical / logical configuration of the network ensures the reliability and facilitates the maintenance of the installation.
Fig.1: Example of the different topologies and spatial configurations of object networks.
As shown in Figure 1, in a linear array, failure of a connection results in network vulnerability. In a star or mesh network, a connection can be disconnected without paralyzing the entire network. Moreover, in a mesh network, each node sends, receives and relays the information. This makes these networks robust to failures and avoids sensitive points because if a node is out of service, its neighbors can still relay the information via another path (indirect routing). However the number of connections is higher. The management of these multiple access points is the object of different routing algorithms in order to find the best operating framework for this type of complex communications. In addition, a technical and economic constraint must be added: the communication frequency used between the objects must not disturb other communication modes such as mobile phone (700-2600MHz) or FM radio (70-110MHz). Therefore, these RF communications protocols must be taken into account by the 3GPP (GSM protocol standardization organization) in the 2G, 3G, 4G and soon 5G standards or using so-called free frequencies (without allocated applications).
The architecture of such a network is illustrated in FIG. 2. The RF network routes the information back to a monitoring server. Informed in real time, the energy provider can send maintenance teams as soon as a fault is detected or stop the station voluntarily. All values, voltage, current, subscriber faults or meter refill can therefore be monitored in real time. For low-cost use and optimum mesh density, these networks dedicated to connected objects must have the following characteristics [2]:
– low energy consumption less than 1W / day
– a large range to limit the mesh by base station of the order of the kilometer.
– the security of the information transmitted (coding and redundancy)
Fig.2: Typical layout of a bilateral telemetry network for renewable energy stations. TCP/IP is short for Transmission Control Protocol/Internet Protocol
The encryption of the data received via an algorithm belonging to the provider secures the transmission of top-up codes, the subscriber and network fault codes [3]. The data that characterize the operator’s network are then collected using new technologies and RF communication protocols. The analysis of these data guarantees preventive maintenance, therefore less expensive, by optimizing the travel of technicians and the fight against fraud. The cost of maintaining such a park is greatly reduced. The conventional network technologies available up to now were too costly and had too much energy consumption (see Table 1). This table shows that the consumption increases with the signal flow or range. In general, the higher the frequency, the smaller the range. But the flow rate is also related to the frequency. The higher the frequency, the higher the flow rate.
Recently, RF protocols dedicated to connected objects appear such as Sigfox and LoRa. Indeed, these optimize the power necessary for the transmission and reception of the signal as a function of the distance that the signal must cover and of the desired flow rate. The RF chips of these last 2 networks cost the least: the Sigfox protocol provides a cost of 2€ per module.
Table 1: Comparison of traditional wireless networks with 2 networks dedicated to connected objects (Sigfox & Lora)
In conclusion, the implementation of radiofrequency technology and connected objects in energy systems will provide unprecedented reliability and quality of service. This optimization guarantees effective preventive maintenance, limits logistical costs and ensures optimal operation. This technological innovation will revolutionize electrification campaigns on a large scale while remaining accessible to the populations of emerging countries. The Internet of objects applied to renewable energies will push the energy sector to improve its electrification processes, to launch new products and services, to respond effectively to the needs and requirements of consumers, while improving compliance, reliability of the installations and achieving cost savings.
References:
1)Khedo, K.K., Perseedoss, R. and Mungur, A., 2010. “A wireless sensor network air pollution monitoring system”. arXiv preprint arXiv:1005.1737.
2) Fadlullah, Z.M., Fouda, M.M., Kato, N., Takeuchi, A., Iwasaki, N. and Nozaki, Y., 2011, ” Toward intelligent machine-to-machine communications in smart grid”, Communications Magazine, IEEE, 49(4), pp.60-65.
3)Wang, Y., Attebury, G., Ramamurthy, B., 2006, “A survey of security issues in wireless sensor networks”, IEEE Communications Surveys and Tutorials 8, 2006, pp. 223.
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