Smart Grid Communication Infrastructure

 Implementation of a Field Area Network Based on IoT Using Smart Grid Communication Infrastructure

1. introduction

Smart grid technology is a game-changing way to improving existing electricity systems. It might be thought of as "technology for all and everything." A smart grid is a network of automated and widely dispersed energy generation, transmission, and distribution. It is distinguished by a full duplex network with bidirectional electricity and information transfer. It is a closed-loop monitoring and response system. A smart grid network connects an electricity distribution system to a network of information and communication. Smart grid technology provides a dependable, efficient, robust, and sophisticated energy distribution system with a plethora of capabilities. The use of renewable energy resources will result in a lower carbon footprint and emissions.

It can be characterized in a variety of ways based on its functional, technical, or beneficial characteristics. According to the United States Department of Energy, "a smart grid uses digital technology to improve the reliability, security, and efficiency (both economic and energy) of an electric system of large generation, through delivery systems to electricity consumers and a growing number of distributed-generation and storage resources." The smart grid's reach ranges from electrification to the internet of everything. The usefulness of smart grid may be imagined for smart agricultural applications, which constitute the foundation of every country's economy.

Chaouchi et al. highlighted possible applications and implementation issues for IoT. The Internet of Things promotes computation, coordination, and communication among diverse devices and network parts. 

As a result, network security and dependability are significant challenges that must be addressed alongside the design and deployment of IoT-based networks and applications. Burhan and colleagues illustrated numerous network aspects, security, and solutions. Kim et al. proposed using visible light communication in Internet of Things-based machine-to-machine and device-to-device interactions. Angrisani et al. suggested an energy optimization and monitoring system for consumer awareness based on message queuing telemetry transport (MQTT). IoT is an IP-based network that integrates heterogeneous devices and hierarchical networks. Interoperability of several communication protocols is a critical need for an IoT-based network. Crioado et al. presented a cyber-physical system integration utilizing an application programming interface for IoT-based applications.

2. Hierarchical Infrastructure for Smart Grid Communication for Smart Farming Applications

The term "smart grid" refers to the integration of electrical and information and communication technologies in order to make the power system more dependable, adaptable, efficient, and robust. It is a smart power grid that integrates diverse alternative and renewable energy supplies through automated monitoring, data gathering and control, and developing communication technologies. The use of a wide range of communication protocols necessitates analysis and optimization based on the needs.These needs may be determined based on the coverage region, application bandwidth requirements, and so on. For agricultural applications, it might be classified as FAN, NAN, or WAN. Various sensors for measuring characteristics such as humidity, temperature, current, flow, and so on can be used. can be used for agricultural field monitoring and control. A communication infrastructure can be used to build an automated watering system. A greater agricultural production may be obtained through smart farming. The communication architecture of a smart grid technology for smart farming is depicted in Figure 1 employing several hierarchical network levels.

Figure 1: Communication infrastructure for smart agricultural applications based on a hierarchical smart grid.

The following hierarchical layers can be used to create a smart grid communication network for intelligent agriculture applications.

2.1 Field Area Network

A field area network can help with agricultural automation. As seen in Figure 2, it comprises of multiple sensor nodes, a smart meter, renewable energy resources and data collecting, and a control system for comprehensive monitoring and management of a smart farm. Smart meters accept orders from the electrical grid and use them to operate various gadgets. Smart farming demands numerous information such as weather conditions, temperature, soil humidity and fertility, source and load conditions for the functioning of various ancillaries, metering data, time of day consumption, auxiliary power, and so on. Wireless sensor networks are used to sense, measure, and communicate these characteristics. A communication backbone can enable full automation of pumping, harvesting, spraying, and other processes.

Pumping, harvesting, spraying, and fertilizer distribution may all be completely automated with the help of a communication backbone. Sensing, measurement, data collecting, monitoring, control, and remote access to field area network characteristics are all part of smart farming. For smart agricultural electric cars, a system for remote monitoring and control of a plug-in hybrid electric vehicle (PHEV) can be built. A PHEV is made up of a gasoline or diesel engine, an electric motor, and a rechargeable battery that can be charged through a power outlet. A field area network is linked to the cloud for web-based monitoring and parameter management. Remote data collecting that is seamless might build an interactive system between researchers, professionals, and diverse stakeholders. Precision farming is based on local circumstances. 

The field area network has a few meters of coverage area. Field area networks can employ IEEE 802.15.1 (Bluetooth), IEEE 802.15.4 (Zigbee), IEEE 802.3 (Ethernet), IEEE 802.11 (WLAN/Wi-Fi), and narrowband power line communication (PLC) technologies, among others. 

Figure 2 shows a field area network.

2.2.NAN (Neighborhood Area Network)

The neighborhood area network (NAN) transmits data from smart meters to the central controller. A few hundred smart meters installed in HANs may be found in NANs. Smart meters are linked to several gateways using NANs. NANs have a coverage area of around 1-10 square miles. NAN requires data speeds of roughly 10-1000 Kbps. For neighborhood area networks, WLAN, cellular technology, and PLC can be utilized.

2.3. Wide Area Network (WAN)

The wide area network (WAN) connects several NANs. Data is collected at numerous collecting locations and delivered to a central controller. The WAN covers hundreds of square kilometers. WAN data rates range between 10 and 100 Mbps. A big bandwidth is required for the administration of a smart grid network across a vast area. WAN is suited for supervisory control and data acquisition (SCADA) systems for monitoring, control, data collecting, and administration of a smart power grid. IEEE 802.16 (Wimax) and cellular technologies such as LTE, 3G, 4G, 5G, EDGE, and GPRS are suitable for wide area network applications.

Geographic information systems (GIS), remote sensing, and the Global Positioning System (GPS) may all be utilized to control smart farming parameters on a field-by-field basis. WAN is appropriate for IoT applications. The Internet of Things enables "machine-to-machine" or "device-to-device" connectivity. Smart farming can benefit from the internet of things in terms of modern crop production practices.

3. Related Work

3.1. Smart Energy System on the Internet

The prototype produced is designed for remote wireless monitoring and control of a smart microgrid system on a field area network. The HTML website was created to monitor and regulate various energy sources. For monitoring and control, the prototype employs IEEE 802.11 and IEEE 802.3 standards. An ethernet shield is used to connect the Arduino Uno to the user interface. For monitoring and controlling the smart power system, a graphical user interface (GUI) is created. The data is received every 2 seconds. The system operates satisfactorily on a wireless local area network with a range of approximately 50 m. The designed prototype was tested using all three energy sources.

The system operates satisfactorily on a wireless local area network with a range of approximately 50 m. All three energy sources were used to test the intended prototype. Sources were assigned sequential priority. The system initially operates on a grid. The load will thereafter be switched to solar and battery power based on the threshold current value. A direct current (DC) microgrid is shown by the prototype. It has the ability to operate in both grid-connected and island modes.

The WPA-PSK security mode was used to test the prototype on a local area network. In the network, a maximum of 254 devices can be linked and regulated. Other encryption protocols that can be used include the wired equivalent protocol (WEP), the wireless fidelity protected access temporal key integrity protocol (WPA-TKIP), and WPA2.

Other encryption protocols are available, including the wired equivalent protocol (WEP), the wireless fidelity protected access temporal key integrity protocol (WPA-TKIP), and WPA2. Different network equipment, such as switches and routers, can be used to extend the network even farther.

A serial terminal application CoolTerm was used to collect real-time data. Depending on their load providing capacities, certain farming machines can run on any of the three energy sources. Figure 3 depicts the architecture of a smart power system's remote wireless monitoring and control. Figure 4 depicts flow charts of the prototype's monitoring and control. 

As demonstrated in Figure 5, the user may monitor data and operate a complete system by entering predetermined instructions on the local network webpage. Figure 6 depicts the prototype's IoT-based monitoring and control. "smartfield.dlinkddns.com" is the address of the website created for the planned system. After the prototype has been tested on the local network, the port may be forwarded to a WAN application. The designed prototype was tested on the website that was created.

Figure 3 depicts the design of a smart power system.

Figure 4: Flow charts for (a) energy monitoring and (b) prototype control.

Figure 5: Screenshot of a smart power system's remote wireless monitoring and control through an HTML webpage.

Figure 6: Website screenshot demonstrating remote wireless monitoring and control of a smart power system.

3.2.Weather Monitoring System

The Internet of Things-based prototype was created for both local and wide area networks. The prototype produced is utilized to measure meteorological characteristics such as temperature and humidity. These variables are critical for agricultural production. The DHT11 sensor is used to detect and measure temperature and humidity. It detects temperature and humidity using a thermistor and a capacitive humidity sensor. These values are sent straight to Arduino Uno's Pin 2. The Arduino Uno has been developed to run a webserver application. An HTML website was created to monitor humidity and temperature. When a client inputs the server's IP address, humidity and temperature are shown on a local network. A server can use the dynamic host configuration protocol to automatically assign

A server can use the dynamic host configuration protocol to automatically assign an IP address to connected clients. The prototype built was utilized to monitor temperature and humidity in a local area network. The Arduino webserver application makes use of an Ethernet shield. Temperature measurements in Celsius and Fahrenheit are included in the prototype. Monitoring humidity and temperature may also be used to move an agricultural load from one energy source to another, as shown in the preceding prototype. For example, if the temperature is low and the humidity is high, the solar photovoltaic system cannot supply the load and must be transferred to the grid to ensure the smooth functioning of farming machinery. IEEE 802.3 and IEEE 802.11 standards are used in the created design. 

The weather monitoring system for field area networks is depicted in Figure 7. The flow chart of the weather monitoring system is shown in Figure 8. Figures 9 and 10 provide a glimpse of the developed system's measurements in Celsius and Fahrenheit, respectively.

Figure 7: Smart agricultural weather monitoring system design.

Figure 8: Weather monitoring system flowchart.

Figure 9 shows a snapshot of the Celsius temperature recorded by the weather monitoring system.

Figure 10. The temperature in Fahrenheit is displayed as a snapshot of the weather monitoring system.