Opportunities and Challenges of Networking Technologies in Smart Grid

Abstract— To make the existing power grid more responsive and intelligent, to incarporate fast emerging DERs, design a real-time pricing strategy and enable the customer to participate in the load reduction program effective communication technology is a primary need. This paper explore the communication opportunities in the HAN—one of the key components of SmartGrid.
Keywords: HAN(Home Area Network), DER(Distributed Energy Resources), WSN(Wireless Sensor Network)
I INTRODUCTION
SmartGrid[1] will integrate the sensor technology, communication technology, alternate energy resources with electric power system, to enable the existing electric network with the abilities of self-healing, interaction, compatibility, integration.[4, 5].Conventional power systems areexperiencing transition from centralized supply side management to decentralized supply&demand side management due to power system restructuring and addition of distributed generations (DGs) with renewable power sources in the past two decades. Therefore load management in the new operating environment becomes more difficult[8].
Home Area Network (HAN) extends smart grid capabilities into the home using different networking protocols. HAN is an important component of the smart grid. It provides energy utilization for both customers and providers. Customers can remotely turnoff the devices based on the real time information from the provider. This enables for the smoothening of the demand curve and better load control.
In the following sections we discuss the prototype implementation of HAN based on ZigBee technology. ZigBee technology is based on the IEEE802.15.4 standard. IEEE802.15.4 is an economic, high-efficiency, low-rate standard for personal area network and peer-to-peer networks, which is working in 2.4GHz, 868 and 928 MHz with two-way wireless data transmission.[6]
I DEMAND MANAGEMENT IN HAN
For the effective generation and transmission of power investigation of power consumption and study of the demand curve is required. In our prototype we can continuously monitor the amount of power being consumed and the accordingly bill the customers. Using linear regression we can estimate the bill at any point of the day based on the consumption till the estimation point. Using the similar technique we can estimate the current consumption before hand at peak hours. Accordingly, the provider can either increase the real-time price or directly implement any of the incentive based programs[7].
A ZigBee Technology in HAN
Zigbee has numerous advantages which makes it ideal for communication in HAN. The most important of them are[9]
1 Low power: In low power standby mode, two AA batteries can be used for 6 months to 2 years.
2 Short response time: It takes 15-30 seconds to to wake up from sleeping mode to access the network.
3 Self-organization: ZigBee uses self-organization method to form a network with flexible topology. Dynamic routing protocol is used to ensure reliable data transmission.
4 High-security: ZigBee uses advanced encryption standard (AES-128) to ensure a high-level security.
ZigBee can also be used for remote monitoring and control of home appliances.
I SYSTEM AND ITS FUNCTIONS
The system consists of current sensors, communication networks, monitoring and controlling equipment and a gateway(or control unit).
The functions of the control unit are[8]:
1 Collect real time power consumption from the power sensors attached to the home appliances.
2 Two way metering function can be implemented to record the sales of power by customer into the grid.
3 Avoid illegal tapping: can be detected by comparing the current usage to the average usage over the past few weeks to months.
4 Display the daily consumption curves to providers and real-time pricing curves to consumers.
5 Predict the bill for the customers according the usage pattern till the prediction point.
6 A GUI which can be used to control the home appliances, select the operating time for individual devices, set timers to switch on/off the appliances based on the real-time price.
7 Provide necessary mechanism for the Direct load control and incentive-based control for effective demand-respnse model.
8 In case of shortage of power, allow customers to choose among the private providers based on the market.
I METHODOLOGY
In this Project we are simulating a Smart Grid environment so that we can have a better insight into How Power Grid actual works , How regional grids are connected , How smart grid protects itself from outage in one region, which leads to increase load in other regions and transmission lines crossing the emergency ratings and causing a Total Black Out. in the system . Firstly we have used NI LABVIEW platform to create a prototype of HAN network . We are using NI 9792 Gateway , NI 3202 WSN node , Electromagnetic relays , UV sensors, ACS709 Current sensors and HAN devices . 2000 W Electric Heaters and 200W bulbs are used to simulate HAN devices . As ACS709 current sensor is optimized to work at 20 Amperes of current , heating devices are needed to draw large currents and bulbs are used to demonstrate how switching is done based on power consumption & central server emergency commands . Fig 1: Price curve for a typical day[8]

In the above figure 1 we can see the real time price curve for a typical day and its peak occurs somewhere in the mid time slot . So we have designed the Billing algorithm in such a way that whoever reduces their power consumption in peak demand time slot should be rewarded by giving incentives & Discount in the Total bill . We also used machine learning algorithms such as Linear Regression to anticipate the demand from the customer side and Generation side should be given enough time to increase their production to meet the demand. V.HARDWARE EQUIPMENT & NETWRORK ARCHITECTURE 1. NI 9792 GATEWAY:
The NI 9792 programmable WSN gateway(as shown in fig.1) is a Real-Time embedded controller with 533 MHz processor, 256 MB DDR2 memory &2 GB nonvolatile storage for local data logging . This high-performance controller features a 2.4 GHz IEEE 802.15.4 radio to communicate with up to 36 distributed NI WSN measurement nodes (in a mesh configuration) each gateway can operate on any of 14 wireless communication channels to increase network size and ensure coexistence with other wireless devices . Dual Ethernet ports , data access Integrated Web (HTTP) and file (FTP) server for remote data access and visualization .By combining the NI Lab-VIEW Real-Time Module with the NI 9792 programmable WSN gateway , embedded applications such as WSN 3202 nodes are deployed to collect measurement data, trigger alarms through SMS or e-mail, and even view monitoring data within a web browser. The WSN gateway coordinates the wireless network, performing functions such as device authentication, message buffering, and network topology administration.The gateway, routers, and end nodes work together to form a mesh network. Measurement nodes can operate as routers or end nodes, providing the flexibility to extend the range of your sensor network. When nodes are configured as routers, they can repeat messages from end nodes and extend network range while acquiring measurement data.
2. NI 3202 WSN NODE
National Instruments wireless sensor network (WSN) platform delivers low-power measurement nodes that have direct sensor connectivity and a 2.4 GHz radio to wirelessly transmit data to a WSN gateway. Each measurement node offers four analog input channels and two to four digital I/O channels that we can configure for input, sinking output, or sourcing output. With the NI Lab-VIEW Wireless Sensor Network (WSN) Module as shown in fig 2, we can customize the behavior of programmable NI WSN measurement nodes. With this module we can optimize node behavior for applications such as customize sample and transmission rates, perform on board analysis or data reduction, respond to digital value changes, perform local control of DIO lines, and even store data to flash memory. The WSN 3202 consists of 4 Analog input channels & 4 DIO channels (sinking or sourcing ) 1-8 pins are the 4 AI channels and their respective ground pins whereas 10-17 pins are the DIO channels & their ground pins . It also consists additional features such as sensor power output 9th pin , which provides 12V,20 mA for driving external sensors and the last pin is DIO power channel which is to be powered for driving output voltage from the DIO channels . Fig 2: Home appliances and the ZigBee node.

3. ACS709 HALL EFFECT CURRENT SENSOR:
The ACS709 consists of a precision linear Hall sensor integrated circuit with a copper conduction path located near the surface of the silicon die. Applied current flows through the copper conduction path (between the IP+ and IP– pins), and the analog output voltage from the Hall sensor IC linearly tracks the magnetic field generated by the applied current. It is to be provided with a continuous single supply voltage of 3 to 5.5 V. The current sensor is to be kept in series with device such that the device current flows through the IP+ and IP– pins and the message (voltage ) signal is to be fed to the analaog input channels of the WSN node (AIO in our case) . Current is calculated by using the formula V io= sensitivity x I ( actual current ) . Sensitivity of ACS709 sensor = 28mv/A.
4. BI-DIRECTIONAL ELECTRO MAGNETIC RELAYS:
Electromagnetic relay consists of a coil of wire wrapped around a soft iron core , a movable iron armature and two sets of contacts .The armature is hinged to the yoke and mechanically linked to one or more sets of moving contacts. It is held in place by a spring so that when the relay is de -energized there is an air gap in the magnetic circuit. When an electric current is passed through the coil it generates a magnetic field that activates the armature, and the consequent movement of the movable contact(s) either makes or breaks (depending upon construction) a connection with a fixed contact. If the set of contacts was closed when the relay was de - energized, then the movement opens the contacts and breaks the connection, and vice versa if the contacts were open.
Relays in our case are used for switching on/off a device the relays are given a 5V supply which is driven by the WSN node .When the 5V supply is given it breaks the circuit and resulting in tripping off the device from HAN network . Switching is controlled by the programmable WSN node which determines when to ON/OFF a device based on house hold power consumption and emergency signals from the central server.
5. ULTRASONIC SENSORS:
Ultrasonic sensors (also known as transceivers when they both send and receive) work on a principle similar to radar or sonar which evaluate attributes of a target by interpreting the echoes from radio or sound waves respectively. Ultrasonic sensors generate high frequency sound waves and evaluate the echo which is received back by the sensor. Sensors calculate the time interval between sending the signal and receiving the echo to determine the distance to an object.
Ultrasonic sensors are used here for replicating motion detection sensors which in turn are used for monitoring the room ,if they didn't detect presence of anyone in the room for a certain span of time we can assume that there is no one in the room and the room can be completely tripped off from the HAN network so by doing this we can save energy which is wasted by the power saving mode (idle mode) of
Air Conditioners & Laptops , PCs ,Heaters as a part of Energy Management scheme (EMS).
Ultrasonic and Current sensor are to powered by using a constant power supply V cc of 5V which is provided by a arduino board or a battery . Both the sensors consist three terminals a V cc supply , Ground (GND) & Message (analog )signal which is to be fed to the analog input channels of the WSN node . VI. SOFTWARE DESIGN
Using the above mentioned Hardware, prototype implementation of Smart Grid Home Area Network is done.Tasks that are accomplished and simulated are Real Time pricing & Billing , Smart home power calculation , Real Time Bill estimator using Linear Regression Model a Machine Learning Algorithm , Advanced Metering Infrastructure (AMI) , Self Healing Mesh Network & Sensor based Home Automation . Firstly power is calculated using the analog samples of current which are fed by the ACS709 Current Sensor in the form of voltage . These values are scaled back to get actual current by using the Sensitivity of ACS709 sensor & the sampling rate of the current samples is determined by the Nquist Rate. As the frequency of the voltage wave is 50Hz minimum number of samples required to recreate the original curve is N >= 2* F , where F is frequency of the signal . So minimum 100 samples are required to regenerate the signal without loss , before analyzing the samples offset voltage in WSN node has to be taken care ,which by experiments found that it is 2.5 Volts. So by the last 100 samples of data RMS current has to calculated and from the power ratings of the devices we can know the Load of the individual device . By calculating the instantaneous power consumption of the individual device and summing it over all the devices we can have Total Power Consumption of the house . By plotting the Total Power Consumption of the house over real time we get the DEMAND RESPONSE CURVE of the individual house by doing it for all the HAN we will get the TOTAL DEMAND RESPONSE CURVE at the Central server .

Fig 3: Instantaneous power consumption.
In Lab view we will provide the customer a User Interface Window so by seeing it he/she can have an idea about the current usage ,Real Time pricing & price of the private entities. So he can adjust his power consumption by switching off devices, which are of low priority or he can buy current from private entities depending on which is beneficial to him . Now after calculating the power consumption , we have to bill the customer by using the real-time price coefficient which we obtain from the server. The server has control over changing the real-time price value, which means the billing should also be done in real-time. We also provided GuI to view the bill at any point of the day(Fig.4).

Fig 4. Total Bill Amount
A Web based server is created using the NI LABVIEW programming which acts as a Central server and the smart meter VI as a Client server . Real Time price and actual Current values are shared among the Client and Central server VI s using the shared variables presuming both are in the same Project . Customer will not have any access for the Smart meter VI he can only see power consumption and Real time prices which are determined by the Central server . Customer has to switch off the devices manually or using the sensors . He is provided with a User interface Website through which he can see the real time data and On/Off a device through internet anywhere from the world .
Central server also tries to anticipate the Demand using the past values of the DEMAND RESPONSE CURVE. Through Machine learning algorithms and incorporating parameters such as area, day & time . So that he can increase or decrease production based on the anticipated demand and try to meet the demand to prevent outages in network .
Prediction of total demand-response using statistical techniques:
By using the data from the demand curves of the previous days we can predict the demand at any point of the day on a particular day. This helps to manage the supply and adjust the real-time price during the peak hours. The technique which we use to achieve this is the linear regression and we use it to model the relationship between the demand and the time.
YI = b1 x1 + b2 x2 + ----------- bp xp where bi's are the coefficients and yi and xi's are the column vectors containing the required data.
Here can be modeled as the total demand and the xi's are the parameters on which the tonal demand depends. In our case for simplicity we can assume it only depends on the time period of a day. We can find the values of bi's using the equation below. B = (X T X)-1 XT Y
After obtaining the bi's we can use them to predict the demand at any given point of time in future.

Conclusion and Future Works
In this project we have modeled a prototype for communication in HAN based on ZigBee Technology. By continuously monitoring the current consumption we can effectively design the real-time price, smoothen the demand-response curve, provide control over home appliances to the consumer, set operating time of a particular device based on the pattern of real-time price curve. In future this project can be extended to monitor individual devices(using sensitive current sensors), implement different real-time pricing strategy based on different Distributed Energy Resources, provide opportunity for the customer to sell the power into the grid.

References

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