Energy Management System (EMS) Using Internet-of-Things

Electricity Sector – Energy Management System (EMS) using Internet-of-Things (IoT)

The last few years have seen a rapid growth in the global energy sector.  The increase in population coupled with expansion of cities has led to the demand for electricity by leaps and bounds. This explosion in the electric demand requires the power sector to achieve an ideal load-balancing target and also have control over the consumption of energy. Development of energy efficient systems and advanced grid networks are needed by the electricity sector to meet the growing needs. New technologies are needed to meet the ever-expanding electric network as the current technologies may soon be obsolete.  In order to improve efficiency and stability of the electric grid, grid architects have adapted  new systems like Smart Grid (SG) and Distributed Generation (DG) (S. M. Samara, M. F. Shaaban, & Osman, 2019). With global climate change becoming a priority due to emission of greenhouse gases by burning of fossil fuels, developed countries take advantage of the operational and energy measurement systems of smart grids’ to improve the efficiency of their current electric systems, and thus reduce their overall carbon dioxide footprint.

New Zealand has among one of the highest share in generation of renewable electricity in the world. Over the period of past 5 years, more than 80% of the total electricity generated has come from renewable sources of energy like hydro, geothermal, wind and solar. This is due to the abundance in supply of natural energy resources. The last few years has seen an increase in the generation and consumption of solar energy.

Table1 shows the annual electricity generation and consumption using renewable energy resources during the period of 2014 to 2018 (add ref).

 Table 1

Generation and consumption of solar energy has shown a positive growth of more than 30% annually.  This paper is aimed at examining the problems faced by the use of solar energy, the impact electric vehicles (EVs) have on the current grid and proposes a solution to help in load-balancing.

Current Problems:

The increase in emission of greenhouse gases has made global warming a major concern of countries now-a-days.  The burning of fossil fuels to generate energy is a major contributor to the emission of the greenhouse gases. The global hunger for energy can be satisfied by the development of new renewable technologies. There have been the advancements in the field of solar technology but the growth in the field of solar energy is still facing various technical hindrances like low solar cell efficiencies, various economic barriers and low performing systems for load balancing. (Kabir, Kumar, Kumar, Adelodun, & Kim, 2018). The amount of usable energy a Solar panel or solar Photovoltaic (PV) cell is able generate determines how efficient it is. Also a solar panel is completely dependent on solar radiation and can generate electricity only in the presence of sunlight. Keeping in mind wind and cloud movement the solar panels could receive sunlight for a maximum of 12 hours a day. No energy is generated at night. Some hindrances like solar intensity cannot be overcome because the solar panels output is completely dependent on the amount of solar energy it receives. This is big problem in regions without intensive solar coverage.

The digital world around is entirely dependent on the electric power system for its fundamental functioning, thus making the electric power grid one of the most crucial infrastructures. Electricity is generated at a power plant and is then transported to the consumer by a complex system comprising of interconnections between sub-stations, transformers and power lines. High voltage power lines act as roads and carry the electricity from the power plant and sub-stations to the consumer. Based on the journey and distance of the power lines from the power plant to the consumer, transformers are needed to either increase or reduce the voltage of electricity. As the power grid and distribution networks grow, transformers will be needed to accordingly adjust the voltage so that electricity can be safely distributed to the consumer. The demands of the 21^st century have left the current electric distribution system to be complex and overburdened. The power grid has become unreliable and unsecure due to issues like power theft , overloading, fault detection etc. (Telang, Bedekar, & Duchakke, 2019). An unstable power grid will hamper the efficient functioning of transformers “failures can potentially lead to unplanned power outages, in addition to costly and time-consuming repair and replacement” (Mahoor, Majzoobi, & Khodaei, 2018).

Impacts of electric vehicles integration on the distribution system

The concept of e-mobility has gained importance in order to combat the growing energy requirement and climate change due to greenhouse gases. This concept has caused a shift in vehicular manufacturing from the traditional internal combustion engine vehicles to Electric Vehicles (EV). Though environment friendly, the increase in power consumption for charging of these electric vehicles will add load to the current electric grid, thus affecting the performance of the power distribution network. The load imbalance due to EV charging will result in voltage instability, issues of power quality, reduction of power reserves etc. (Deb, Kalita, & Mahanta, 2017). Also when multiple EVs or large scale electric vehicles are simultaneously connected to the grid, it could lead to increase in the grid peak load. Some distribution and transmission networks may not be efficient enough to carry the quality of energy it needs. The power grid will also be affected by the EV’s charging stations. Voltage instability and phase imbalance will result in transformers getting overloaded, thereby causing power loss and damage to the transformer. Below is an extract showing the impact of EV’s on the current power grid (Zhao, Zhao, & Xia, 2015).

Proposed Technology

With the use of technologies such as Advanced Metering Infrastructure (AMI), Internet of Things (IoT) and communication systems a smart hybrid electric grid can be achieved where in renewable energy generation devices like Solar Photovoltaic (PV) can be integrated at the residential level and connected to the current grid.

Internet of Things (IoT) can be defined as a framework that leverages on the availability of devices and interconnection solutions, as well as augmented physical objects providing a shared information base on global scale, to support the design of applications involving at the same virtual level both people and representations of objects (Atzori, Iera, & Morabito, 2017). In layman’s terms in IoT is a system of interrelated and interconnected devices, objects or people with unique identification number (UID) which can communicate information over a network without requiring human-to-computer interaction.  The definition of IoT has evolved over the years due to emergence of new technologies like machine-learning, real-time analytics and virtual environment. From a consumer point of view IoT technologies can be related to the concept of “Smart Homes”. A smart home is software ecosystem where-in multiple devices and appliances (like washing machines, thermostats, and home security systems) can be controlled remotely by a device associated with that system like a smartphone. For example devices like Smart Thermostats which allows the consumer not only to adjust the desired temperature but also monitor their energy consumption in real-time (Ayan & Turkay, 2018). Wearable technologies such as Smart Bands and Google Glass use IoT technologies to communicate with house appliances and also help in monitoring health and vitals in individuals. Some IoT enabling technologies are NFC (Near-field communication), Bluetooth, Wi-Fi, Li-Fi, RFID (Radio-frequency identification) and GSM (Global System for Mobile communications)

Smart Grids are the next generation of electric grids using advancements in information technology in which AMI is a key component. It relies heavily of communication between the connected products and services and thus helps in improving power quality. Based on data generated and analysed from smart meters AMI controls various applications related with electricity and services.  Smart meters along with connectors and the Meter Data Management System make up the AMI (Ghosal & Conti, 2019). This information can also be accessed by the power company for further research and understanding of power consumption in a particular region. On the other hand, users can themselves monitor their power consumption based on the information provided by the smart meter and make a cost –effective electric plan (Yi, Chen, & Chen, 2018).

The solar PV system is one of the most important renewable sources for power generation. Solar energy benefits include environmental safe, surplus availability and low installation cost due to the advanced technology and mass production (Arab, Kedjar, Javadi, & Al-Haddad, 2019). A solar PV converts sunlight (solar radiation) into electricity. A residential PV power system gives the consumer the power to generate some or all of his/her electric demands and storing excess power for future or night-time usage. 

Proposed Use of tech

An Energy Management System (EMS) is proposed which will consist of Power Grid, Central Control Unit, Solar PV and User Interface and Application. EMS is a bi-directional electric network system which not only stores excess electricity but is also able to provide the power grid with electric current.

Electricity generated by the PV cells will reduce the overall load on the grid and be cost efficient and economical for the consumer. An inbuilt transformer will convert the Direct Current (DC) from the solar PV to Alternating Current (AC) which is safe for domestic use. The central control unit controls the amount of energy stored in batteries for back-up or for use during the night-time or power outages. A smart meter gives a consumer more control over the consumption of electricity and costs involved. A Smart Home is designed to incorporate EMS and all the appliances within it are connected using various IoT in a software eco-system (Ricci et al., 2008). Using a mobile application, consumers are able to monitor and control their energy consumption. For example, during the winter season, a smart thermostat can be remotely activated to heating the room just before the consumer arrives. It can also be set to automatically cut off once the desired temperature is acquired. This prevents unwanted usage and wastage of electricity (Ayan & Turkay, 2018). Another example is usage of sensor devices in rooms. The sensor detects the presence of person entering and leaving a room. The sensor is connected to a web application and the user’s phone via the Wi-Fi connection. If the person leaves the room without turning of the electrical appliances, data received from the censor is analysed and a notification is sent to the user’s device encouraging them to return and turn off the respective device (Susanti, Fatrias, Ichwana, Kamil, & Putri, 2018).  IoT enabling technologies such as wireless sensor networks, mobile internet, communication protocols and cloud services will help in connecting the EMS together. The excess power stored during the day, can be used to charge EV’s. Furthermore, it will also be able control the vehicle-to-grid (V2G) system in which the unwanted electricity stored in a vehicle is returned to the grid. The EMS could result in the home becoming self-sustaining and being completely independent of the power grid.

Based on the successful implementation of the EMS, a Mobile Energy Generation and Management System (MEGMS) could also be designed. This system could consist of an EV attached to PV Panels mounted on a shipping container, Lithium-Ion battery array and a bi-directional inverter (Samara, Shaaban, & Osman, 2019). The system would be able to provide electric current to regions of low solar radiation while also satisfying a diverse electric generation grid without affecting the stability of the system.

References

• Arab, N., Kedjar, B., Javadi, A., & Al-Haddad, K. (2019). A Multifunctional Single-Phase Grid-Integrated Residential Solar PV Systems Based on LQR Control. IEEE Transactions on Industry Applications, 55(2), 2099-2109. https://doi.org/10.1109/TIA.2018.2883551
• Atzori, L., Iera, A., & Morabito, G. (2017). Understanding the Internet of Things: definition, potentials, and societal role of a fast evolving paradigm. Ad Hoc Networks, 56, 122-140. https://doi.org/10.1016/j.adhoc.2016.12.004
• Ayan, O., & Turkay, B. (2018, 25-27 Oct. 2018). Smart Thermostats for Home Automation Systems and Energy Savings from Smart Thermostats Symposium conducted at the meeting of the 2018 6th International Conference on Control Engineering & Information Technology (CEIT) https://doi.org/10.1109/CEIT.2018.8751790
• Deb, S., Kalita, K., & Mahanta, P. (2017, 21-23 Dec. 2017). Review of impact of electric vehicle charging station on the power grid Symposium conducted at the meeting of the 2017 International Conference on Technological Advancements in Power and Energy ( TAP Energy) https://doi.org/10.1109/TAPENERGY.2017.8397215
• Ghosal, A., & Conti, M. (2019). Key Management Systems for Smart Grid Advanced Metering Infrastructure: A Survey. IEEE Communications Surveys & Tutorials, 1-1. https://doi.org/10.1109/COMST.2019.2907650
• Kabir, E., Kumar, P., Kumar, S., Adelodun, A. A., & Kim, K.-H. (2018). Solar energy: Potential and future prospects. Renewable and Sustainable Energy Reviews, 82, 894-900. https://doi.org/https://doi.org/10.1016/j.rser.2017.09.094
• Mahoor, M., Majzoobi, A., & Khodaei, A. (2018). Distribution asset management through coordinated microgrid scheduling. IET Smart Grid, 1(4), 159-168. https://doi.org/10.1049/iet-stg.2018.0076
• Ricci, A., Vinerba, B., Smargiassi, E., De Munari, I., Aisa, V., & Ciampolini, P. (2008). Power-Grid Load Balancing by Using Smart Home Appliances (pp. 1): IEEE.
• S. M. Samara, M. F. Shaaban, & Osman, A. (2019). Management of Mobile Energy Generation and Storage System. Conference,  Retrieved from http://ezproxy.aut.ac.nz/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=edseee&AN=edseee.8716012&site=eds-live https://doi.org/10.1109/GTDAsia.2019.8716012
• Samara, S. M., Shaaban, M. F., & Osman, A. (2019). Management of Mobile Energy Generation and Storage System. Conference,  Retrieved from http://ezproxy.aut.ac.nz/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=edseee&AN=edseee.8716012&site=eds-live https://doi.org/10.1109/GTDAsia.2019.8716012
• Susanti, L., Fatrias, D., Ichwana, D., Kamil, H., & Putri, M. V. (2018, 22-26 Oct. 2018). A Configuration System for Real-Time Monitoring and Controlling Electricity Consumption Behavior Symposium conducted at the meeting of the 2018 International Conference on Information Technology Systems and Innovation (ICITSI) https://doi.org/10.1109/ICITSI.2018.8696022
• Telang, A. S., Bedekar, P. P., & Duchakke, A. K. (2019). Emerging Smart Grid Communication Technology for Mitigating Power Distribution Network Problems. Machine Learning Research, 4(1), 1.
• Yi, C., Chen, H., & Chen, Y. (2018, 6-8 Dec. 2018). A Smart Meter Design Implemented with IOT Technology Symposium conducted at the meeting of the 2018 International Symposium on Computer, Consumer and Control (IS3C) https://doi.org/10.1109/IS3C.2018.00097
• Zhao, Z., Zhao, B., & Xia, Y. (2015). Research on Power Grid Load after Electric Vehicles Connected to Power Grid. 36. https://doi.org/10.1109/GDC.2015.14