Role of Cutting Edge Technologies in Smart Grid Implementation

Preface: Conventional electrical grids generate electricity from fossil fuels (oil, coal, and gas). These power plants are far away from the load area, so transmission and distribution systems are required to control the load from the conventional power plant.

The following are the issues that conventional grid systems face.

• Lack of real-time demand information: Because it operates in a one-directional way, it is unaware of the exact demands. To address this issue, a load dispatcher was implemented. However, the load dispatcher does not have real-time data. It is sometimes viable to use specific algorithms to achieve accuracy, although this is usually dependent on historical data. This results in a surplus or shortfall in power generation.
• Transmission and distribution losses: These losses occur because the generation and consumption sites are in different places. These losses vary according on the geographical, environmental, and infrastructure configurations, as well as the operational conditions.
• Harmonics and Distortion: To address the requirement for variability and uncertainty, the world is shifting from thermal to renewable energy sources. The assumption is that both power generation and consumption will remain constant. Solar and wind energy generating technologies, on the other hand, are subject to weather conditions. As a result, this profile modification causes harmonics and distortion in the current grid system. The current transmission and distribution system is not capable of handling such harmonics.

Smart-Grid is electrical networks that integrate digital technologies ,?sensors, software, and robust communication networks to more efficiently meet electricity supply and demand in real time while lowering costs and ensuring grid stability and reliability. It operates by adhering to the principles listed below:

• Bidirectional Flow of Electricity: In contemporary society, even households and factories are installing solar rooftops, and they are also producing electricity to some scale. As a result, electricity must flow in both directions.
• Real-time information access: Variable tariff implementation requires real-time information access in order to manage excess and deficit electricity.
• Support for Distributed Power Generation: To reduce transmission and distribution losses, modest power generation sources are necessary that can offer both local consumption and excess power that can be transmitted back into the grid. Additionally, this can reduce the harmonic affect.
• Self-Monitoring and Self-Healing: To minimize outages or their impact, the grid should be capable of continuous monitoring. Self-monitoring will aid in prediction and prevention, while self-healing will assist in fault isolation and system restoration.

Smart Grid Components: The goal of smart grid implementation is to manage the consistency of power generation from various sources, track power flows from points of generation to points of consumption (even down to the appliance level), and control the power flow or load to match generation in real time or near-real-time. The smart grid consists of the following components.

• Smart meters are electronic devices that capture information about electrical energy, voltage levels, current, and power factor in near-real time and regularly transfer it to electricity suppliers for system monitoring and consumer invoicing.
• Sensing and Measurement System: Many sensors (temperature and humidity) are utilized to detect weather conditions, which have a direct impact and correlation on an area's power requirements. All of these weather conditions have a direct impact on the load and generation profile of that region.
• Phasor measuring system determines the magnitude and phase angle of an electrical physical entity, such as voltage or current ID, by synchronizing with a shared time source. This time, synchronized measurements are critical because if the grid, supply, and demand are not exactly matched, frequency imbalances could result in grid stress, eventually leading to a power outage.
• Integrated communication system consists of sensors, data, an automation system (substation automation, demand response and distribution, automation, and SCADA Energy Management System), and communication. Integrated communication enables real-time control of information and data exchange, which enhances system reliability, utilization of assets and security.
• Microgrid Integration: A microgrid is a small-scale power supply network that is intended to provide power to a local community or set of industries. It permits local power generation in accordance with local rules and includes a variety of small power-generating sources (solar, wind, fuel cells, biogas, and microturbines), making it highly flexible and efficient. It is linked to both the local generating units and the utility grid, which prevents power outages. A microgrid includes distribution generation capabilities, a load balancing controller, an energy storage mechanism, and a point of common connection. Microgrid integration is required to sell extra power generated during the day following energy storage.

Business Challenges and Mitigation

High Capital costs, Price Fluctuation and Regulatory Barriers are the top 3 business challenges. Utilities companies are already started working on that and they are on the right path.

• High capital costs: Smart grids require considerable investments in upgrading or replacing existing infrastructure and equipment with new technology. They also incur additional operational and maintenance expenditures to manage the complex system. Utility businesses are fully aware of the cost of inaction (COI). They understand that bidirectional electricity flow and microgrid integration would not only minimize transmission losses, but will also open up new revenue prospects such as the establishment of an EV (electric vehicle) ecosystem. In the United States, Smart Grid Grants announced a $3 billion grant ($600 million per year for fiscal years 2022-2026) for grid resilience technologies and solutions. Similar funding schemes are underway around the world. Apart from that, utility firms have a defined ROI plan, and as an evolution strategy, they purchased LTE/5G spectrum. Examples include the United States (Ameren, Energy, Hawaiian Electric, SCE, SDG&E Southern Company, and Xcel Energy), France (EDF), Poland (PGE), China (SGCC), Korea (Korea Electric Power Corporation), Japan (Kansai Electric Power), and Bahrain (EWA).
• Price Fluctuation: Fossil fuels are still required to generate the electrical energy needed to power the system. When these countries reduce output of certain fuels, the scarcity of these resources causes fluctuations in prices and availability. The advent of wind farms, solar power production, and other zero-emission types of energy generation, as well as microgrid integration, will help to sustain bidirectional electricity flow. The One Sun, One World, One Grid (OSOWOG) attempt aims to reduce total reliance on fossil fuels. The goal for the OSOWOG program is founded on the universal fact that "The Sun Never Sets." The OSOWOG initiative aims to integrate various regional networks into a single grid that will be utilized to transfer renewable energy power. The bidirectional flow of electricity will help to control price swings. V2G (Vehicle to Grid) is one example of this. During peak hours of power usage, about 92% of all vehicles are parked. So, when a vehicle is idle, the on-board battery can be connected to a neighboring electrical grid using smart communication devices. The goal is to leverage the electricity from idle electric vehicles to help in peak shaving. The vehicle's batteries can be fully charged during off-peak demand hours and discharged at any time, depending on the grid's power requirements. Prosumers (consumers who produce and share excess energy with the grid and other users) are not only key stakeholders in the development of smart grids, but they also play an important role in peak demand management and price volatility.
• Regulatory barriers: Smart grids involve a variety of stakeholders and industries, each with their own set of interests and purposes. They also necessitate adjustments in existing policies and regulations governing the operation and management of the electricity system. That is reason several international collaboration efforts for smart grids are underway to accomplish the Net Zero Emissions by 2050 (NZE) goals. International smart grid partnerships address distinct system needs around the world, with the primary purpose of sharing knowledge and best practices on technology and business models, as well as discussing implementation results in each network partner country. The programs are aimed at enhancing international cooperation in the development of smart grid standards, encouraging manufacturers to produce and export smart grid products, and increasing user acceptability. Existing international collaboration programs on smart grids include the International Smart Grid Action Network (ISGAN), the Digital Demand-Driven Electricity Networks Initiative (3DEN), the Global Smart Energy Federation (GSEF), the International Community for Local Smart Grids (ICLSG..

Role of cutting-edge technologies to overcome operational challenges.

Top 3 operational challenges in Smart-Grid implementation are given below.

• Legacy Support: Smart Grid addresses the compatibility issue between existing equipment and smart grid components. Thus, the replacement of aging power grid components with intelligent electronic components is critical.
• Vulnerability to Cyber attacks: As the Sensors report points out, smart grids require advanced communication networks to convey, process, analyze, and manage massive volumes of data. Unfortunately, this necessity exposes them to cyberattacks.
• Route Instability: To ensure that a smart grid provides a consistent source of electricity to consumers and businesses, electricity providers must solve packet loss, a primary cause of network unreliability. Packet loss happens when data units (known as packets) fail to reach their intended destination. It causes service to slow down, interrupting the network and perhaps generating a loss of connectivity

The above challenges are mitigated with the help cutting edge technologies which are essential for creating a resilient and adaptable grid. These include enhanced sensors and devices, communication networks with edge capabilities, and AI?models. The ultimate goal is to help utilities improve grid management, minimize energy losses, and respond quickly to outages.

• Private LTE/5G with Network Edge Setup: Global utility firms purchased private LTE/5G licenses. The goal is to deploy a network that can support dual-band radio. Intelligent AI models can run on the network edge.This allows them to manage both low-power and low-latency use cases.
• Advance Sensor and Device Integration: Sensors are used to measure a wide variety of physical parameters in power generation, transmission lines, substations, distribution lines, energy storage, and customers. These include current transformers (CTs), voltage transformers (VTs), phasor measurement units (PMUs), merging units (MUs), smart meters, temperature sensors, humidity sensors, accelerometers, rain gauges, internet protocol (IP) network cameras, pyranometers and pyrheliometers (solar irradiance), weather stations, sonic anemometers, partial discharge sensors, gas sensors, ultrasound and ultra-high frequency sensors, torque sensors, discharge rate sensors, load leveling sensors, occupancy sensors, and power quality monitors. The goal is to detect any parameter fluctuations in near real time and manage corrective operations to ensure grid dependability during fault scenarios. Furthermore, the measured data should be consumable by intelligent devices and include a timestamp and sensor position to aid decision-making in smart grid operations. These smart sensors are devices composed of several modules, including the data acquisition module (monitoring and measuring the analog signal), the data conditioning module (converting it into a digital signal), the microprocessor, the GPS-based synchronization module, and the 5G-enabled communication module, as well as various intelligent models to detect anomalies.
• AI/ML Models: AI models are critical for the efficient operation of smart grids. Here are a few examples of AI models that have improved grid operation.
• Load Forecasting (LF) Model: The complexity of scheduling and operating the smart grid is growing as a result of the increased integration of renewable energy sources including solar, wind, and tide power. Contemporary electrical systems depend on LF for planning and operation since it is one of the essential elements that keeps the power system adaptive and stable. Different sublevels are classified as short-term (minutes to hours), mid-term (hours to weeks), and long-term (for years) LF in order to facilitate accurate forecasting. Furthermore, LF may also be impacted by a number of other factors, including the time of day, the season, the event, the kind of customer, and the academic calendar. Mid- and long-term load factor forecasting is typically modeled as functions of past power consumption data, in addition to other variables including weather, customer base, and demographic information.
• Power Grid Stability Assessment Model: The assessment of power grid stability Models include voltage stability, tiny signal stability, frequency stability, and transient stability, which refers to the system's capacity to stay synchronized in the face of significant disturbances while maintaining a stable range of frequencies. The capacity of a power system to remain in an equilibrium state of operation or swiftly transition to a new equilibrium state following a disturbance is known as stability. Precise real-time dynamic power system models are the foundation of these models. Stability analysis is provided via the Wide Area Measuring System (WAMS) and Phasor Measurement Units (PMU).
• Smart Grid Security Model: The smart grid's two-way energy flow and data exchange have exposed it to security vulnerabilities. This can be addressed by implementing private LTE/5G networks. Furthermore, Artificial Neural Network (ANN) and Support Vector Machine (SVM) model techniques are used to detect malicious voltage control actions in the low-voltage distribution grid, while Reinforcement Learning (RL) algorithms are used to conduct security situational analysis for the smart grid.

Conclusion & Next steps

Smart-Grid is assisting utilities in becoming customer-focused businesses rather than merely suppliers of essentials. Customers expect choice, transparency, and tailored energy solutions. To meet these needs, Smart-Grid provides various billing options, real-time access to usage statistics, and simple channels for troubleshooting. Customers often want value-added services that go beyond the realm of traditional products. Utilities must accept these services and change their workflows accordingly. This includes investing in cutting-edge grid infrastructure, such as renewable energy sources, installing EV charging infrastructure, deploying smart technologies, and prioritizing customer demands. Smart Grid technology enables utilities to create a more sustainable energy usage culture, improve customer interactions, and reduce customer churn.