Smart beneficial with the ongoing rise of renewable

Smart Grid is a technological advance power distribution system which continuous reads and predicts the demand, Usage and production needed. This system works on two-way communication of consumers and the distributors and between the distributors and power generating companies. The system is also beneficial with the ongoing rise of renewable power and its implication of continuous grid matching levels. The system of Smart Grid uses several sensors and an advanced level of communication between the meters and controlling units. The power meters would be generating more than 100 TB of data daily for almost a small area of 200 houses. Due to this we need Big Data applications to read and analyse the real-time data and reach economically beneficial forecasts. These forecasts will be benefiting both the consumers and suppliers in different ways. We will be studying how such a smart system can be implemented and the challenges it will face.

 

Key words: Smart Grid, Big Data, Digitalization, Utility Optimization

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Introduction

The power gird is a system which connects the consumers of electricity to the generators. This grid contains a lot of different equipment which enable the transportation of power which we know as transmission from the site of generation to the point of consumption. This equipments are usually large transformers, heavy high-tension cables, and different type of safety and protection devices. India is a power-hungry nation with an ever-growing need for power consumption. Out of the 1.4 billion people without electricity 300 million are from India. With such figures the nation is always trying hard for new technologies to achieve a surplus power generation stage where all its citizen are able to consume electricity as per their needs.

Recently, the electricity consumption has changed in practice and in nature worldwide. The electricity uses are evolving: positive energy buildings, electric mobility, variable intensity urban lighting, storage batteries, etc. The electricity production modes are also evolving thanks to the development of renewable energies and the transformation of the energy mix. The electrical system must therefore evolve towards greater reliability, efficiency and flexibility in order to better take into account the development of new uses and to preserve the balance between consumption and production in a changing energy landscape. Smart grids become a real solution to these concerns, by introducing Information and Communication Technologies (ICT) into electricity grids and integrating efficiently the actions of all users (producers and consumers) to guarantee a sustainable, safe and cost-effective supply of electricity.

Smart grids ensure efficient connection and exploitation of all means of production, provide automatic and real-time management of the electrical networks, allow better measurement of consumption, optimize the level of reliability and improve the existing services which in turn lead to energy savings and lower costs. The implementation of smart grids features leads to a very large increase in the volume of data to be processed due to the installation of smart meters and various sensors on the network and the development of customer facilities, etc. For example, a smart meter could send the consumer energy usage every 15 min, so every million meters can generate 96 million reads per day instead of one meter reading a month in a conventional grid. So, in addition to energy management, smart grids require great data management to be able to deal with high velocity, important storage capacity and advanced data analytics requirements.

 

Smart Grid

We first consider the reasons for development of smart grid and then discuss what is the innovative solution it provides.

Conventional grid problems:

Presently, the grid is facing a multitude of challenges that can be outlined in four categories. First there are infrastructural problems since the system is outdated and unfit to deal with increasing demand. As a result, network congestions are occurring much more frequently because it does not have the ability to react to such issues in a timely fashion. Ultimately such imbalances can lead to blackouts which are extremely costly for utilities especially since they spread rapidly due to the lack of communication between the grid and its control centres. A second flaw is the need for more information and transparency for customers to make optimal decisions relative to the market, to reduce their consumption during the most expensive peak hours. Finally, a third problem is the inflexibility of the current grid, which can’t support the development of renewable energies or other forms of technologies that would make it more sustainable. The fact that renewable sources such as wind and solar are intermittent poses a significant problem for a grid that does not disseminate information to control centres rapidly. These problems are addressed by the smart grid through improved communications technology, with numerous benefits for both the supply and demand sides of the electricity market.

Smart grid is defined as an intelligent network based on new technologies, sensors and equipment’s to manage wide energy resources and to enhance the reliability, efficiency and security of the entire energy value chain. The main advantage of smart grids is the ability to better integrate renewable energy sources into the system and supervise energy consumption and production thanks to a bidirectional flow of energy and data between power generation, distribution and consumption. Power generation is the first step in smart grid value chain, it includes power sources such as nuclear, hydropower and renewable and it relays on wide area monitoring and control technologies to communicate with the next step called power distribution. This later, is based on a proximity network that connects consumers with the electricity grid and transmits data using advanced metering infrastructure. Power consumption is the last step on smart grid value chain and it involves the users of electricity, both residential and industrial. It is increasingly common for the consumer to generate electrical energy using alternative energy production methods and hence it is very important to supervise their consumption and production to optimize the service.

Fig.1 Shows a typical Smart Grid infrastructure and the various key components built in it.

Benefits of Smart Grid

There are various benefits of a smart grid network some of which are:

·         Better facilitate the connection and operation of generators of all sizes and technologies.

·         Allow consumers to play a part in optimizing the operation of the system

·         Provide consumers with greater information and options for choice of supply.

·         Significantly reduce the environmental impact of the whole electricity supply system.

·         Maintain or even improve the existing high levels of system reliability, quality and security of

·         Supply and Maintain and improve the existing services efficiently and Foster market integration.

·         Reduced operations and management costs for utilities, and ultimately lower power costs for consumers

·         Reduced peak demand, which will also help lower electricity rates

·         Increased integration of large-scale renewable energy systems

 

 

 

Big Data

 

“Big Data” tends to refer to the use of predictive analytics, user behaviour analytics, or certain other advanced data analysis methods that extract value from data, and seldom to a size of data set. Big data is data sets that are so voluminous and complex that traditional data processing application software is inadequate to deal with them. There are three dimensions to big data known as Volume, Variety, and Velocity. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy. Analysis of data sets can find new correlations to spot business trends, prevent diseases, combat crime and so on. Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet search, urban informatics, and business informatics. For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration. Big data uses inductive statistics and concepts from nonlinear system identification to infer laws (regressions, nonlinear relationships, and causal effects) from large sets of data with low information density to reveal relationships and dependencies, or to perform predictions of outcomes and behaviours. Big data has four characteristics these are also knows as “4Vs” of that make any data ‘big data’. These are Volume, Variety, Velocity and Veracity.

·         Volume – it is the huge amount of data that must be processed to do valuable analysis.

·         Variety – it is the different data types present in the data pool to be processed.

·         Velocity – the speed at which new data is being generated.

·         Veracity – Uncertainty of data i.e. whether the data coming is reliable or not.

 

 

Smart Grid and Big Data

Big data can be used in smart grid for many different analysis. We can analyse the consumption patterns in an area to determine there daily peak load. We can analyse the quality of power being generated from different sources and make an optimised mix which is high on reliability, etc. The generators can analyse how much they will be able to sell on a given day and take managerial decisions on the basis of data. Now we look into how big data and smart grid can be integrated.

Big data analysis needs data sources for continuous flow of data into the system. There are distinct data classes according to the type of extracted values: (i) Operational data which is the electrical data of the grid that represent real and reactive power flows, demand response capacity, voltage etc. (ii) Non-operational data is not related to grid power but it refers to master data, data on power quality and reliability etc. (iii) Meter usage data is another kind of data associated to power usage and demand values such as average, peak and time of the day etc. (iv) Event message data comes from smart grid devices events like voltage loss/restoration, fault detection event etc. Finally, (v) Metadata, which is used to organize and interpret all the other kind of data. All these data are collected from several sources such as meters, sensors, devices, substations, mobile data terminals, control devices, intelligent electronic devices, distributed energy resources, customer devices and historical data. 

The grid collects data from different sources and stores it as a huge quantity of dataset that should be easily consumable for analytics. Analytics has a critical role to make the grid more intelligent, efficient and gainful. Various kind of analytics in smart grids are: (i) signal analytics which is based on signal processing, (ii) event analytics which focuses on events, (iii) state analytics which help to have a vision about the state of the grid, (iv) engineering operations analytics which is responsible of the grid operating side, and (v) customer analytics which process customer data.

 

There are several models that can combine the various kind of the previous analytics classes such as descriptive, diagnostic, predictive, and prescriptive models. Each model describes an operation side of the grid. Descriptive models are used to describe customers behaviours in demand response programs and provide a basic understanding of their practices. After customers description, diagnostic models come to understand customers behaviours and analyse their decisions. All these previous models are useful to make predictive models to predict customers decisions in the future. Finally, there is prescriptive models which are the high level of analytics in smart grid, because they affect marketing, engagement strategies and the decisions to make.

Customer analysis can reveal their demand profiles, demand response, diversion analytics and customer segmentation. Event analytics can tell us where an event occurred or will occur, its classification and correlation with other stakeholders and hardware. Engineering operation analytics will give operational effectiveness, system performance and load trends & forecasts. The engineering analysis is most useful for power generators. 

Fig. 2 Customer data analytics structure and what all methods will be used for it.

Big Data processing can be done in two manners: The first is batch processing, which process data in a period and is used for data processing without high requirements on response time. The second, is stream processing and is used for real-time applications. This kind of processing requires a very low latency of response.

 

Smart Grid and INDIA

Indian power sector is under great pressure from all its stakeholders be it regulators, consumers, generators or distributors (DissComs). The regulators want to build up higher capacity of environmental friendly non-conventional power sources. The consumers wants better quality of power and in many places even the basic that is a power connection. The generators are unable to make profits from there investments due to the inefficient operations of there plants. The distributors are the ones in most loss as Indian power transmission companies make more than 30% transmission losses. The companies want to reduce these losses, provide customer better services and earn profits. As the country is going towards digitalization of many industries the power industry is one which is being left behind. Smart grid can be of great use as it would be able to provide solution for many different problems which the industry is facing.

Benefits of smart grid possible in India:

The business cases in Indian smart grids are present in various forms, such as:

·         Accurate and well-timed meter reading enables an intervention for loss reduction.

·         Remote connection disconnection of consumer load.

·         Accurate temper alert such as sanctioned load violation, DT overloading

·         Rooftop solar power speeds up a shift to green energy and produces consumer cost savings in the long run.

·         Time-based pricing (Time-of-Use Tariff) signals the consumer to be more dynamic. The Indian Electric Vehicle (EV) rollout requires a functional charging infrastructure – and its management.

·         Distribution Companies (DISCOMs) provide the anchor infrastructure for smart grids and cities creating a need for value added services and new business models. However, there is critical need to establish business cases for self-finance of these investments.

The efforts for the development and deployment of Smart Grids in India were being carried out through India Smart Grid Task Force (ISGTF) and India Smart Grid Forum (ISGF) since 2010 under the aegis of Ministry of Power (MoP). During the implementation of 14 Smart Grid Pilot projects in State utilities, it was felt that smart grid efforts required urgent concerted focus for which it was necessary to create a comprehensive institutional arrangement capable of dedicating the manpower, resources and organizational attention needed to take it forward. A Smart Grid Vision and Roadmap for India was approved by the Ministry of Power in August 2013 which also envisaged the launch of a National Smart Grid Mission (NSGM) having its own resources, authority, functional & financial autonomy to plan and monitor implementation of the policies and programmes prescribed in the roadmap. The current pilot projects are going on in Karnataka, Punjab, Himachal Pradesh, West Bengal, Tripura, Haryana, Assam, Telangana, Puducherry, Uttar Pradesh, Gujarat, Rajasthan, Maharashtra and Chandigarh. The total number of consumers covered under this pilot project are 10,27,313 (Ten Lakh Twenty-Seven Thousand Three Hundred Thirteen). Most of these projects are under the control of POWERGRID corporation of India a government organisation.      

 

 

 

 

Conclusion

 

Smart Grids are most comprehensive technology during recent years and it has been grown rapidly because of its benefits. It has many features and the transition to a fully implemented smart grid brings a host of benefits in an often-symbiotic relationship: GRID OPERATORS will enjoy a quantum improvement in monitoring and control capabilities that will in turn enable them to deliver a higher level of system reliability even in the face of ever-growing demand. UTILITIES will experience lower distribution losses, deferred capital expenditures and reduced maintenance costs. CONSUMERS will gain greater control over their energy costs, including generating their own power, while realizing the benefits of a more reliable grid. THE ENVIRONMENT will benefit from reductions in peak demand, the proliferation of renewable power sources, and a corresponding reduction in emissions of CO2 as well as pollutants such as mercury. “Smart grid” enabled distribution could reduce electrical energy consumption by 5-10%, carbon dioxide emissions by 13-25%, and the cost of power-related disturbances to business by 87%. (Source: The Electric Power Research Institute). Smart grid enabled energy management systems to have proven in pilots to be able to reduce electricity usage by 10–15%, and up to 43% of critical peak loads. (Source: The Brattle Group, SMUD and PNNL.) The Smart Grid vision generally describes a power system that is more intelligent, more decentralized and resilient, more controllable, and better protected than today’s grid.

With India looking forward to a centralized grid and increase its production through renewable power utilities the need for a robust distribution system is seen. Smart grid can provide solution to this, implementation of such a technology will be easier when the nation is in process to upgrade its current user on digital meters. The country is still behind in providing a power to every citizen and hence concept such as micro-grid can be tested with controlling through smart-grid.