Self adapting smart electrical grid

Abstract

Following the invention of electricity the electrical grid system was one of the biggest achievements of the twentieth century. It has been responsible for delivering power to millions of homes and businesses. As the demand for power increases due to the continued modernization of our society the strain on the current power grid is increasing at a steady pace. Since 1982 the demand for electricity has surpassed transmission growth by 25% each year, in essence we are using up more resource then we are generating, [15]. This has led to the system showing signs of weakness in the form of Blackouts. There have been 5 blackouts in the past 40 years out of which 3 of them have occurred in the last 9 years, [15]. At the same time requirements of more environmentally friendly power sources is supplying additional engineering challenges. Case in point, the population of US just accounts for 4% of the world's population but it is responsible for generating 25% of the greenhouse gasses that are currently emitted with the electrical grid system being one of the biggest contributors. In its present state the electrical grid system is also highly inefficient and wastes precious natural resources used to generate this power. If only the grid efficiency is increased by 5% that would be equivalent to removing greenhouse gas emission from 53 million cars, [15]. Ultimately the thing that directly affects consumers is the dollar amount that they pay for this electricity, which has also doubled over the past couple of decades. The present process that uses a centralized control center to balance the grid seems to be inadequate and ageing at a rapid pace. This way of power delivery is now more than 50 years old, it may have been the best that technology had to offer during that time but in today's world of rapid information exchange and distributed parallel processing its seems antiquated. This thesis proposes a solution that is dependent on a more distributed manner in which the grid can be balanced rather than relying on a single control center. This paper puts forward a communication protocol and a communication algorithm that makes the system self-adapting to changing power demands in real-time. The algorithm is designed to prioritize distribution of power locally hence cutting down on the need to transmit power over long distances while reducing the demands on the remote power generation units