A Smart Grid Approach to Sustainable Power System Integration

Many factors can be identified for faster incorporation of renewable energy resources to displace the traditional fossil fuel energy sources. These factors are divided into three different aspects. First is the rapid decline of the cost of renewable energy sources and their associated components. The second factor can be attributed to the increasing pressure to transition from fossil-fuel energy sources which have detrimental environmental effects towards more sustainable energy source. A third aspect can be introduced in countries which are blessed with an enormous amount of fossil fuel resources, where the preservation of these limited natural resources is of paramount importance to the country that holds it. The dissertation includes the Kingdom of Saudi Arabia as the primary case study. However, the algorithm developed is applicable for other geographical locations which share similarities to the kingdom. The kingdom is considered to be one of the countries with an abundance of fossil-fuel reserves. The unique features of Saudi Arabia are primarily the availability of solar radiation and wind speed as well as high percentage of electrical loads which can be controlled such as energy-intensive desalination plants. This feature, in particular, provides a significant driver for renewables to penetrate the electricity generation mixture. With loads that are deferrable, the issue of renewable sources variability can be mitigated and reduced with an optimized operation strategy. Therefore, the research tends to define and model electrical loads by how susceptible they are to the time of service. The types of loads considered are summarized as non-deferrable such as typical electrical loads in which the demand must be satisfied instantly, semi-deferrable loads which they share the same features as the non-deferrable, however, a storage medium is available to store energy products for later usage. This category of loads is represented by a water desalination plant with a water tank storage. The final load model is the fully deferrable load which is flexible in regarding time of service, and this type of load can be represented by an industrial production factory, such as a steel or aluminum plants. The concept of value storage is introduced, where energy can be stored in different forms which are quite different from a typical storage component (i.e., batteries). The justification to start increasing the penetration of renewable sources into the existing grid in countries which have abundant fossil fuel might not be evident. However, the dissertation provides both economical as well as environmental justifications and incentives to approach more sustainable energy sources. The economical and technical evaluation is referred to as the Generation Expansion Planning (GEP). This type of problem is associated with high complexity and non-linearity. Therefore, computational intelligence based optimization methods are used to resolve these issues. Heuristic optimization methodologies are utilized to solve the developed problem which provides a fixable approach to solve optimization problems

A Smart Grid Approach to Sustainable Power System Integration

Many factors can be identified for faster incorporation of renewable energy resources to displace the traditional fossil fuel energy sources. These factors are divided into three different aspects. First is the rapid decline of the cost of renewable energy sources and their associated components. The second factor can be attributed to the increasing pressure to transition from fossil-fuel energy sources which have detrimental environmental effects towards more sustainable energy source. A third aspect can be introduced in countries which are blessed with an enormous amount of fossil fuel resources, where the preservation of these limited natural resources is of paramount importance to the country that holds it. The dissertation includes the Kingdom of Saudi Arabia as the primary case study. However, the algorithm developed is applicable for other geographical locations which share similarities to the kingdom. The kingdom is considered to be one of the countries with an abundance of fossil-fuel reserves. The unique features of Saudi Arabia are primarily the availability of solar radiation and wind speed as well as high percentage of electrical loads which can be controlled such as energy-intensive desalination plants. This feature, in particular, provides a significant driver for renewables to penetrate the electricity generation mixture. With loads that are deferrable, the issue of renewable sources variability can be mitigated and reduced with an optimized operation strategy. Therefore, the research tends to define and model electrical loads by how susceptible they are to the time of service. The types of loads considered are summarized as non-deferrable such as typical electrical loads in which the demand must be satisfied instantly, semi-deferrable loads which they share the same features as the non-deferrable, however, a storage medium is available to store energy products for later usage. This category of loads is represented by a water desalination plant with a water tank storage. The final load model is the fully deferrable load which is flexible in regarding time of service, and this type of load can be represented by an industrial production factory, such as a steel or aluminum plants. The concept of value storage is introduced, where energy can be stored in different forms which are quite different from a typical storage component (i.e., batteries). The justification to start increasing the penetration of renewable sources into the existing grid in countries which have abundant fossil fuel might not be evident. However, the dissertation provides both economical as well as environmental justifications and incentives to approach more sustainable energy sources. The economical and technical evaluation is referred to as the Generation Expansion Planning (GEP). This type of problem is associated with high complexity and non-linearity. Therefore, computational intelligence based optimization methods are used to resolve these issues. Heuristic optimization methodologies are utilized to solve the developed problem which provides a fixable approach to solve optimization problems