Final Akshada Anand Palnitkar

Optimization methods for integrated electricity-natural gas systems

Supervisor: Dr.ing. Sergio Grammatico
 

Abstract:
Energy systems have been continuously evolving with the advancement in technology. The expected result would be a smooth transition towards clean and more sustainable energy systems which work closely with one another. Since electricity and natural gas are the two most utilized energy sources, there has been quite some research on their independent usage. The focus on using the available energy resources optimally and effectively is a need for energy providers as well as the energy consumers. However, there are different challenges in making these optimal decisions because most of the energy providers have their independent networks. The progress in energy sector has promoted the use of integrated energy systems from different geographical locations. A smart energy system that connects energy consuming sectors to the power grid to improve the synergy between energy production and consumption is referred as integrated energy system or sector coupling. Integrated systems include several large subsystems referred as areas consisting of electricity and natural gas networks. These large systems are connected to one another through one or more connections known as tie-lines and/or tie-pipes and the energy dispatch can be controlled by the area operator. The main intention of an integrated system is that the electricity and natural gas networks are closely linked as opposed to the formerly isolated systems. The interdependence of systems adds to the complexity of the network and calls for new methods to optimally solve this multi-area IEGS problem. New optimization approaches are required to balance the networks as the natural gas network brings a strong non-convexity to the optimal flow problem making it difficult to solve using commercial solvers. 

The goal of an optimal energy flow problem for an IEGS network consisting of an objective function is to minimize the system's overall operational cost while satisfying the constraints for the electricity network, natural gas network and the coupling constraints. The coupling constraints play a critical role in finding the optimal solution since multi-area systems are being studied. This study attempts to provide insights into some of the available methods of relaxation/approximation for linearizing the nonlinear, non-convex constraints, their performance, efficiency, and reliability of these methods for multi-area networks. In this overview, various formulations and solution methods of the optimization problem have been examined. Their performance has been compared based on certain performance metrics to find the best possible method to solve such complex optimization problems. Since the integrated systems usually are extremely large, it is vital to separate them into smaller subsystems to solve the optimization problem efficiently. For instance, the electrical and natural gas networks can be separated based on their physical properties, leaving just the coupling constraints between these regions to be considered. This is known as decentralizing the network. There are different methods used for the decentralized optimization and it is important to study these algorithms for multi-area IEGS. A summary of the features and simulation results of various methods has been provided.

The investigation begins with an introduction of the research problem and the rationale for the investigation. This study emphasizes the significance of relaxation techniques used to relax the non-convexity and studying optimization methods for integrated electricity natural gas systems. The mathematical formulations and optimization strategies utilized to solve the models are explained in detail. The performance of optimization algorithms is assessed based on certain performance metrics. Finally, this thesis concludes by summarizing the primary findings for the best possible optimization method and suggesting future research possibilities in this topic. To determine which approach best fits the OEF problem for IEGS, a thorough numerical comparison of various relaxation techniques, centralized and decentralized scheme of operation must be made. It is imperative to note that these techniques solve the approximated problem, not the original nonlinear, non-convex problem, which would leave some room for errors and hence an area of future improvement.