Exploring PyPSA for Load Flow Analysis using an IEEE Test Bus Study and Optimization Emphasis using a Modified IEEE Test Bus on PV Integration and Sector Coupling

The increasing utilization of distributed energy resources (DER), particularly solar and wind power generation, alongside the deployment of energy storage and changing demand patterns due to the electrification of transport and industrial heating sectors, are not only causing electricity demand to rise but also leading to stochastic dynamics in power flow patterns. This paper demonstrates the utilization of PyPSA (Python for Power System Analysis) for load flow analysis and optimization for handling time-varying solar PV generation and sector coupling. A comparison of load flow analysis between PyPSA and MATPOWER is conducted using standard IEEE test buses of 9 buses. Additionally, a case study of modified IEEE test bus is presented, showcasing the optimization of an energy system with time-series data of solar PV, load, conventional generation, and integration with transport and heat sectors. The findings demonstrate that load flow analysis produces excellent results for each branch. In addition, the lowest costs for electricity and heat demand can also be obtained by power generation on supply and heat production.