This thesis presents challenges and necessary requirements for simulating shared photovoltaic (PV) energy production and appliance consumption scheduling in urban apartment buildings. Such simulations are useful as a tool to better understand the benefits of using PV systems that are collaboratively shared across households and how smart control systems for demand-side management can improve their utilization by reducing the amount of both excess and lack of energy at any time. An overview of factors that influence energy production and consumption in such environments is introduced and details on how these can be processed and represented in simulation software are presented. As part of such simulations, information about the energy production is necessary and this thesis proposes a method for obtaining this information. The method combines mathematical models for calculating how the sun’s angle of incidence on PV panels affect the production at any time and place, with the weather variations obtained from real measurement data from selected households in Konstanz, Germany. For the consumption part, the focus is specifically on automatic appliance load scheduling for washing machines and dishwashers based on the amount of available PV production at any time. Consumption is obtained by extracting and replicating consumption data from the same German households and classifying it into several types of washing programs. Finally, as a result of implementing the established requirements and methods presented, a simulation software called SolarSim has been developed and technical software documentations are provided for this, as well as a software for processing measurement data.