Agent-based simulation and simulation optimization approaches to energy planning under different scenarios: A hospital application case

Abstract

In complex multi-energy systems, one of the main goals is that combining optimal circumstances to acquire minimum system cost as decreasing energy consumption without an outage of energy supply. This study mainly has focused on flexible solutions that include the controlling of a multi-energy system and its components such as electricity, heating, natural gas, and converters to minimize the overall system cost and reduce carbon emissions by observing of demand whether is satisfied. The technique of agent-based simulation and simulation optimization approaches has been adopted as solution methods for tackling these difficulties. As a case study to implement the flexible solutions, the multi-energy system of a large hospital complex placed in Turkey was selected. These flexible solutions based on the integration of cogeneration and photovoltaic systems to existing energy infrastructure have been simulated under multi-tariff and singe-tariff electricity price strategies for different years. The used data in the model has been gathered from the hospital electricity and natural gas bills, the energy projects realized for the hospital in the past, and other various sources including PVGIS database, Turkish State Meteorological Service, commercial cogeneration/PV panel manufacturers, and publicly available reports. The results indicate that the effective presence of cogeneration and photovoltaic is notable in the decreasing total system cost taking into consideration also lower carbon emissions. Once current system was simulated, it was compared with other proposed possible configurations with different two scenarios. Based on the simulation models that were optimized with different metaheuristics such as genetic algoritm, the economic results show that the both of two scenarios can be profitable (simple pay back periods around 5.28 and 6.6 years respectively) even without any public funding. Furthermore, it was determined that cogeneration-based scenario-2 provided a 12.35 % reduction in carbon emissions compared to the base scenario, while scenario-3 provided a 16.94 % reduction compared to the base scenario, and both scenarios are proven to be quite environmental friendly.