Search

In recent years, the rising global energy consumption along with the pressure for the race to- wards a rapid decarbonization of the energy economy have led to the emergence of new tech- nologies that reshape the way we generate, distribute and consume energy. Under this spec- trum, many countries are creating policies that foster distributed energy generation. The wide penetration of Distributed Energy Resources (DERs) along with the ongoing liberalization of energy markets and the recent developments in the world of Information Technology (IT) re- quire an extensive reinvention of the way energy systems are organized, communicate and oper- ate withing the energy landscape. As a way of handling DERs, allowing for a larger penetration of Renewable Energy Sources (RESs) and generating more value streams for their owners and other stakeholders involved in the energy regime, the idea of Virtual Power Plants (VPPs) was introduced. A VPP acts as a platform for DERs that aggregates the capacities of various RESs and energy assets together within a unified portfolio with the aim of improving power gener- ation, management as well as connecting those resources with the wholesale energy markets. For fully realising the potential of VPP projects, techno-economical analysis needs to be carried out. Nevertheless, given the wide variety of DERs that could potentially be included in a VPP portfolio, their unique technical characteristics and the integration of various energy markets and regulations, conducting such an analysis could be a quite complex and computationally intensive task. Therefore, for tackling the aforementioned challenges a portfolio modeling and assessment tool was created allowing for the formulation of complex VPP portfolio’s by encapsulating the oper- ation of energy storage, Electric Vehicle (EV) charging points, heat pump systems and thermal storage systems along with RESs while being optimized for Day Ahead market participation. The tool consists of two main modules, an interactive data bank that serves as a data driven asset modeling toolbox and a two-stage stochastic Mixed Integer Linear Programming (MILP) optimizer that simulates the operation of the portfolio on a given use case. The operation of the VPP is then assessed by generating and tracking numerous Key Performance Indicators (KPIs). Use cases were conducted to verify the accuracy of the proposed software and highlight the operation of a portfolio within different seasons using data related to buildings and RES units located in the Netherlands for the months of January, April, July and October. Results demon- strated strong alignment of VPP’s financial performance with the weather due to the differences between consumption and generation between warmer and colder weather. The total profit was found to be 1259.86€ for the month of July, 959.61€ for the month of April, 534.49€ for the month of October and 196.35€ for the month of January. Objectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant