Completed projects

2021

Smart charging strategies and optimal PV-EV sizing to increase the combined PV-EV hosting capacity in the distribution grid

The project will be a continuation of Reza Fachrizal’s PhD project research up to now, in which EV smart charging models for a single residential building and a community has been produced, and its impact on the residential LV distribution grid performance and hosting capacity has been assessed. As a continuation, the proposed project will also be extended for workplace charging stations in cities and its impact in the city grid will also be evaluated. The project also aims to collect actual EV charging data from existing EV charging stations (EVCS) operators to validate the commonly used EV charging models.

Solar utilization plans for system and resource effective deployment of photovoltaic systems

Many photovoltaic systems are connected to local electricity distribution networks. An important question is where the systems should be placed and connected for maximum resource and system efficiency. In this project, a method is developed for establishing so-called solar utilization plans by combining solar cadastres with geographical data for various relevant parameters. A case study for Herrljunga municipality shows that a well-planned connection of solar parks is of crucial importance for the utilization of existing infrastructure.

District heating in sustainable future residential areas

The project District Heating in sustainable future residential areas shows what role district heating can play in future residential areas, both based on a resource efficiency perspective and regarding global carbon dioxide emissions. In particular, the project examines the combination of district heating and electricity production through solar cells. The project also highlights the importance of using the right and defined concepts to assess energy and climate performance.

2020

Probabilistic Forecasting for Battery Managment

The purpose of this research project led by RISE is to investigate the conditions for how household batteries should be sized and managed for best usage. The aim is to deepen the knowledge for local storage; how it shall be dispatched and what external services it can provide to the grid. Load profiles from single-family houses are clustered and a PV/battery system is then fitted for each cluster profile. Battery dispatch algorithm is based on artificial intelligence models (AI) for probabilistic prognostication of electrical loads and solar PV generation for optimal battery dispatch.