Energy Storage for Smart grid Prosumers
Figure 1, Different energy storage systems will handle a given situation with different success. The prosumer is here supplied via solar power and the reference gives the energy that the storage system has to handle to fulfil the demand. As can be seen only the Li-ion battery chosen here will be approximately satisfactory in this situation.
Background
Due to the inherent random nature of renewable energy sources (peak power production possibility do most of the time not coincide with the peak power need) we need to store this energy produced “carbon free”. Different storage methods exist (e.g., batteries, flywheels, etc.) and they all have different characteristics and, thus, different advantages and disadvantages. For a given prosumer (i.e., electrical load) with a given renewable power input (e.g., wind, solar etc.) different energy storage systems will be unequally suitable. By analyzing the behaviors of the electrical loads, the renewable energy sources and modeling the vast number of different energy storage systems the most suitable combination can be found. Or the suitability of, e.g., a given battery at a, e.g., farm with solar power can be stated (as illustrated in the figure below).
Aims
In this project, we aim to analyze the suitability of different energy storage systems installed at a prosumer in a smart grid and to state the type and characteristics of the optimal energy storage system.
Approaches
By modeling (and translating) the physical performances of various energy storage systems (charge and discharge characteristics, capability, losses etc.) to electrical circuits we can implement these in available software and include various electrical loads and renewable energy sources. Thus, we can first test the suitability of a given energy storage system in a situation and then use available optimization routines to find the optimal system for that situation. By using experimental setups the models of the energy storage systems can be improved and the behavior better understood (e.g., losses). Challenges are to find models that are realistic in terms of level of complexity but accurate enough compared to experimental data and also to find representative and accurate data from usage of renewable energy sources at various electrical loads.
Keywords
Energy storage, smart grid, renewable energy, batteries, flywheels, CAES, SMES
Research Group
Project leader
Associate Prof. Daniel Månsson
Dept. Electromagnetic Engineering, School of Electrical Engineering, Royal Institute of technology KTH
Other project members
Cong-Toan Pham, Ph.D student
Dept. Electromagnetic Engineering, School of Electrical Engineering, Royal Institute of technology KTH
Yang Jiao, Ph.D student
Dept. Electromagnetic Engineering, School of Electrical Engineering, Royal Institute of technology KTH
Links and references
All results available via https://www.kth.se/profile/manssond/
Additional funding (apart from StandUp for Energy)
The Swedish Energy agency, China Scholarship Council (CSC).
