We had a chat with our partners at Eilat (Israel) to learn more about the simulations which are expexcted to take place in the upcoming months.
In the next months MUSE GRIDS DSM and Multi-energy planning tool will be virtually tested in the Eliat municipality (Israel). Could you tell us a bit more about the simulations which are expected to take place in Eilat?
Muse-Grids energy planning tool is one of the ways Eilat is planning to assess its plans. The tool will serve Eilat on a Macro scale to estimate different scenarios to reduce consumption and to assimilate more RE systems, mainly Solar PV and BIPV. The simulation is expected to evaluate the Hotel area at the North of the Gulf as well as assess the reduction on the demand side by simulating the use of the Gulf of Eilat water as a heat exchange for the hotels chillers. The Gulf of Eilat’s water temperature gets to below 25 degrees with depth, we expect that the use of the Gulf Water will help reducing about 30-40 percent of the electricity consumption of the hotels.
How the city of Eilat will benefit from MUSE GRIDS tools to achieve its energy independence?
Climate change, while typically addressed by national governments, is also being addressed at the city level to circumvent national bureaucracy. As of today, Eilat and the Eilot Region are producing 75% of the daily energy consumption from solar PV. The city aims to 100% reduction during day time by the end of 2022 and to create surplus energy that will be stored and used during night time. As part of its plan, Eilat also prepares an action plan with the help of the Ministry of Energy to develop the ability to disconnect form the national electricity grid. The MUSE GRIDS tools will help the city to evaluate the action plan’s different scenarios and to create a more accurate assessment of the baseline.
What are the main challenges related to it?
Eilat is a tourist city with more than 3 M tourists a year, this creates very high changes in the energy consumption along the year. During the summer the energy reaches a very high demand while in the winter it is much lower. Another challenge is to collect the actual consumption data related to the hotels and other city areas. Also the city lacks knowledge on its daily and hourly use along the year, and this creates a knowledge gap that needs to be assessed by modelling.