Flexibilty of future energy scenarios

If the Netherlands wishes to achieve an 80% CO2 reduction by the year 2050, technologies such as heat pumps and electric vehicles will be required to replace their fossil fuel burning counterparts. These technologies however have large consequences for electricity networks; not only will the amount of electricity transported over the networks increase, but so will the peak loads, pushing transformers and cables to their operating limits. This is a challenge that network operators are currently facing, and new methods are required to help them prepare for the future. In this thesis the flexibility of future energy technologies with the goal of limiting network loads in the Dutch low voltage electricity grid is investigated. ‘Flexibility’ refers to different variations, control strategies, and combinations of technologies that exist. Focus is placed on eight electric vehicle charging strategies and five types of electric heat pumps. Solar photovoltaics, electric hot water boilers, micro CHPs, and electric heaters as well as the effect of household insulation and thermostat setting are also investigated. The impact on the electricity grid is quantified by creating a testing environment in which the load of transformers and cables can be easily determined for any combination of market penetrations of the above technologies. Three representative low voltage networks are considered: A city, a village, and a countryside neighborhood. Calculations are carried out for a typical summer and winter day with 15 minute intervals. The technologies are modeled as Strand-Axelsson loads to take into account simultaneousness and accurately be able to predict the peak load of any number of users. The testing environment is validated by comparing the results to those obtained by Gaia, a software package specifically designed for carrying out electricity network calculations. Power demand profiles for all technologies are created using different modeling strategies. The electric vehicles are modeled based on mobility data of 50.000 Dutch citizens. Eight control strategies are modeled, examples are: uncontrolled charging, night time charging, and vehicle to grid. To model space heating technologies a Matlab model has been constructed that accurately predicts the heat demand of a household taking into account factors such as household type, insulation, thermostat setting, and outdoor temperature. With the model the power demand profiles of heat pumps and other heaters are created by modeling their control strategies. The electric vehicle and heat pump profiles are verified by comparing the results to measured data obtained from Alliander. The power demand profiles are entered into the testing environment and simulations are carried out. The impact of each technology on transformer and cable loads is quantified and the effects of flexibility are investigated. It is found that uncontrolled use of heat pumps and electric vehicles present problems for the electricity network: market penetrations as low as 20% could cause transformer loads to reach values above 100%. Flexibility options however do exist and can be used effectively to limit network loads. Electric vehicles offer the most flexibility since the charging times are the easiest to control. Heating technologies have limited flexibility but improving household insulation and using the right thermostat settings can reduce network loads. Micro CHPs combine very well with other technologies and can be very effective at limiting the loads caused by both electric vehicles and heat pumps.

Subject

flexibility
electricity grid
electricity network
heat pumps
electric vehicles

To reference this document use:

http://resolver.tudelft.nl/uuid:79801e1e-ef19-4136-963d-c149f11bf56b

Embargo date

2012-02-01

Part of collection

Student theses

Document type

master thesis

Rights

Files

PDF

Laumans_C.J._-_Flexibilit ... thesis.pdf

2.59 MB

Close viewer