The value of smart grids : quantifying the value of the implementation of smart grids for the Distribution System Operator on a district level : a cost benefit analysis – S.J. Barentsz
Introduction This study investigates and values solutions to the challenges that the traditional electricity grid is facing. As the competitiveness of electricity in transport and heating continues to increase, this will further contribute to the electrification of our energy demand. As the peak loads are expected to increase due to this electrification, this will require a different design of our distribution electricity grid. The study therefore questions whether traditional reinforcement is the best alternative to cope with higher peak loads and investigates whether smart grid are a better alternative. To research this subject a method to perform a cost-benefit-analysis is developed that results in the NPV of a smart grid implementation for a specific district in the Netherlands from the perspective of the DSO.
Methodology In order to value a smart grid for a specific district this research focuses on the low voltage grid and uses a case study to determine and quantify the possible effects of smart grids. To quantify the benefits model is developed that is able to simulate the total grid load of this case study. Based on the costs differences between the smart grid and the 0-alternative (the ‘conventional’ solution), the value of a smart grid can be determined. The key difference between the alternatives is flexibility. The smart grid alternative assumes that the load patterns (both production and consumption) can be modified due to the incorporation of load flexibility within the energy system. To this end, the amount of flexibility is determined: in the smart grid alternative flexibility is realized by controlling the activity of household devices and a second alternative incorporates a district storage system to realize flexibility.
Conclusion Implementation of a smart grid resulted in cost savings for the DSO in two of the three delineated scenarios. Storage proved to be the least favorable alternative in all scenarios. The model in this study provides a clear and well substantiated approach to quantify and value required grid investments. With knowledge of the load forecast and potential flexibility levels in all alternatives and scenarios, DSOs have several instruments available to cope with the energy transition. Moreover, the case study results prove that both investment, as well as operation & maintenance costs can be reduced. The magnitude of this reduction is dependent on the alternative and future scenario. With the knowledge on potential savings and future developments, the DSO might rethink their policy and actively steer towards smart grids, creating new business opportunities along the way.
