Cost-efficient smart metering, a dynamic model for optimization of costs and benefits of smart metering
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Cost-efficient smart metering, a dynamic model for optimization of costs and benefits of smart metering
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Cost-efficient smart metering, a dynamic model for optimization of costs and benefits of smart metering
- 1. Dynamic model for optimization of costs and benefits of smart metering
- 8. Legend PLC 2 nd gen. PLC 3 rd gen. BPL PLC over MV Wired IP DSL CATV Fiber optics Mobitex (1G) GPRS (2,5G) UMTS (3G) LTE (4G) WiMAX (4G) SMS Meshed RF 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Increasing availability Decreasing availability Constant availability
- 10. CO2 abatement at the demand side is cost effective providing opportunities for smart metering Diagram used with kind permission of McKinsey and company
Notes de l'éditeur
- Odd but true: most business cases predict negative results and still smart meters are rolled out. As one representative from a utility regulator stated: I you decide to have a new kitchen installed you don’t calculate a business case for it, do you? Most cost benefit analyses that have positive results are influenced by single variable: energy savings by domestic consumers. The fact whether a business case has a positive or negative value can be manipulated by increasing or decreasing the projected energy savings. The energy savings however are not beneficial to the companies that invest in the facilitation of the savings.
- Sometime back (when working for Kema) I was involved in number of cost/benefit analyses. One was conducted for the Min of Economic Affairs in the Netherlands. During the process it turned out that the four major grid operators could not come to consensus on the way to calculate costs and benefits. The final report presented average values whereas significant variations in costs and benefits were reported by the grid operators. It turned out that a single model for costs and benefits could not be applied for these companies.
- Differentiate in selection of functionality and timing of deployment (departure from ‘now or never’ scenario)