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24 | 11TH - 17TH MARCH 2016 | UTILITY WEEK Operations & Assets Market view T he highly industrialised European economy requires good quality power supplies – and reliability. Distribution system operators (DSOs) are incentivised to provide this service in a cost-efficient manner within the relevant regulatory framework. At the same time, integration of distributed generation and other technologies such as electric vehicles or energy storage pose chal- lenges to the traditional business and opera- tional processes of DSOs. Smart distribution grids are becoming enablers for endeavours to support changing patterns of power gen- eration and consumption in Europe. An enhanced methodology is necessary to identify cost-effective solutions from a DSO perspective. Such a methodology has been applied within a collaborative research and development project – funded under the European Commission's seventh framework programme – called Discern, the distrib- uted intelligence for cost-effective and reli- able distribution network operation. Discern describes and implements different network solutions to aid future network development (smart grid use cases), and evaluates their technical impact and economic viability. The smart grid use cases applied within Discern have been designed to address a number of common emerging network issues such as optimum medium-voltage network monitoring and automation, real-time moni- toring of low-voltage grids, optimised auto- mated meter reading through virtual data concentration, and identification of techni- cal and non-technical losses. Discern has developed a suite of practi- cal tools that support DSOs at all stages of smart grid system design: frameworks that help DSOs develop and express the detailed requirements and architectures of their smart grid solutions, tools that promote interoper- ability at the semantic level, simulation and optimisation techniques for determining the optimal intelligence in networks, and meth- ods to evaluate the technical and economic performance of a solution. The experiences from Discern provide valuable recommendations to stakeholders that will help promote the efficient develop- ment of effective and replicable smart grid solutions, including enhancements to regu- latory environments and measures that will promote the adoption of standards. The methodology to evaluate the eco- nomic attractiveness of a use case is based on key performance indicators (KPIs) that were defined at the beginning of Discern, with data provided by DSOs from field measurements and/or through simulations. For each use case, performance KPIs were specified to measure technical impact and cost KPIs to provide information on budget and cost structure. These have been supple- mented by supporting data that was neces- sary to use the KPI results in an economic evaluation model using the discounted cash flow method. The data included parameters to define the scope of the model, parameters to monetise performance KPIs, and parame- ters to detail costs, such as life expectancy of hardware/soware, cost degradation, opex and communication expenditure. Revenues are calculated by combining performance KPIs and monetary values; expenditures are calculated by combining cost KPIs, cost parameters and information on the associated equipment deployed at the demo site – from the project characteristics. Revenues and expenditures are calculated as an annual value for the start year and car- ried forward in consideration of supporting data for 20 years. If available, operational effects, such as measurable effects of smart grid solutions on operational processes, are accommodated. As a result, the development of the (discounted) cash flow over time and the resulting net present value (NPV) can be calculated. This provides key information on economic viability, cost-benefit ratio or pay- back period of the use case. Also, to account for project risk, the economic evaluation has been complemented with Monte Carlo simu- lation to assess the project uncertainties, and sensitivity analysis to provide insight into the sensitivity of the NPV with respect to marginal changes of input parameters. However, this approach does not yet incorpo- rate the impact of the regulatory framework under which the use case is deployed. Only a qualitative evaluation of the impact of regu- lation on the net benefits is incorporated in the evaluation, with a focus on the economic regulation of the DSO's costs and revenues. The method is a robust initial approach to evaluate the economic attractiveness of use cases based on KPIs. However, some consid- erations must be taken into account when evaluating economic results: • With regard to innovation projects, it must be acknowledged that costs may not be representative of the solution as eventu- ally rolled out across an organisation's network. For example, procurement may Do smart grids make sense? Alan Birch, Daniel Grote and Katrin Spanka describe a project to evaluate the economics of smart grids – considered essential to support changing patterns of energy generation and consumption. THE DISCERN ECONOMIC EVALUATION METHOD SOURCE: DNV GL – ENERGY Monte Carlo simulation Cash flow/NPV Input Calculation Output Expenditures Expenditures Expenditures Project characteristic Performance and cost KPIs Operational effects Supporting data • General parameters • Monetary values • Cost parameters Time series (TMSE) (calculation of NPV) Sensitivity analysis (Tornado) Start values Start values Revenues Revenues Revenues