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Storage Optimization in Distribution Systems Roger Cremers & Gabriël Bloemhof KEMA (The Netherlands) CREMERS – NL – RIF Session 4 – Paper 0180.

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Presentation on theme: "Storage Optimization in Distribution Systems Roger Cremers & Gabriël Bloemhof KEMA (The Netherlands) CREMERS – NL – RIF Session 4 – Paper 0180."— Presentation transcript:

1 Storage Optimization in Distribution Systems Roger Cremers & Gabriël Bloemhof KEMA (The Netherlands) CREMERS – NL – RIF Session 4 – Paper 0180

2 Frankfurt (Germany), 6-9 June 2011 Need for tool to assess storage solutions  Utilities are faced with increasing number of distributed energy sources. Storage devices can facilitate the implementation of these sources in the power system  The implementation of storage devices in power systems faces the utilities however with a lot a of questions that need to be answered CREMERS – NL – RIF Session 4 – Paper 0180

3 Frankfurt (Germany), 6-9 June 2011 Typical questions  Can a storage system alleviate the problems in my distribution network?  I have a limited amount of money to buy storage systems. What systems should I buy?  I need a certain amount of storage capacity in my power system. Should I buy only one storage device or multiple smaller devices?  Can storage based solutions compete with classical solutions? CREMERS – NL – RIF Session 4 – Paper 0180

4 Frankfurt (Germany), 6-9 June 2011 Too many alternatives to analyse…  Optimizing the location, type and size of mobile storage systems is a combinatorial problem with (too) many possible solutions CREMERS – NL – RIF Session 4 – Paper 0180

5 Frankfurt (Germany), 6-9 June 2011  New planning tool for optimising the application of (mobile) storage systems in electrical power systems  PLATOS can assist to address relevant issues involved with storage applications CREMERS – NL – RIF Session 4 – Paper 0180 PLATOS

6 Frankfurt (Germany), 6-9 June 2011 PLATOS is based on artificial evolution CREMERS – NL – RIF Session 4 – Paper 0180

7 Frankfurt (Germany), 6-9 June 2011 Performance indicator  Performance of each unique solution is indicated by a performance indicator PI = NPV (annual benefits, annual costs) CREMERS – NL – RIF Session 4 – Paper 0180

8 Frankfurt (Germany), 6-9 June 2011 User definable solution space  User defines: What benefits and costs to be taken into account Number of storage types and sizes to choose from Desired storage technology Optimization objective Network constraints CREMERS – NL – RIF Session 4 – Paper 0180

9 Frankfurt (Germany), 6-9 June 2011 Graphical and tabular output  Use of single line diagram to present results graphically  Creation of Excel file containing all relevant results CREMERS – NL – RIF Session 4 – Paper 0180

10 Frankfurt (Germany), 6-9 June 2011

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12 Main features of PLATOS  Optimization of storage application in power systems Optimization of location, size and type Optimization criteria can be changed by the user Monitoring of optimization process  Performance indicators can be defined by the user Definition of points of interest within power system Both technical and economical performance indicators  Graphical and tabular output  Comparison with classical non storage based solutions  User definable load and generation patterns  Tool can be used for each voltage level  Transparant and uniform comparison of storage and non storage based solutions to network problems CREMERS – NL – RIF Session 4 – Paper 0180

13 Frankfurt (Germany), 6-9 June 2011 Questions ? CREMERS – NL – RIF Session 4 – Paper 0180


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