The Storage Capacity of Co Generation. Christof Wittwer Fraunhofer Institute for Solar Energy Systems ISE, Germany EuroSolar 2006

Transcription

1 The Storage Capacity of Co Generation Christof Wittwer Fraunhofer Institute for Solar Energy Systems ISE, Germany EuroSolar 2006

2 Context Distributed Generation and CoGen -> Vision of Smart Grids and Islanding Control Concepts for DG -> PoMS Prototype Electrical and Thermal Storage Devices -> Autonomous Operation Optimization -> Schedules for CoGens Results 2

3 CoGeneration in a Building Electricity and Heat: Gas, Fuel, Pellets, Biogas etc Invest and Return Feed In Tariffs Heat Demand Operation Thermal Storage: Thermal Peak Shaving fossil or bio fuel heat electricity Use of Thermal Storage Devices Decoupling of Heat and Electricity Production 3

4 CoGen with Local Heat Network combination with gas fired heater CoGen for base load Usually modulated heater Local heat network Problem: at summer time less heat demand Quelle: ASUE 4

5 Annual Load Duration Curve Profitability 5000 h operation time Only Base load Heat load leaded operation Constant feed in tariff in germany (KWK) 5500 Betriebstunden/Jahr 5

6 CoGen Operation at Summer Time: Short phases for cogen operation, strong switching Thermal energy generation with conventional heater Need for thermal storage 6

7 Monovalent CoGen Operation CoGen plant with thermal storage devices Large peak power with a well sized CoGen needed, profitabily problematic Storage device leads to extended operation time of CoGen, and allows integration solar thermal systems Quelle: ASUE 7

8 Monovalent CoGen Operation with Thermal Storage Less operation time Thermal storage needed (or strongly modulation) Risc of storage losses In der Praxis 2900 Betriebstunden/Jahr 8

9 Monovalent Operation - Schedules Minimum operation time of CoGen Storage: state of charge (SOC) Optimization problem Optimized Controller e.g. POMS Power Flow Management System 9

10 CoGen Operation Controlled by Heat or/and Electrical Load CoGen active on electrical demand. Heat and electrical load profiles not really correlated Discoupled by thermal or electric storage device Optimized Controller linear programming for optimized schedules 10

11 Management System POMS Am Steinweg MVV Energie 11

12 Management System POMS Am Steinweg Networked Operation System Based on Intelligent Embedded System Deviced PCU 20 kv PCU: Central Industrial PC (Transformer Station) PIB: Interface Boxes for Component Management control prognosis 400 V Web based Access to Weather and Tariff Data PV + load load fuel cell business CHP battery 12

13 Management System POMS Am Steinweg DG-Components: CoGen 30 kw el / 45 kw th 2 Boilers a 345 kw PV Generator: 28 kwp Thermal Storage 3000 l 13

14 Optimisation Problem 14

15 Simplified Storage Model C sto [] t [ 0,C sto_max ] P charge P discharge [] t [ P, ] min_charge P max_charge [ t] [ P, P ] min_discharge max_discharge 15

16 Cost Functions Operation costs (without invest) Fuel costs maintenance costs delivery costs Feed in / purchasing / CoGen-KWK payment Cost Peaklevel (demand rate) Cost Optimization Problem min[ cost] min[ C el _ grid el _ grid + C Trafo_in BHKW el + C Boiler trafo_out G BHKW C = E c E gain + P c C C BHKW Boiler E = η EBoiler = η BHKW _ el el c fuel ct fuel + E G g BHKW = EBHKW _ el + E Boiler KWK BHKW _ el c c el maint_ Boiler ] peak maint_ BHKW peak 16

17 Results of Optimal Control: CoGen Schedule Thermal storage management Electrical and thermal optimization by costfunction Electrical peak load in the evening, thermal base load in the night CPLEX optimization software 17

18 Results of CoGen and Thermal Storage Use Simulation results of one year operation with and without thermal storage: operation time of CoGen 5100/3140 h Starts: 490/501 Thermische Leistung [kw] 18

19 POMS Operation with Thermal Storage: Web Interface Power Flow Management System (PoMS) with distributed intelligent device controller (PIB) Java Based Access to Central Unit PCU Secure Web Integration (Linux, SSH, etc ) 19

20 Management Battery Systems: Peak Shaving and Islanding Cohen Schedules Battery Dispower Results 20

21 DG-Management with Battery, CoGen, PV Smart Grid Battery Peak Shaving 21

22 Optimized 22

23 POMS Operation at Testsite Am Steinweg - optimized schedule operation - CoGen, PV,BAT - HT / NT Tariff 23

24 Conclusions Thermal storage for DG needed and higly relevant for market New prediction and grid system models are needed Optimal control for distribution grids (MW level) Interaction of centralized and local system controllers are needed R&D project Badenova Freiburg 24