NATIONAL TECHNICAL UNIVERSITY OF ATHENS CHEMICAL ENGINEERING SCHOOL COMPUTATIONAL FLUID DYNAMICS UNIT DEVELOPMENT OF AN EFFICIENT REAL-TIME OPTIMIZATION STRATEGY FOR A HYBRID POWER GENERATION SYSTEM CONSISTING OF PHOTOVOLTAIC ARRAYS AND FUEL CELLS (PV-FC) P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos ENERTECH 2007, 18-21 October, Athens P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Objective of the Study Development of a Global Solar Irradiance Prediction Model on horizontal surface  Prediction of Photovoltaic Power Generation Development of an optimal-decision strategy for a Renewable Energy System with Hydrogen Storage based on the Model Predictive Control rolling horizon concept P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Part I: Global Solar Irradiance Model P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Part I: Global Solar Irradiance Model P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Part I: Global Solar Irradiance Model P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Part I: Prediction of the PV Power Generation Global Solar Irradiance on tilted surface Location data, astronomical data, slope of the PV Array Global Solar Irradiance on horizontal surface Neural Network Model Sun Ambient Temperature PVOut=f(GSIT,Tamb) V I Photovoltaic Αrray P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Proposed Hybrid Power Generation System Purchased Electricity Part II: Hybrid Power Generation System Proposed Hybrid Power Generation System Consumer Fuel Cells Metal Hydride Tanks Electrolyzer Purchased Electricity PV(kW) PE(kW) CS(kW) SE(kW) Elin(kW) Elout(m3/h) FCin(m3/h) FCiout(kW) INV Sold Electricity Photovoltaic Array P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Part II: Formulation of an LP optimization problem Decision Variables Energy consumed by the electrolyzer Purchased/Sold Electricity from/to the grid Amount of Hydrogen consumed by Fuel Cells Stack Amount of Hydrogen stored in Metal Hydride Tanks Objective Function to minimize Cost of electricity Energy produced by the Photovoltaic Arrays Consumption Profile Data Formulation and solution of a Linear Programming Problem P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Part II: Equations-Constraints P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Part II: PV Power Generation-Load Profile (Deterministic) P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Part II: Specifications of installed hybrid systems 1st Scenario 2nd Scenario PV array 5kWp Electrolyzer 0.25Nm3/h 0.5Nm3/h Fuel Cell Stack 1.2kW Metal Hydride Tanks 5m3 P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Part II: Decision strategy for two different scenarios of a RESHS: Electrolyzer 0.25Nm3/h-0.5Nm3/h P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Part II: Purchased electricity as a function of the hydrogen storage capacity (Electrolyzer 0.25Nm3/h-0.5Nm3/h) P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Part II: PV Power Generation-Load Profile (Updated) P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Part II: Specifications of the installed hybrid system 1st Scenario PV array 5kWp Electrolyzer 0.25Nm3/h Fuel Cell Stack 1.2kW Metal Hydride Tanks 5m3 P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Total Purchased Energy (kWh) Total Discarded Energy (kWh) Part II: Deterministic and updated decision strategies for scenario 1 with true PVOut and CS profiles Total Purchased Energy (kWh) Total Discarded Energy (kWh) Deterministic schedule using true PVOut and CS temporal profiles 18.4940 16.6175 Updated schedule using true PVOut and CS temporal profiles 9.9677 8.1868 P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Conclusions Development of a prediction model for the GSI daily profile on horizontal surfaces based on the RBF neural network architecture Forecasting GSI on the tilted surface of the PV array, using the following information: the GSI prediction on horizontal surfaces, astronomical and geographical data and the slope of the PV array Estimating the electrical energy produced by the PV array, given the ambient temperature and the GSI on the tilted surface Development of a model that realistically describes the performance and the constraints of the hybrid system Formulation and solution of an optimization problem that minimizes the cost for purchasing electrical energy. The formulation takes into account the estimated photovoltaic power generation over a future prediction horizon and a profile of the energy demand over the same time horizon P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Finally the proposed model.. ..may prove to be a very useful tool for optimal decision making in hybrid power generation systems which combine RES and hydrogen technologies P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

NATIONAL TECHNICAL UNIVERSITY OF ATHENS CHEMICAL ENGINEERING SCHOOL COMPUTATIONAL FLUID DYNAMICS UNIT DEVELOPMENT OF AN EFFICIENT REAL-TIME OPTIMIZATION STRATEGY FOR A HYBRID POWER GENERATION SYSTEM CONSISTING OF PHOTOVOLTAIC ARRAYS AND FUEL CELLS (PV-FC) P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos ENERTECH 2007, 18-21 October, Athens P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

APPENDIX

Prediction of Global Solar Irradiance by a Gaussian-type function Part I: Global Solar Irradiance Model Prediction of Global Solar Irradiance by a Gaussian-type function Description State Clear 6 Few Clouds 5 Partly Cloudy 4 Cloudy 3 Heavy Clouds 2 Rainfall 1 P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Decision strategies for November reference day

Decision strategies for November reference day

Decision strategies for March reference day

Formulation of the LP optimization problem minfTx A*x<=b x Aeq*x=beq lb<=x<=ub x = linprog(f, [], [],Aeq,beq) 7 variables*72 time periods 4*72 time periods (equalities) 1*72 time periods (inequatlities) P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Part II: PV Power Generation-Load Profile (Deterministic) P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit

Part II: PV Power Generation-Load Profile (Deterministic) P. L. Zervas, H. Sarimveis, J. Α. Palyvos, N. C. Markatos, ENERTECH 2007, 18-21 October NTUA, Chemical Engineering School, Computational Fluid Dynamics Unit