Dr. Mohamed Bin Shams Dr. Shaker Haji*

Transcription

1 Students' Senior Project: Ali Salman, Hussain A.Ali, Alaa Jameel Supervised by: Dr. Mohamed Bin Shams Dr. Shaker Haji* One Belt, One Road Initiative Bahrain Shanghai Renewable Energy Conference May 13-14, 2017 Kingdom of Bahrain

2 2

3 Feb 21, 2010 Visitors Center Hall: 10 x 60 W light bulbs + a 2 ton A/C Total ~ 3 kw

4 2 Renewable Energy Sources 4 x 260Ah/12V (48 V DC System - Series) 20 x 200 W p = 4 kw p m/s cut in: 3 m/s Public Grid 1.2 kw Nexa FC Stack 6 x bar H 2 M-H Canisters 2 x 60 NL/h H 2 Generator (water electrolyzers)

5 Power [W/m 2 ] Temperature [ o C] or Wind Velocity [m/s] 1000 Climate Related Data Environmental Conditions Solar Irradiation Ambient Temperature Module Temperature Wind Velocity :00 AM 6:00 AM 12:00 PM 6:00 PM 12:00 AM 6:00 AM 24/06/ /06/2010 Date & Time 7 Courtesy of Bapco

6 Power [W] Battery SOC [%] or H 2 Pressure [bar] 3000 AC Laod P [W] Energy Related Data PV P [W] WT P [W] FC P [W] Bat. SOC [%] 70 H2 Pressure :00 AM 6:00 AM 12:00 PM 6:00 PM 12:00 AM 6:00 AM 24/06/ /06/2010 Date & Time 0 8 Courtesy of Bapco

7 9

8 (1) To analyze, model, & forecast meteorological data (driving forces) (2) To analyze the energy data from the hybrid RE system Ultimate Goal: Optimize the performance of the RE system (e.g. maximizing CO 2 saving) 11

9

10 Data collection (1 st May th April 2011) Bapco s Green Energy Station Data.

11 Time Series Analysis: Meteorological Data Modeling 1. Estimating Missing Points 2. Stationarizing data (if required) 3. Parameter Estimation (Least Square Error) 4. Validating Models (Residual Analysis) 5. Forecasting 6. Validating Forecasting Accuracy 7. Other Statistical Analysis

12 Energy Data Analysis 1. Efficiency Calculations: various systems 2. Energy Calculations: Load, RE, Storage & PG 3. Calculations of CO 2 Savings & Emissions 4. Feasibility Calculations: PV & WT

13

14 Speed, m/s Average daily wind speed: ARIMA (1,0,0): Actual Data Actual wind speed Forcasted Trans. Actual wind Datavelocity speed Modeled UCL wind speed LCL y = x y t = y t 1 + ε t

15 Radiation W/m2 Average daily solar radiation: ARIMA (1,0,0): 600 Radaition W/m Actual Solar Radiation Modeled Solar Radiation UCL LCL Forecasted Data Actual Data y t = y t 1 + ε t

16 Temperature, C Average daily ambient temperature: ARIMA (0,1,2): Actual Actual Ambient DataTemperature Forecasted Data Modeled Ambient UCL Temperature LCL y t = y t ε t ε t 2 + ε t

17 Temperature, C C Average daily solar module temperature: ARIMA (0,1,1): Actual Data Module Temperature Forcasted Data Modeled Module UCL TemperatureLCL y t = y t ε t 1 + ε t

18

19 Energy, MJ 3,500 3,000 2,500 2,000 1,500 1, Monthly load of the station Load of the station, MJ

20 Monthly Contribution, % Monthly systems contributions to load demand 100% 80% 60% 40% 20% 0% 0 0% Annual and systems contributions to load demand 10.7 GJ Grid Monthly Contribution of Renewable Sources, % Monthly 90% Contribution of public Grid, % Renewable Energy 5.14 GJ 30% GJ 70% 1.25 GJ 10% Solar system Wind Energy

21 Energy, MJ Monthly energy out from storage system Annual energy out from storage system 236 MJ 5% Storage Energy Out from Batteries, MJ 4268 MJ 95% Annual Storage Energy Out from Batteries Storage Energy Out from Fuel Cell, MJ Annual Storage Energy Out from Fuel Cell

22 CO 2, kg CO 2 Savings: Annual Saved CO2, kg 1,429 Estimated CO2 Savings, kg Annual Emitted CO2, kg CO2 Emitted, kg 621

23 Units efficiencies: Equipment Efficiency, % Maximum Minimum Standard deviation Reference Wind Turbine 57.64% (a) 74.34% 37.29% 9.74% < 59% (Bitz) [4] Solar Panel 7.00% (a) 11.56% 3.15% 2.46% < 15% max [5] Fuel Cell 37.7% (b) 37.75% 37.65% - < 40-60% [6] (a) Average monthly efficiency (b) Average instantaneous efficiency for October and February

24

25

26 Effectiveness, Payback Period, Energy Cost of Wind & Solar systems: Equip. Wind Turbine Solar Panel Cost, $/W Lifetime, years Rated Power, kw Avg. Meas. Power, kw Effectiveness, % Comm. PBP, years Resid. Energy Cost, $/kwh (fils/kwh) (442) (223) * Effectiveness = Avg. Measured Power / Rated Power

27

28 The following models were found satisfactory in modeling: ARIMA( 1,0,0): Wind speed ARIMA( 1,0,0): Solar radiation ARIMA( 0,1,2): Ambient temperature ARIMA( 0,1,1): Solar module s temperature data The station load was met by renewable energy ( 70%) and public grid (30%). Solar Panels contributed with 90% while the wind turbine contributed with 10% to the RE mix. Due to the governmental subsidies of electricity, non of the PV or WT was found feasible. The solar panel is more feasible than the wind turbine.

29 Modify the mechanism, so the grid cover only the energy shortage due insufficient supply from renewable and storage systems. Regular maintenance and upgrading the data acquisition system. Subsidies should be provided to RE technologies for them to be feasible. Optimizing the station operation/configuration, for further CO 2 savings.

30 Bapco, Awali Services Prof Waheeb Al-Naser & Mr Hussain Al- Ansari Heliocentris (system manufacturer) Our students: Ali Salman, Hussain A.Ali, Alaa Jameel.

31 [1] Dr.Cluas Fischer and Dr. Nroman Siehl, 2010, Heliocentris Energirsysteme GmbH, Power Point presentation, Heliocentis, Berlin-Germany [2] Montgomery etal, (2008). Introduction to Time Series Analysis and Forecasting, Wiley. River Street Hoboken [3] Description of Transformation, [Last visit on 13 January 2013] [4] The Royal Academy of Engineering (Wind Turbine Power calculations) pdf, [Last visit on 6 January 2013] [5] Alfasolar, (Solar Module Series alfasolar pyramid 54), [Last visit on 6 January 2013] [6] EERE Information Center-U.S (Fuel Cell Technologies Program) df, [Last visit on 6 January 2013]

32