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© Q3 Energieelektronik GmbH Page 1 Monitoring and Operation of PV-Battery Systems Daniel Föhr, M.Eng. Product Manger Energy Systems Q3 Energieelektronik.

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Presentation on theme: "© Q3 Energieelektronik GmbH Page 1 Monitoring and Operation of PV-Battery Systems Daniel Föhr, M.Eng. Product Manger Energy Systems Q3 Energieelektronik."— Presentation transcript:

1 © Q3 Energieelektronik GmbH Page 1 Monitoring and Operation of PV-Battery Systems Daniel Föhr, M.Eng. Product Manger Energy Systems Q3 Energieelektronik GmbH

2 © Q3 Energieelektronik GmbH Page 2 Content  The QBEE Energy System  Determine load profiles  Recording methods and quality of load profiles  Requirements of intelligent PV-battery systems  Advantages of monitoring PV-battery systems  Outlook – From PV to Smart Grid

3 © Q3 Energieelektronik GmbH Page 3 QBEE – The Energy System Maximum usage of own PV energy by minimal purchased power  For new installations  For existing installations  State of the art lithium-ion technology  Compact and powerful

4 © Q3 Energieelektronik GmbH Page 4 Setup and components of the QBEE Energy System 1.5 kW bidirectional inverter Suitable for photovoltaic and wind energy with integrated charge controller and energy management Battery With integrated battery management system with 2.0 / 4.0 / 8.0 kWh Grid Sensor Monitoring the input and reference power of all thre phases

5 © Q3 Energieelektronik GmbH Page 5 QBEE as DC/AC coupled system Installation as a retrofit for an exisiting system or with an additional PV generator. In this case the battery can be charged via the DC input and/or over the AC connection.

6 © Q3 Energieelektronik GmbH Page 6 Determine of load profiles  Determine of the load profile is essential for the battery system layout  The layout of the ideal PV generator and the matching storage capacity for each individual household gets more and more complex  Do not store more than necessary!  Oversized batteries can rarely be exploited  Unused capacity increase costs per kW  The base load capacity determines the storage capacity

7 © Q3 Energieelektronik GmbH Page 7 Consumption behaviour During the day almost never at home Consumption mainly at night. At daytime long time to charge.  High storage potential, no large-scale PV generator needed Partially working Consumption is distributed relatively evenly.  Tuned mix of PV and Battery Family with children Consumption is highest during the day. Less excess energy available for loading.  Large PV generator for natural self-consumption Consumption behavior can be divided into categories

8 © Q3 Energieelektronik GmbH Page 8 Determine of load profiles QBEE GridSensor Inductive power measurement of all three phases. No separation of the lines needed. Easy DIN rail mounting in the meter cupboard. Ideal for determining an accurate statement: One year measurement with a time resolution of 1 second and irradiation data

9 © Q3 Energieelektronik GmbH Page 9 Standard load profile Example of a standard load profile (H0) with average values of 15 minutes Source: BDEW

10 © Q3 Energieelektronik GmbH Page 10 Individual load profile Example of an individual load profile with pulsed loads in a temporal resolution of 1 second

11 © Q3 Energieelektronik GmbH Page 11 Alternative method – consumption behavior by consumer groups ▪ On the basis of the yearly load consumption a standar load profil is scaled ▪ Merge into main consumer groups ▪ Determine of percentage weighing and tempral distribution ▪ Accuracy of +/- 10%

12 © Q3 Energieelektronik GmbH Page 12 Advantages of Monitoring PV-Battery Systems Requirements:  Fast acting battery system and cell technology  Communication interface between EMS and BMS  Interface for external variables  Interface for Demand Site Management  Bidirectional communication link for external

13 © Q3 Energieelektronik GmbH Page 13 Battery System with Forecasting EMS BMS Forecasts Generator and load models Load profile for battery system Battery model SOC forecast  Communication interface between EMS and BMS  Weather forecast/ Market price prediction  Forecast and determine of load profiles  Optimized operation of battery management  SOC prediction in dependence on load profile forecast

14 © Q3 Energieelektronik GmbH Page 14 Dynamic control of EEG regulations Dynamic 70 or 60% regulation according to the EEG considering:  Entire house load  AC-coupled battery system as an intelligent load  Additional access load

15 © Q3 Energieelektronik GmbH Page 15 Demand site management Excessive energy consumers: e.g. white goods, hot water don‘t need to be supplied by the battery system  Monitoring of PV-Forecast  Deposited load profile  Link with Home Automation System  Shift consumption in peak PV production time  Increase natural self-consumption  Relief of public grid and battery

16 © Q3 Energieelektronik GmbH Page 16 Purchase and Sale of Electricity PV electricity can be offered profitable outside the EEG market regulations. In combination with battery, monitoring an forecasts:  Determine excess energy/demand  Supply security for the time period  Voltage stability in case of short-term weather changes  PV systems can combine to generate a virtual power plant and use their backup capacity for short term trading at the EEX. Source: Solarworld

17 © Q3 Energieelektronik GmbH Page 17 Offering balancing energy  Based on the monitoring data also unused storage capacity can be identified  Receptive systems can have a positive effect on the grid by providing balancing energy: If they are able to obtain and delivery energy in times of grid overload.  In combination with a bidirectional connection a lucrative market model for the expiring EEG.  E.g. municipal utilities are eager to regulate their power within their own grid.  PV-battery systems can also act as a virtual power plant Source: next-kraftwerke.de Short term trading with virtual power plants

18 © Q3 Energieelektronik GmbH Page 18 Conventional Storage Conventional storage has no relief effect for the public grid Maximum feed-in into the grid Charge till battery is full Consumption of PV electricity Peak production goes directly into the grid Source: BSW

19 © Q3 Energieelektronik GmbH Page 19 Grid optimized charging Charge when much electricity is generated Reduced feed-in into the public grid Low feed-in power increases local grid capacity Combinded with an PV forecast the battery systems can contribute to:  Regulating the voltage on local low voltage grid  Regulating the frequency in the whole European grid Source: BSW

20 © Q3 Energieelektronik GmbH Page 20 Outlook – From PV to the Smart Grid PHOTOVOLTAIC  Feed-in  70% Regulation/Load management  Power Balancing/Reactive power control  Supervision & Control SMART GRID  Intelligent purchase and sale of electricity  Supply of positive and negative control power  Load Management (E-Mobility Devices) SMART HOME  Energy management - Energy saving - Intelligent energy distribution - Demand site management  Link with Home Automation System  Emergency supply  Hot water preparation Quelle:

21 © Q3 Energieelektronik GmbH Page 21 Q3 Energieelektronik GmbH & Co. KG Daniel Föhr Product Manager for Energy Systems Marktplatz Biberach Germany Mail Web Thank you for your attention


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