1. ONDŘEJ NOVÁK Control Technology Department, Faculty of Electrical Engineering, Czech Technical University in Prague Ondřej Novák, ČVUT ondrej.novak@fel.cvut.cz Household consumption control and secure integration of RESs [Renewable Energy Sources] Control system concept and pilot project presentation České vysoké učení technické v Praze Project BIOZE

2. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Project BIOZE  Joint Project of FAV ZČU, FEL ČVUT, FEL ZČU, Pontech s.r.o. and Cygni spol. s r.o.  Grant of TAČR (Technological Agency of the Czech Republic): Project Alfa TA01020865  Partial project: Power consumption control with regard to the integration of Renewable Energy Sources (RESs) Project BIOZE

3. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Power System Control Group  Research group at the Department of Control Technology, Faculty of Electrical Engineering, Czech Technical University in Prague, active in the field of modelling, simulation and optimisation in power engineering  Co-project management of the BIOZE project  Since 2005, co-project management of the SESyS project – Reliability and economy of system services for ČEPS, a.s.  Simulation of dispatching control in transmission systems  Simulative optimisation of regulative ranges for auxiliary services  Routine application as an analytical tool for the preparation of documents to the annual arrangement of transmission system operation Project BIOZE

4. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Power consumption control Project BIOZE  Goal: to minimise negative impact of installed (fotovoltaic) RESs on DS  Overflow into DS  Overvoltage in grid  Idea: to consume power on the spot, i.e. at the place where it has been generated  Accumulation of power generated in fotovoltaic units in household hot-water heaters

5. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Goals of power consumption control Project BIOZE With consumption control Without consumption control export

6. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Principle of control algorithm  2 nd step: Adherence to the calculated reference from the 1 st step  Optimisation of hot-water heater switching  Calculation repeated in each 5 minutes  Limits for optimisation: Capacity of heaters (hot water quantity) Limitation for switching : prevention of excessive wearing (of switches) Optimiser Controlled consumption + + - Resulting balance Prediction of uncontrolled consumption Prediction of uncontrolled consumption Prediction of uncontrolled generation Prediction of uncontrolled generation Two-step calculation of switching times of hot-water heaters:  1 st step: Minimisation of power output flows to/from the area (= maximisation of local utilisation of generated power)  In accordance with the prediction of power generation & consumption in the controlled area for 12 hours  Result: Reference power output balance of the area for the next 12 hours Project BIOZE Prediction of uncontrolled consumption Prediction of uncontrolled generation

7. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Principle of control algorithm  2 nd step: Adherence to the calculated reference from the 1 st step  Optimisation of hot-water heater switching  Calculation repeated in each 5 minutes  Limits for optimisation: Capacity of heaters (hot water quantity) Limitation for switching: prevention of excessive wearing (of switches) Optimiser Controlled consumption Uncontrolled consumption Uncontrolled generation + + - Resulting balance Prediction of uncontrolled consumption Prediction of uncontrolled consumption Prediction of uncontrolled generation Prediction of uncontrolled generation Two-step calculation of switching times of hot-water heaters:  1 st step: Minimisation of power output flows to/from the area (= maximisation of local utilisation of generated power)  In accordance with the prediction of power generation & consumption in the controlled area  Result: reference power output balance of the area for the next 12 hours Project BIOZE

8. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Implementation of control algorithm with the measurement of output balance at DTS Project BIOZE cloudiness forecast (t : t + T P ) typical fotovoltaic generation (t : t + T P ) „DD“ fotovoltaic Prediction of power consumption (t : t + T P ) Controlled consumption Instructions for hot water heater control (t) Optimiser output balance DTS (t) TDD daily consumption chart (t : t + T P ) Prediction of uncontrolled generation (fotovoltaic) & consumption Prediction of uncontrolled generation (fotovoltaic) & consumption Prediction of power generation fotovoltaic (t : t + T P ) Metering of output flow from DTS T P – predicative horizon of calculation = 12 hrs Meteo-data Uncontrolled generation and consumption Input of controlled consumption (t) Uncontrolled consumption balance (t) metering transmitted data

9. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Implementation of control algorithm with simulated output balance of DTS (without on-line measurement of balance) Project BIOZE cloud forecast (t : t + T P ) typical fotovoltaic generation (t : t + T P ) „DD“ fotovoltaic daily consumption charts (t) and typical fotovoltaic generation (t) revised acc.to actual weather TDD Prediction of power consumption (t : t + T P ) „DD“ fotovoltaic measured input and voltage at the places of consumption control (t) Controlled consumption instructions for hot water heater control (t) Optimiser output balance DTS (t) TDD daily consumption chart (t : t + T P ) Prediction of uncontrolled generation (fotovoltaic) & consumption Prediction of uncontrolled generation (fotovoltaic) & consumption Prediction of power generation fotovoltaic (t : t + T P ) Load Flow grid simulation T P – predicative horizon of calculation = 12 hrs Meteo- data

10. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Pilot project Horušany  Horušany (region Plzeň)  Small municipality connected to DS by one supply TS (250kVA)  installed fotovoltaic power sources 120 kWp  problems of compliance with voltage limits  “export balance” of the municipality Project BIOZE

11. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Simulated control results  Performed while supposing optional control of all hot- water heaters in the area (40 households)  Performed in the period April - May 2011 (available measurement data of power output flow at DTS)  Consumption of hot water in households simulated according to respective data from the project IEA ECBS – measurement data on hot water consumption have not been available  Simulation in accordance with measured balance at DTS Project BIOZE

12. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Simulated control results  Three scenarios have been simulated to demonstrate the impact of information on the hot-water heater status (quantity of hot water):  Scenario No.1: Hot-water heaters have no hot water quantity detection Hot water volume must not be lower than 45% of the total capacity It was necessary to heat water at 100% capacity at least once a day (to synchronise the estimation of status and the real status of respective hot- water heater)  Scenario No.2: Each hot-water heater has been equipped with a sensor sending a signal when the quantity of hot water decreases below 25% of its capacity Hot water volume must not be lower than 20% of the total capacity  Scenario No.3: Each hot-water heater has been equipped with a sensor sending a signal when the quantity of hot water decreases below 25% or increases above 75% of the total capacity Hot water volume must not be lower than 20 % of the total capacity Project BIOZE

13. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Simulated control - results Scenario No.123 Reduction of power export [%] 42.446.951.1 Reduction of power import [%] 26.525.324.9 Reduction of min-max output range [%] 34.736.438 Reduction of power transferred [%] (in 4 days) [MWh] 24.126.526.7 1.131.251.26 Project BIOZE

14. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Simulated control – 24hr detailing, scenario 1 Project BIOZE  E MAX = 65 kWh (maximum import)  E MIN = -84 kWh (maximum export)   E + = 608 kWh (total consumption)   E - = -503 kWh (total generation)  E MAX = 58 kWh  E MIN = -56 kWh   E + = 496 kWh   E - = -418 kWh Blue field= hot-water heater pwr consumption Green field = other power consumption Red line = fotovoltaic power generation Black line = power balance

15. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Consumption control results – from real operation 00:0003:0006:0009:0012:0015:0018:0021:00 -100 -50 0 50 Time Outputs [kW] Output at transformer station with heater control without heater control  6 hot-water heaters available for control ~ 13 kW Project BIOZE

16. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Consumption control results – from real operation  Detail of consumption control impact on output balance of DTS  Switching-on 13 kW for 15 minutes Project BIOZE

17. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Summary  Created algorithm can suppress the export of power from respective area down to one half  Presented solution offers better exploitation of transmission capacity of DS  Power supply quality has been improved (voltage stabilisation)  Possible savings of investments in grid reinforcement Project BIOZE

18. ____ ______ _____ _________ _ ____ _______ ________________ _______ ______ ________ Further development  Implementation of the Optimiser as an embedded system (on ARM architecture)  Development of algorithms for the estimation of hot water consumption from the hot-water heater power input  Extension of the pilot project by adding the hot water consumption metering (hot-water heater operation control should be then better)  Extrapolation of the control scheme for power control at HV level  Optimisation of HV area operation to generate required power output values for the control at LV level  Decentralised cooperation among more LV areas Project BIOZE