Ondřej Novák, ČVUT ondrej.novak@fel.cvut.cz

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

5. Power output balance of a transforming station 100 50 Power output [kW] 0 -50 Optimised balance Original balance -100 1 2 3 4 5 6 7 8 9 10 11 Days Imported and exported power Maximum import a export 800 100 import 80 600 60 400 40 Power output [kW] 20 200 Power [kWh] 0 0 -20 -40 -200 -60 -400 -80 -100 -600 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Days Days Goals of power consumption control export Without consumption control With consumption control Project BIOZE

6. Principle of control algorithm Prediction of uncontrolled consumption Prediction of uncontrolled consumption Prediction of uncontrolled generation • 2nd step: Adherence to the calculated reference from the 1st 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) Prediction of uncontrolled generation Optimiser Controlledconsumption + - + Resulting balance Two-step calculation of switching times of hot-water heaters: • 1st 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

7. Principle of control algorithm Prediction of uncontrolled consumption Uncontrolledconsumption Uncontrolledgeneration • 2nd step: Adherence to the calculated reference from the 1st 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) Prediction of uncontrolled generation Optimiser Controlledconsumption + - + Resulting balance Two-step calculation of switching times of hot-water heaters: • 1st 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 algorithmwith the measurement of output balance at DTS „DD“ fotovoltaic TDD Meteo-data cloudiness forecast (t : t + TP ) Uncontrolled consumption balance (t) Prediction of uncontrolled generation (fotovoltaic) & consumption Uncontrolled generation and consumption typical fotovoltaic generation (t : t + TP ) daily consumption chart (t : t + TP) Controlled consumption Metering of output flow from DTS Optimiser Input of controlled consumption (t) Instructions for hot water heater control (t) Prediction of power generation fotovoltaic (t : t + TP ) output balance DTS (t) Prediction of power consumption (t : t + TP ) metering transmitted data TP – predicative horizon of calculation = 12 hrs Project BIOZE

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

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 Project BIOZE

14. Simulated control – 24hr detailing, scenario 1 • EMAX = 65 kWh (maximum import) • EMIN= -84 kWh (maximum export) • SE+ = 608 kWh (total consumption) • SE- = -503 kWh (total generation) • EMAX = 58 kWh • EMIN = -56 kWh • SE+ = 496 kWh • SE- = -418 kWh Blue field= hot-water heater pwr consumption Green field = other power consumption Red line = fotovoltaic power generation Black line = power balance Project BIOZE

15. Output at transformer station with heater control 50 without heater control 0 Outputs [kW] -50 -100 00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00 Time Consumption control results – from real operation • 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