Design and Operation of Future Energy Systems

Design and Operation of Future Energy Systems – an Technology Providers View Michael Metzger VDE Kongress 2016, Mannheim

Siemens Corporate Technology

Design and Operation of Future Energy Systems Agenda

Motivation Digital twin of our energy system Analysis of a target system 2035+ Conclusion

unrestricted © Siemens AG 2016 Page 2

Corporate Technology

Energiewende is not only a technical issue – even more important are business models, regulation (politics) and markets Unbundled electrical power supply in Europe

Grid

Generation Steam power plant

Combined cycle/ Simple cycle

Hydropower

Nuclear power

Photovoltaics

Grid

Simple cycle power plant

Onshore wind

Biomass

Small hydro

Spot Market

Transmission

Energy Supplier

Transmission and distribution grid operators are responsible for grid stability. Transmission and distribution grid operators have a monopoly.

Energy Supplier Energy suppliers are responsible for energy supply. Energy suppliers are competitors. A distribution grid is used by multiple energy suppliers.

Distribution

End Customer

The end customer is expected to become a more important driver in the future Industrial Site


Building


To reach the climate goals we have to integrate all the energy sectors Different transition paths

A

Space

Somewhere else B

C

Water Gas/Fuel Cold Heat Electricity

here

now later

Generation  Utilization



Future energy systems are becoming multi-modal and decentralized  Efficient Design and Management needs the help of a digital twin Water Transport

Water Production

Pumping Station

Water Tanks

Smart Building w/ heat pump & thermal storage

Gas Supplier Gas Transport

Gas Station

Private Wind or Solar

Water Distribution Biomass

Gas Distribution Heater, Chiller Heat Station

C(C)HP2)

Power to gas (liquid, chemical) Offshore Wind Park

District heating cooling

Microgrid Controller Microgrid

Industry Storage Thermal Storage

Pumped Hydro

Engine Generator with C(C)HP2)

District heating cooling

Storage Solutions

Onshore Wind

Fuel cell

Electrical Vehicle Infrastructure

Onshore Wind Park Network Control Center

Controllable LV transformer Large Scale PV Plant

Fossil Power Plant Power Station

Bulk Generation Energy Management System (Production Plant)


Power Station

Power Station

Distribution and DER1)

Transmission Building Energy Management System

Smart Meter Smart Energy Agent

1) Distributed Energy Resources

Buildings and Industry Access Point Internet of things

Power AC Power DC

Nanogrid within Building (e.g. DC grid in Data Center)

Heat/Cold Gas

Water supply

2) Combined (Cooling) Heat and Power Corporate Technology





With the Energy System Development Plan (ESDP) we are analyzing the system and market level, e.g. for Germany in a European energy market

80% renewable energy 2035+

Residual load 500MW

Digital twin of the European energy system

250MW

0MW

-250MW

-500MW

Scenario for 2035+ (80% share from renewable sources)



Fine grain modeling of the renewable in-feed & demand in Germany – embedded into European model needs consistent and detailed data Integration of Renewable feed-in and demand Meteorological data as basis for renewables

Electrical & thermal load modelling Electricity demand sector CTS Exemplary heat demand in category 47:Retail sector

• Electrical and thermal loads are modeled for • Consistent meteorological data across Europe

o Private sector

• High spatial and temporal resolution

o Commerce, Trade and Services (CTS)

• Enables the modeling of realistic feed-in time series

o Industrial sector

• 15-minute resolution of solar radiation (SoDa) • Hourly data for wind-speed and temperature (eraint)

• Spatial resolution: ZIP code area (PLZ5), down to single company (large industrial sites) • Hourly time resolution



The cellular approach enables the evaluation of distributed energy resources in system simulations Cells are defined as the supply area of one 380 kV / 110 kV substation

Cell definition and characteristics  One cell comprises all distributed energy systems (DES) (decentralized generation, electric / thermal loads and energy storages) connected to one 380kV / 110kV substation  The individual DES in one cell are aggregated per technology (combination) (e.g. combined heat and power plants, heat pumps) and sector (households, trade, commerce and services, industry)  The aggregated DES per cell are modelled in the system simulation as virtual power plants considering aggregated technical and demand constraints of the individual DES

Dots mark substation Colors mark one cell One cell consists of PLZ 5 regions PLZ: Postleitzahl (engl. zip code) unrestricted © Siemens AG 2016 Page 9


Market simulation determines schedules for all power plants and aggregated distributed energy systems European Multimodal Market Simulation

Optimization of energy system operation in Europe based on the objective function of cost minimization  Market based generation time series for fossil power plants (Unit commitment based on merit order with technical restrictions)  Storage technology operation (pumped storage, Power2Gas,…)  Operation plan for each cell (decentralized generation & storage) − Generation: combined heat and power, heat pump, heating rod, boiler − Storage: electrical storage, thermal storage, high temperature storage − Transport: e-mobility

Power plant schedules

 International electricity exchange  For European neighbor countries power plants are modelled via vintage classes, block wise modelling is also possible


Cell schedules


Based on the unit commitment ESDP is able to analyze the need for transmission grid expansion Objective and methodology

European Multimodal Market Simulation

Objective:  Estimate the transmission grid expansion costs for future energy system scenarios  Estimate the expansion cost savings of cell autarky (i.e. using distributed flexibilities to minimize imports and exports to/from each substation supply area)

Assignment to grid nodes

Busbar

Methodology and assumptions:  Transmission grid including all TYNDP1) and approved NEP20142) measures until 2024 as a starting point  Market schedules from market simulation (EMMS) are assigned to grid nodes  Grid expansion need is estimated using power flow simulations and expansion heuristic Component

Power Plant

Wind

PV

Cell residual load

Cost assumptions

Double 380 kV AC OHL system

1,4 Mio. €/km Power Flow Simulation

380 kV switchgear

4 Mio. €

380/110 kV transformer (300 MVA) Source: Netzentwicklungsplan 2014


1)

Ten Year Network Development Plan

6,5 Mio. € 2)

Grid expansion heuristic

Netzentwicklungsplan


Based on the unit commitment ESDP is able to analyze the expansion and intelligent management measures in the power grids Objective and methodology

Cell Data

 Objective:  Estimate the distribution grid expansion costs for future energy system scenarios  Estimate the reduction of expansion costs due to innovative grid operation, such as Internet of Things, storage and reactive power management  Methodology:  Detailed Nationwide Modelling of Medium (MV) and Low Voltage (LV) Grids

Distribution Grid Generator Inhabitants Identify MV Areas Population density

 Generate individual combined MV and LV grids

Classify MV Areas

Archetypes

 Assign demand and generation profile for every customer  Grid expansion need is estimated using power flow calculation and expansion heuristic

Model MV & LV Grid Stuctures Registers Assign Customers to Grid Nodes

Modeled German System MV Grids Total Lines MV/LV Transformers unrestricted © Siemens AG 2016 Page 12

3991

Power Flow Calculation

1.1 Mio. km 580000

Grid expansion heuristic Corporate Technology





ESDP Phase 1 German Climate Goals 2050 is the base for all modified scenarios Summary of analyzed scenarios in phase 1 (using market simulation). Renewable Sources

Reference Scenario 1. German Climate Goals 2050 1) Assumptions from recent study on GER climate goals: Prognos/GWS/EWI, 2014 80% of electricity consumption from RES & 60% of end-energy demand from RES No power2gas

PV

Onshore

Gas Turbines/ Large CHP

Storage + Other

67 GW

70

18

12

4

75

150

64

60

19

21

11

35

+

GW TWh

Results of Simulation

368 TWh 264 GW

67 GW

78

70

18

12

4

75

150

64

60

19

21

11

35

+

GW TWh

Results of Simulation

447 TWh 132.5 GW

99 GW

63

47

6.5

12

4

61

101

23

60

19

22

11

66

+ Results of Simulation

GW TWh

264 TWh

1) EWI/GWS/Prognos: „Entwicklung der Energiemärkte – Energiereferenzprognose“, Studie im Auftrag des Bundesministeriums für Wirtschaft und Technologie, 2014. 2) IHS Inc.: „A More Competitive Energiewende: Securing Germany’s Global Competitiveness in a New Energy World“, 2014.


Coal based electric power

RoR

78

3. Gas Revolution 2) (2025) Gas is the main fossil energy source; Europe will have an 100 % integrated gas net, gas is imported from different sources; German CO2 goals not reachable

Biomass

182 GW

2a/b. My Own Storage (2050) Combination of residential PV with massive integration of cheap electric storage with a) 2-15 kWh and b) 500 kWh. Modes of operation: max. self-supply vs. system-oriented utilization. ηAC2AC: 80%

Offshore

Conventional & Storage

PV = photovoltaic's RoR = run of the river hydroelectricity


What is the system impact of different power to heat and thermal storage options in the future energy system? Summary

1

2

3

4

• •

Flexibility of decentral technologies (heat pumps, resistive heating, CHP-heating) has positive effect on system costs reduces curtailment of renewables significantly

•

P2H at CHP sites (district-heating) reduces variable system costs significantly more that decentral technologies in 1)

•

reduces curtailment of renewables significantly

•

Optimal dimensioning: P2H for 70% of thermal power of the district heating plants, heat storage capacity for 10h

•

P2H at industrial sites with High-Temperature Heat Pumps (100o-150o C, without thermal storage) reduces variable system costs

•

High ratio of reduction of variable costs to annuity of necessary investments

•

P2H at industrial sites with resistive heating (150o – 500o C) and high-temp. heat-storage reduces variable system costs

•

Optimal dimensioning: P2H for 100% of thermal power of the process heating, heat storage capacity for 10h

•

reduces curtailment of renewables significantly

P2H = Power to Heat, CHP = Combined Heat and Power


P2H: Power to heat; CHP: Combined Heat and Power


What is the system impact of a large penetration of electrical PV storage in the future energy system? Summary

1

2

3

4

5

• Market driven operation of PV storage is expected to have a significant impact in the electricity market. • BUT massive integration of storage seems not to be a game changer.

• Market driven operation of storage can reduce OPEX of the energy supply in DE by 10%.

• Seasonal storages lead to a full autarky of 60% of buildings & self-consumption rates of 70%. • Daily storages do not lead to autarky of buildings, but 50% self-consumption rate.

• Profitability of seasonal storages is critical, as they are operated with only 1.5 cycles per year.

• Storage has little impact on grid reinforcement costs. • Distribution grid friendly storage operation can reduce peaks due to PV in-feed and load.



Massive integration of storage seems not to be a game changer • A massive penetration of seasonal, decentralized PV storage (~11 mio units, 50 kW, 500 kWh) does not change the generation amount of power plants significantly (for optimal self-consumption AND market driven operation) • Operation with maximum self-consumption has negligible impact on the overall system. • Market-integration of PV storage has an impact and improves the integration of renewable sources: • Reduced net export and generation quantities of power plants • No dumped energy (down regulation of renewables) • Pumped storage power stations are almost entirely replaced (better efficiency of PV storage) 140 120

TWh

100 80

Without el. storage

60

Large el. storage (self-consumption) Large el. storage (market)

40 20 0 Lignite

Hardcoal

SCGT

SCGT = Single Cycle Gas Turbines, CCGT = Combined Cycle Gas Turbines


CCGT

Pumped storage (turbining)

Dumped Energy

Net Export






We have to identify a suitable migration path for each market region of interest – partnering with important stakeholders is key

Energiewende 2.0