prosumers’ impact on the electricity system heinisch... · batteries perfectly scalable suitable...

PROSUMERS’ IMPACT ON THE ELECTRICITY SYSTEM

VERENA HEINISCH

Chalmers University of Technology, Göteborg, Sweden Department of Energy and Environment

Divion of Energy Technology, Energy Systems Group

Research on techno-economic energy systems modelling, centralized and

decentralized developments in electricity systems, prosumers and micro-generation

Project funded within the ”Forskarskolan Energisystem” by Energimyndigheten

[email protected]

HOUSEHOLD ANNUAL ELECTRICITY COST

VS. SYSTEM OPERATIONAL COST OPTIMIZATION

mailto:[email protected]

SAEE Luleå, 2016, Impact of Prosumers on the Electricity System Verena Heinisch, 2016-08-24

WHAT DOES THE FUTURE ELECTRICITY CONSUMER LOOK LIKE?


• Produce - electricity from household PV panel

• Store - e.g. diurnal shifting of energy to

make use of their PV production

behind the meter

• Buy & Sell - from and to energy utility

PROSUMERS

Modelling of cost optimal operation

- of a large share of PV battery systems

- on Swedish residential dwellings

- within the Nordic electricity generation system

- in the year 2032

- from a household as well as a system perspective


Decreasing costs of PV and

batteries

Perfectly scalable suitable also for

different kinds of small customers

Motivation

Modelling of cost optimal operation

- of a large share of PV battery systems

- on Swedish residential dwellings

- within the Nordic electricity generation system

- in the year 2032

- from a household as well as a system perspective


Household operational patterns do not comply with max system value at all times

- Capacity value for system vs. energy value of batteries for

household

- Difference in system operational costs and resource utilization

Seasonal differences in charge and discharge patterns exist for system

and households

Volatile marginal prices increase the system value of batteries while the

biggest value for households with PV battery systems is the diurnal shifting of electricity

Method and Study Set-Up

Summary

STRUCTURE OF THIS PRESENTATION R

ESU

LTS


European electricity dispatch model

EPOD

Household electricity cost optimization

model

Optimizing total costs for Electricity generation to fulfill

demand



EPOD


model

Optimizing total costs for Electricity generation to fulfill

demand

Optimizing household annual electricity costs



EPOD


model

FEEDBACK Electricity prices

Load curves (considering BESS)

Optimal battery

operation pattern

System

perspective

Optimal battery

operation pattern

Household perspective

Optimal investment in battery and PV capacity

(used in both cases)




household



and households



RESULTS


System Opt Household Opt Difference in %

Total costs [M€] 27 350 27 380 -0.12

StUp costs

Powerplants

[M€]

861 872 -1.31

Total system operational costs lower under system

optimization case

Total annual system operational costs all regions

System benefit from batteries eg:

Avoid start-up costs

Different utilization of available

generation

Resource utilization and operation cost

difference

System Opt Case uses more fuel type

Household Opt Case uses more fuel type


Resource utilization and

operation cost

difference

Due to different

battery charge and discharge patterns

2 weeks in summer


Household - keeping PV

generation behind

the meter

- diurnal charge

pattern

System - Optimized electricity

generation

- Low marginal costs


More occasions with low charging from household

perspective operation

System: few times, charging high

amounts

Households: regularly, lower

amounts

Energy vs. Capacity Value of

Batteries

Frequency of Charging amount per hour




household



and households




0,000

0,010

0,020

0,030

0,040

0,050

0,060

0,070

0,080

0,090

0,100

System Household

Average Charge per hour - SE 4

WINTER [GWh/h] SUMMER [GWh/h]

0,000

0,050

0,100

0,150

0,200

0,250

0,300

System Household

Average Charge per hour - SE 3

WINTER [GWh/h] SUMMER [GWh/h]

Utilization of of batteries much lower under summer time during system

optimization

- Storage as a service ?

- System optimization during winter time – household utilization during summer time ?


Summer Winter

Household perspective -356.2 -123.3 M€/year

System perspective -11.7 M€/year

Benefit from operating battery during season:

Control Whole Year Summer Household

Winter System Operation No Control Batteries

Total system costs 27 350 27 370 27 380 M€/year

Household annual el. costs 1790 1913 2270 M€/year

Increasing costs, from full control over operation of batteries to no control

Is it worth paying households to operate batteries from system perspective during

winter time ?

Biggest value from battery for

households in summer

Still system value in winter

considerably lower than

household value




household



and households




Marginal Prices Green

Policy Scenario (goal for

RES) - More fluctuating and

higher prices in winter hours

- Higher price hours for

household optimization

case

Climate Market Scenario

(cap on CO2) - Less fluctuating marginal

prices than above scenario


System – Battery used to

minimize system

operational costs

Household – diurnal

charging patters for PV

electricity


System Opt Household

Opt

Difference in

%

Total costs [M€] 43 880 43 8890 -0.013

StUp Costs [M€] 568.9 568.7 0.035

Minimal savings in total system operational costs

From system perspective Batteries most beneficial in a

system with high share or RES

From household perspective Lower capacity (compared to

GP scenario) of PV and batteries

beneficial to decrease annual

electricity costs

- Less fluctuating generation and marginal prices

- Lower value of batteries to be scheduled after system

optimum

- Lower investment in battery and PV capacity from

household side

Climate Market Scenario – less volatile prices:




household



and households



SUMMARY

PROSUMERS’ IMPACT ON THE ELECTRICITY SYSTEM

VERENA HEINISCH

Chalmers University of Technology, Göteborg, Sweden Department of Energy and Environment

Divion of Energy Technology, Energy Systems Group

Research on techno-economic energy systems modelling, centralized and

decentralized developments in electricity systems, prosumers and micro-generation

Project funded within the ”Forskarskolan Energisystem” by Energimyndigheten

[email protected]

HOUSEHOLD ANNUAL ELECTRICITY COST VS. SYSTEM OPERATIONAL COST OPTIMIZATION

mailto:[email protected]



EPOD


model



Optimal battery

operation pattern

System

perspective

Optimal battery

operation pattern


• Year 2032, Green policy ( renewables, variable prices) & Climate Market (cap on

emissions) scenario

• Measured load data from several thousand Swedish households (EON) – scale up

depending on type

• Solar generation profile and discharge efficiency for batteries



EPOD


model



Optimal battery

operation pattern

System

perspective

Optimal battery

operation pattern


Value of battery system to the system and to the

household

“Storage as a service”


• Battery Capacity

SE4 1.98 GW

SE3 5.97 GW

• PV Capacity

SE4 1.82 GW

SE3 6.23 GW

Household Capacity

Investment

PV and load profile aggregated per region


Charge (positive –

green)

Discharge (negative –

red)

Patterns

- Less times of battery

utilization from system

optimization

perspective

- But utilizing full

capacity - Regular diurnal

pattern to store PV

generation in

household

optimization case


Include NoBatPlusPV and NoBatnoPV Cases????


AVERAGE SELF SUFFICIENCY

SE1 32,2 %

SE2 24,3 %



EPOD

50 regions in Europe, 3 hour time stpes

DC load flow represantation

Ramping/start up costs & limitations

for thermal power

Representation regional storage

limitation of Nordic hydro power

…

Power plant data base

Resources description

Scenarios

Investment model ELIN

Dispatch model EPOD

Power grid

& Electricity

Trade

PV/DSM

household

level

Transport

system and

district

heating

Prosumers


• Very ambitious renewables policy

• EC “High renewable”

• Climate , RES and efficiency polices

• EC “High energy efficiency”

• International carbon trade

• EC “Diversified supply techn.”, “High GDP”

• Existing policy measures

• EC ”Current policy”

Refe-rence

Climate market

Green policy

Regional policy

Technologicaldimension

Policy dimension


SE4 System Household

YEAR [GWh] 459 724

WINTER [GWh] 291 359

SUMMER [GWh] 168 365

SE3 System Household

YEAR [GWh] 1313 2227

WINTER [GWh] 784 1119

SUMMER [GWh] 529 1108

0

100

200

300

400

500

600

700

800

System Household

Battery Charge - SE 4

YEAR [GWh] WINTER [GWh] SUMMER [GWh]

0

500

1000

1500

2000

2500

System Household

Battery Charge - SE 3

YEAR [GWh] WINTER [GWh] SUMMER [GWh]


Summer Winter

Household perspective -356,23 -123,28 M€/year

System perspective -11,65 M€/year

Benefit from operating battery during season:

27330

27340

27350

27360

27370

27380

27390

Control Whole Year Summer Household Winter

System Operation

No Control Batteries

Total system costs

0

500

1000

1500

2000

2500

Control Whole Year Summer Household Winter

System Operation

No Control Batteries

Household annual el costs


Continuation of the

Study

- Residential battery PV systems also in other geographical areas

- Consider prosumers with different objectives (self-sufficiency etc.)

- Smaller scale – Case Study Region/Community – less aggregation in

modelling

- Consider behavioral complexity of prosumers (intangible costs, bounded

rationality, …)

prosumers’ impact on the electricity system heinisch... · batteries perfectly scalable suitable...

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