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CENTRO STUDIDI ECONOMIA E TECNICA DELL’ENERGIA

“GIORGIO LEVI CASES”

CENTRO STUDI DI ECONOMIA E TECNICA DELL’ENERGIA“GIORGIO LEVI CASES”

Progetto di ricerca

Coordinated control techniques for distributed resources in modern electric

distribution networks (smart grids )

Assegnista: Massimiliano CoppoResponsabile scientifico: Prof. Roberto Turri

Area di ricerca: SMART GRID


~INV INV

MV network LV networkabcn

Rationale:The increase of DG requires shifting the power system management duties on the distribution networks

New network management features proposed

� Distribution Management System (DMS) at MV level

� Flexibility on the voltage management through MV/LV transformerswith OLTC capability

� Better understanding of the LV network and adoption of new control schemes


Future regulatory framework:• Improve the integration of RES in the grid support

• Extend the energy market to include offers coming from MV or even LV networks

The Italian example:3 market models have been proposed by AEEGSI

TSO

(ASM)

DER

DSO

Transmission

Grid

Distribution

Grid


Municipality area

Tertiary Load

Domestic Load

Industrial Load

Agricultural Load

PV production

-5

0

5

10

15

20

P [

MW

]

-5

0

5

10

15

20

P [

MW

]

Load Energy Database

Gen. PowerDatabase

PS location

Demography& economy

Municipality areas

Other geographicalinformations

GIS software

- Combination of geogr. informations

- Estimation of the boundary for each PS

Incidence Matrix

Load and gen. power profiles

Total PS energyconsumption /

generation

PS power exchange

time-profiles

PS1 PS2 PS3

Mun 1

Mun 2

Mun 3

Representative model of primary substation• Energetic analysis based on open-data and

geographic interface system (GIS) databases

• MV network topology built using representative models developed for project ATLANTIDE

Example of power profiles defined for PSs in Sardinia


PILOT BUS selection

Token is sent to each pilot with a POWER REQUEST

Token is COMMUNICATEDamong buses for the request

fullfilling

Token is sent back to the NS which checks the new conditions

MV Distributed Regulation strategy concept:• information-networks model• communication among buses and a central supervisor for power requests

Token 1

Token 2

Token 3

Net

wor

k

Sup

ervi

sor

Token 1

Token 2

Token 3

AR

EA

1

AR

EA

2

AR

EA

3

Areas definition basedon SENSITIVITY ANALYSIS

and measurements


ResourceParticipation

shareP

reductionP

increaseWind 30% � �

PV 50% � �

CHP 10% � �

Active Demand 20% � �

∆P [MW]

-15

-10

-5

0

5 04

812

1620

240

50

100

150

200

Co

st €

/MW

h

P reduction

P increase

Time [h]

∆P [MW]-12 -10 -8 -6 -4 -2 0 2 4

40

60

80

100

120

140

160

Co

st €

/MW

h

∆P [MW]

h. 11 h. 20

0

40

80

120

160

0 4 8 12 16 20 24

Co

st [

€/M

Wh

]

time [h]

WIND PV CHP Active Demand

Application of Market Model 2

Assumptions• Time-varying availability and cost for ancillary services by

the distributed resources

Outcomes• Aggregated P/cost profiles for each time instant


Proposal for distributed storage integration in the MV gridConsidering application of MM3, storage units are considered connected either:

� to the primary substation (PS) on a dedicated line

� along the MV network feeders

Centralised storage unit:

� Supposed to face the deviations from the scheduled HV/MV exchange profile

Decentralised storage unit:

� Need to respect a daily charging cycle

� Could offer additional services in the ASM-D


� Allow the distributed storage to evaluate their optimal discharging profile while limiting the power flow from the main grid

Constraints:

∑ = =ni ix1 0

• the sum of the contributions is limited by the DoDmax possibly reduced by εu and εl

• the SoC value must return to the initial value:

��

��

• the power exchangeable by the storage is limited by its capability area and power share coefficient


Application of Market Model 3• Storage unit connected at the PS MV busbar

• Provision of ancillary services by distributed storage units

• Power profiles are applied to all MV network customers or Secondary Substations

• Random perturbations are introduced

0 4 8 12 16 202

4

6

8

10

12

Time [h]

P[M

W]

P profile Success Failure

EXPECTED OUTCOME

• Failure rate of the power profile compensation technique applied to the PS as a function of

i. Centralised storage size

ii. Number of distributed storage and respective size


Future work

• A sizing strategy for the centralised energy storage (connected at PS MV busbar) is being developed

• The centralised storage size should be reduced by the adoption of several distributed storages (which could also be used for network management purposes)

• A local market should involve private-owned storage units in the power profile compensation action in the Market Model 3


Coordinated control techniques for distributed resources in modern electric

distribution networks (smart grids )

Thanks for your attention

Massimiliano Coppo

[email protected]

centro studi di economia e tecnica dell’energia...

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