Smart Control of Low Voltage Grids Christian Oerter, Nils Neusel-Lange

Wuppertal University – Institute of Power System Engineering

Germany

July 31st 2014

IEEE Power & Energy Society General Meeting 2014 Panel Session:

Advanced Modelling and Control of Future Low Voltage Networks

1

Current Challenges on Distribution Level

• Integration of decentralized generation units, especially due to the German “Energiewende”

• “Electrification” of air conditioning for buildings (heat pumps and air cons)

• Future integration of electric vehicles and storage units

• Increased capacity utilization, overloading possible

• Exceedance of the permitted voltage range

Voltage

Length of the line

Ur + 10%

72,1A 129,8A

187,6A

Overloading!

NAYY 4x50 SE Ith,max = 142A 10kV/0,4kV

St,r = 400kVA

2

Future Distribution Grids – conventional or smart?

Problem: Grid capacity bottleneck

Conventional grid expansion measures

Smart Grid

Solution: Intelligent grid expansion

Substitution

Technology Options: Ancillary Services Smart Outage Management Smart Market Condition Monitoring

Additional features

Technical and economical benefits

3

Monitoring and Control System for LV-grids

4

Monitoring and Control System for LV-grids

• Process sequence: – Cyclic operation

– Virtually real-time (10sec cycle interval)

• Optimization tasks: – Robustness

– Performance

• Main modules: – Grid State Identification

– Control Process

Grid State Identification

Control Demand Reset Demand

Update Process Values

System Initialization

Grid State Analysis

Control Process

Set Points

5

Monitoring of LV-grids

• Grid State Identification – Minimal sensor environment

due to cost efficiency

– Estimation of load and feed currents to compensate the lack of information

– Phase-selective power flow calculation

• Grid Topology Identification – During grid operation switching

operations can be necessary

– Grid State Identification depends on accurate topology for power flow calculations

– Automatic topology-change recognition

Topology II

Topology I

Low Voltage Grid State Identification

including predictive methods

Cycle Inputs:Slack-VoltageMeasured Branch Currents

uSlack , iBranch,Meas

Static Grid Parameters:TopologyTechnical Data

R’Branch X’Branch LBranch

Unique Grid State

uLoad , iBranch , sSlack

I/O parameters of the developed algorithm

6

Voltage and Power Control for LV-grids

• Combination of control facilities (actuators) for LV-grids, e.g. controllable transformers with OLTC, generation units, loads or storage units, in a consecutive, 3-stage control model – Avoidance of active power curtailment as long as possible!

– Active power curtailment necessary to resolve overloading conditions!

Ur +10%

Ur -10%

1st stage: controllable transformer

2nd stage: power factor control

3rd stage: active power control

1.

2. 3.

# nodes/line length

3-stage control model in an infeed-oriented scenario

7

Voltage and Power Control for LV-grids

• Influencing parameters on actuator effectivity: – Grid topology

– Position of the actuator within the grid

– Control range of the actuator

• Task for the control algorithm: Identification of the most suitable actuator to resolve a given critical grid state – Maximum effectivity of the actuator leads to minimum influence on

customers and decentralized generation units

– Compensation of customers/producers for curtailed active power by the grid operator

– German government consideration: 5% curtailment of the annual energy yield without compensation

8

Sensitivity-based Control for LV-grids

• Control algorithm is based on runtime sensitivity analysis – Sensitivity matrix describes the influence of an actuator

on the grid’s nodes and branches

– Sensitivity matrix calculation is based on the grid’s topology data, separately for power factor control and active power control

Transformer with OLTC

400rTS kVA

40rP kW 40rP kW 40rP kW

40rP kW 40rP kW 40rP kW

Zone 1

Zone 2

1 2

3 4 5 6 7

8 9 10 11 12

sensor Um, Im, Pm, Qm, cos φm

(m ϵ [L1, L2, L3] : phase)

sensor/actuator

Cable

Overhead lines

9

Direct Control Strategy for LV-grids

• Characteristics: – Sequential process sequence

– Short cycle times

– 1 set point per cycle

– Multiple cycles for resolving critical grid states (where necessary)

Grid State Analysis

Grid State Identification

Update Process Values

System Initialization

Set Points

ControlProcess

Control Model Stage 1:Direct Voltage Control

Control Model Stage 2:Power Factor Control

Control Model Stage 3:Active Power Control

Control Demand Reset Demand

10

Optimized Control Strategy for LV-grids

• Characteristics: – Iterative process sequence

– Increased cycle times

– Multiple set points per cycle

– Resolving critical grid states within a single cycle (if technically possible)

Grid State Analysis

Grid State Identification

Update Process Values

System Initialization

Set Points

ControlProcess

Control Model Stage 1:Direct Voltage Control

Control Model Stage 2:Power Factor Control

Control Model Stage 3:Active Power Control

Set Point Verification

Control Demand Reset Demand

11

Virtual Measurements

Initialization

Smart Grid System(Virtual Entity)

Set Points

LV-Grid Simulator(Power Flow Calculation)

Scenario Setup

Node # Cycle #

Dev

iati

on

fro

m U

r [%

]

-15%

-10%

-5%

0%

5%

10%

15%

1

2

24

68

1012

-15

-10

-5

0

5

10

15

12

34

24

68

1012

-15

-10

-5

0

5

10

15

Node # Cycle #

Dev

iati

on

fro

m U

r [%

]

-15%

-10%

-5%

0%

5%

10%

15%

Simulation Results

• Comparison of both control strategies in case of an exceedance of the permitted voltage range

Optimized Control Strategy

Direct Control Strategy

1. Set point: OLTC 2. Set point : Power Factor 3. Set point : Power Factor

*12cos 0,95ind

2%U

*11cos 0,95ind

Simulation Environment

12

Field Experience

Tasks:

• Engineering tasks, social & legal tasks

• Validation of the developed algorithms

Results:

• GSI max. error: 1.5% – Estimation error: 1.0%

– Measurement error: 0.5%

• Control process pretest

27 loads

7 loads

11 loads6 loads

5 loads

3 loads

3 loads

5 loads

3 loads

3 loads

5 loads

7 loads

5 loads

24 loads

Substation #1

Substation #2

3 loads

Node #40

Node #214

Node #71

open cut-off point

closed cut-off point

13

Conclusion

• Cost-effective system, minimum of components

• Avoidance of critical grid states

• Better utilization of existing grid capacity

• Avoidance/Delay of expensive grid expansion measures

• Extension for MV-grid application under development

Lessons learned from field application:

• Smart Meters not useable as measurement devices a.t.m.

• Compensation of customers for curtailed active power

• Experience with power line communication technology

• Developed algorithms worked reliable in first tests – tuning and adaption for further improvement

14

Thank you for your attention!

christian.oerter@uni-wuppertal.de

http://www.evt.uni-wuppertal.de

15