Active Response

A Network Optimisation Approach

Real Time Network Reconfiguration

for Operations’ Flexibility

Visit Innovation.ukpowernetworks.co.uk

Introductions: On The Webinar Today

John Dirkman, Nexant Product Manager

Luca Grella, Active Response Project Lead

Hamdi Shishtawi, Active Response ANM Lead

Mark Jaggassar, SGS Director of Grid Analytics

15:00IntroductionHamdi Shishtawi

15:05Active ResponseLuca Grella

15:15ANM Implementation and IntegrationMark Jaggassar and Hamdi Shishtawi

15:30Optimisation Engine DemonstrationJohn Dirkman

15:50 Q+A

Agenda

8.3M homes and businesses28% of UK Total

9.3GW Distributed Generation Connected32% of UK Total

16GW Peak Demand28% of UK Total

About UK Power Networks

About Smarter Grid Solutions

Global software company with European Headquarters

Implementing and managing 500 MW of DER under management with an additional 1 GW of contracts in delivery

Flexible technology create unique partner IP propositions

Multi-use case DERMS interfacing to the grid and market unlocks the true value of DER

Continuous R&D on top of proven platform ensures market leadership

World-class reference customers operationally using our technology

Breadth and depth of team covering technical and commercial aspects

Flexible architecture to configure and scale deployments

Our purpose is to develop and deliver the most flexible and scalable DER management software platform that enables energy companies to create and implement solutions for the transition to net zero carbon emissions.

About Nexant – At A Glance

Innovative Technology-Enabled Services, Software, and Consulting.

60+Electric and Gas Utility Clients

Wide Breadth of Program

ServicesFrom Grid

Operations to the Customer

Our Clients: Utilities & ISOs

750M+Annual kWh

Savings Delivered

20 Years of Proven Expertise in Technology

Enabled Program Design, Delivery,

and Grid Management

History:

• Founded in 2000• 380 Employees• 11 Offices 80+

Energy and Electrical Engineers

Active Response

Luca Grella

The Active Response Project - Introduction

Hardware Development and

Deployment

• Design, install, commission new SOP and SPB PEDs on HV & LV

Software Development and

Deployment

• Develop software and algorithms to coordinated solution

Project Planning, Trials

and Analysis

• Four live trials between mid-2019 and 2021

• Analyse benefits

Learning & Dissemination

• Document and share learning from live trials and research

Work Packages1. 2. 3. 4.

About

The project will demonstrate the following two

methods in four separate trials (2020-2021) to

maximise capacity:

• Network Optimise – Optimisation and

Automatic reconfiguration of HV & LV networks

in combination, using remote control switches

and Soft Open Points (SOPs).

• Primary Connect – Controlled transfers

between primary substations using a Soft

Power Bridge (SPB) to share loads and

optimise capacity.

ObjectivesLead:

Partners & suppliers:

Funded by Ofgem’s

Network Innovation

Competition (NIC).

• Duration: 2018-2022

• Five project partners,

lead: UKPN

• Total cost: ~£18.2m

• NIC funded: ~£13.8m

• UKPN funded: ~£3m

• External funds: ~£1.3m

Project Deliverables and Benefits

Increased network flexibility

Network optimisation

Network control benefits

Reduced CIs & CMLs

Network reinforcement

deferral

Spare capacity [kVA] release

Significant financial, capacity, and carbon benefits associated

with deferral

Reduction in customer disruption

Faster and more cost-effective distributed

generation connection offers

Ref Deliverable

1High Level Design Specification of Advanced Automation Solution

2 Trial Site Selection Criteria and Process Outcome

3 Learning from Hardware factory tests

4Learning from Commissioning and Operation of Active Response Software Solution tools

5Initial Learning from the Installation and Commissioning of Active Response Hardware

6Project technology handover, rollout and adoption into BaUplan

7Review of the Active Response Methods applicability in Scottish Power Energy Network licence areas

8 Presentation of findings from the project trials

9 Review of solution applications and project business case

Key Achievements to Date

SOP/SPB preliminary and detail design

completed

LB switch and monitors preliminary design

completed

Remotely controlled CB functional requirement

finalised

Optimization architecture defined

Offline trials

completed

4 Academic partners officially appointed

Deliverable 1, 2 and 3 delivered

Site selection methodology for SOPs

and SPBs defined

Active Response ANM system requirements

defined

SOP/SPB key testing completed

Site preparation/construction plan for first SPB ever

created in place

Enhanced RTUs (Type E) with required I/O

schedule required for advanced optimization

installed on site

Change reporting mechanism required for

automatic real time communication

PowerOn/RTU delivered

2T SOPs locations approved by Council

Dplan enhancements for BaU transition defined

The Project Products

ACTIVE NETWORK MANAGEMENT SYSTEM

Soft Power Bridge (SPB)5 MVA

Soft Open Points (SOP)260 & 400 kVA

LV Circuit Breakers & Link Box Switches

The Trials

Active HV

Active HV will demonstrate Network Optimise and the benefits of automated HV network optimisation only.

Network Optimise

ANM will be applied to the 11 kV network and the new generation of LV hardware including SOPs. The trial will demonstrate the benefits of the active reconfiguration of networks, by releasing capacity for new connection.

Primary Connect

Primary Connect will trial a SPB and demonstrate direct connection between two primary substations. The trial will show the ability of the SPB to release network capacity be managing primary substation peak demands.

Active Response

Active Response will demonstrate both project methods in combination. This will enable the complete solution to be trialled to prove that the technologies operate in conjunction with each other to maximise the benefits.

Active Network Management System

Mark Jaggassar

Advanced Network Model Based Analytics

Active Response leverages advanced network model-based analytics• Detailed representations of the grid that model the electrical characteristics• Enables Grid360’s suite of load flow based optimization techniques

Driven by live telemetry• Real-time measurements of voltage, current, and power provide the ability to

dynamically respond to the state of the electrical grid

Advanced optimization uncovers efficiencies in network operation• Given the real-time state of the network, is there a more optimal running

arrangement that would release capacity or mitigate power quality issues • Outcome is a set of recommended control actions for Active Response devices

Active Response devices• Remotely tele-controllable switching devices• Power electronics devices that regulate electrical flows at 11 kV and 400 V

Conceptual Model

Active Network Management System

Grid360 Optimisation Engine• AR Algorithms• Load Flow• Fault Level• State Estimation

ANM Strata• Overall ANM supervisory duties• Connection to live system• Enacting of services (such as

Grid360)• Instruction of control for ADMS

Harmonised Network Model• CIM format• Comprehensive network

information

Advanced Distribution Management System• PowerOn (Fusion/Advantage)• Real time connectivity to field

equipment• Connectivity to PI historian• Automation (APRS, PORT, etc.)• Real time control

Field Remote Terminal Units (RTU)• Data collection and aggregation• Connectivity to ADMS• Field device systematic polling• Unsolicited message responses

from both ends

Active Response Field Devices• Link box switches• Link box monitors• Internal software RTU

Active Response Field Devices• PEDs, LV CBs• DNP3 slaves• Unsolicited message initiation and

threshold

ICCP

API

DNP3

DNP3

DNP3

Operationalising Advanced Analytics

Simulation and

Optimization

Real time Control and

Automation

Local DER Control

Preventive Control Layer:

• Simulation and optimization based on real-time data to schedule or dispatch

against target objectives

Corrective (ANM) Control Layer:

• Responds to external stimulus and DER status to issue real-time setpoints

• Fast-acting autonomous control to ensure control actions or optimization

objectives are delivered and enforced

• All DER control / dispatch is through this unique layer

Fail Safe Control Layer:

• Using distributed algorithms to monitor DER compliance, communications

health and implement locally autonomous fail-safe controls

Layering of control is fundamental to delivering flexibility from DER

Grid360

UKPN Operations

Software Architecture

Optimisation Engine

Grid360

Load Flow

State Estimation

Contingency

Forecasting

Optimisation

Can be operated in offline mode, using

offline models and imported datasets.

Active Response Optimisation

Active HV

Active LV

Secondary Connect

Primary Connect

Active Network Management (ANM) Platform

Strata

Advanced Distribution Management System (ADMS)

PowerOn

Distribution Network

Network Assets, exchanging data via Remote Terminal Units (RTUs)

Active Response Network EquipmentSPBs and SOPs

Link box switches and monitors

LV circuit breakers

RMUs

Active Response ADMS Functionality

RTUs notify PowerOn of constraint

SOPs, SPBs and LV switches represented in PowerOn

Active Response ANM functionality

Provide Grid360 analytics with live telemetry

Failsafe control to implement optimal control schemes

KEY Active Response Scope Wider ANM project

Active Response Online Solution Architecture

Existing business as usual

Test Harness Software Architecture

Optimisation Engine

Grid360 Load Flow

State Estimation

Contingency

Forecasting

Optimisation

Can be operated in offline mode, using offline

models and imported datasets.

Active Response Optimisation

Active HV

Active LV

Secondary Connect

Primary Connect

Active Network Management (ANM) Platform

ANM Strata

Active Response Test Harness Functionality

Simulate changes to network based on optimisation outputs

Provide simulated measurement data based on historical data

Active Response ANM functionality

Provide Grid360 analytics with live telemetry

Failsafe control to implement optimal control schemes

KEYActive Response Scope Wider ANM project

ANM Test Harness Interface

ANM Strata – Grid360

Active Response Offline Testing Architecture

Input / output data

Tests and Results

Hamdi Shishtawi

Some Results Trial 1 Trial 2 Trial 3 Trial 4

Voltage 11kV 11kV and 0.4kV 11kV 11kV and 0.4kV

Number of nodes ~400 ~2600 ~230 ~2600

Number of loads simulated

~150 ~1650 ~60 ~1700

Telemetry the number of optimisable loads

~50 loads (1 years’ worth of half hourly P and Q data

for every load point)

~1800 loads (4 weeks’ worth of

half hourly P and Q data for

every load point)

~60 loads (1 year worth of half hourly P

and Q data for every load

point)

~1800 loads (4 weeks’ worth of

half hourly P and Q data for

every load point)

Execution time for

1-week time series simulation

2 hours 7 hours 45 minutes 7 hours

Output file size for 1-week time series simulation

750kB 1100kB 750kB 1100kB

Number of 1 day runs

61 24 0 15

Number of 1 week runs

6 20 44 16

Total time simulated

~100 days ~160 days ~300 days ~130 days

Total computation time

~30 hours ~160 hours ~30 hours ~130 hours

“In total, nearly 2 years of time-series data was generated over the course of the offline trials to

characterize the impacts of Active

Response”

Trial 1 Site

Trial 1 Site

Managing the Anticipated EV Peaks - Active HV

200

300

400

500

600

700

800

900

1000

1 9 :1 2 2 2 :4 8 0 2 :2 4 0 6 :0 0 0 9 :3 6 1 3 :1 2 1 6 :4 8 2 0 :2 4 0 0 :0 0 0 3 :3 6

LOA

D L

EVEL

(A

)

TIME

160% EV Peaks Winter 2019 Peak Day

Instance

NumberTime Stamp

Number of

Resolved

Buses

Resolved

Branch

Overflow (A)

Resolved

Branch

Overflow (%)

1 12/12/2019

18:00

1 0.218827 100%

2 12/12/2019

18:30

1 0.100317 100%

3 12/12/2019

19:00

0 0.129392 87%

Instance

NumberTime Stamp

Number of

Resolved

Buses

Resolved

Branch

Overflow

(kVA)

Resolved

Branch

Overflow (%)

1 12/12/2019

18:00

6 3683.783197 93.65%

2 12/12/2019

18:30

15 4824.811226 80.03%

3 12/12/2019

19:00

0 9.17417238 0.11%

Monitored

Unmonitored

Trial 3 Site

Connecting Two Primary Substations - SPB

SeasonOptimisation Mode

P = Real Power,

No. Branch

overload before

optimisation

No. Branch

overload after

optimisation

Net resolved

overload by

SPB

Spring P optimisation 0 0 0

Summer P optimisation 0 0 0

Autumn P optimisation 0 0 0

Winter P optimisation 2 0 2

Trial 4 Site

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Active Response – Future of the Network

Instance

NumberTime Stamp Active LV

Secondary

Connect

Resolved

Branches

Resolved

Overload (kVA)

Resolved

Overload (%)

102/04/2019

03:00Yes No 6 245.46 100.00%

202/04/2019

05:30Yes No 4 535.30 27.34%

304/04/2019

01:30Yes No 5 2314.59 100.00%

405/04/2019

11:30Yes Yes 2 485.78 43.87%

505/04/2019

13:30No Yes 1 5.22 0.50%

605/04/2019

17:00No Yes 1 110.40 25.53%

705/04/2019

17:30Yes No 9 380.25 100.00%

Grid360 Demo

John Dirkman

Thank You For Attending!

Visit Innovation.ukpowernetworks.co.uk

Active Network:A Network Optimisation Approach

John Dirkman, Nexant Product Managerjdirkman@nexant.com

Luca Grella, Active Response Project LeadLuca.Grella@ukpowernetworks.co.uk

Hamdi Shishtawi, Active Response ANM LeadHamdi.Shishtawi@ukpowernetworks.co.uk

Mark Jaggassar, SGS Director of Grid Analyticsmjaggassar@smartergridsolutions.com