Vision of Active Distribution Network and Congestion Management

Vision of Active Distribution Network and Congestion Management QIUWEI WU/Associate Professor Center for Electric Power and Energy (CEE) Technical University of Denmark (DTU) 29th October 2015 1 Corporate Presentation, October 23, 2015

Outline Introduction of DTU and CEE Vision of Active Distribution Networks Congestion Management in Distribution Networks

Total students ~11.500 including PhD 1.493 and Int. MSc 1.000 Research publications 5.534 QS World Engineering & Technology University Ranking 2015/2016: no. 2 in Scandinavia no. 10 in Europe

Mission DTU will develop and create value using the natural sciences and the technical sciences to benefit society Education Innovation Scientific advice Research

Center for Electric Power and Energy (CEE) Development of a reliable, cost efficient and sustainable energy system based on renewable energy Competence areas Electric power components Electric power grids Distributed energy resources and control Energy system operation and management Electricity markets and energy analytics Near 100 staff members incl. 30 PhD-students Located at Lyngby Campus and Risø Campus Bachelor and master programs Electrical Engineering / Wind Energy / Sustainable Energy / Electric Energy Technology Strategic partnerships

Strong National and International Collaboration Selected Partners Academic partners: (CH) (NL) (CN) (DK) (DK) (NO) (FI) (UK) (US) Commercial and industrial partners: (US) (HK) (SE) (SE) + many more (DK) (DK) (DK) (BE) (DK) (UK) (CH) (DK) (US) (DK) (DK) (DE) (DK) (DK) + many more Networks: (EU) (EU) (Global) (Global) (EU)

Renewable-based Energy System A Danish Strength Position World-record energy system with 39% wind power Ambitious energy strategy towards 100% renewable energy in 2050; 50% wind in power system in 2020 No. 1 in Europe in energy technology export Record in attracting EU-funding within energy Close collaboration between Stakeholders: authorities, companies and universities European hub for Smart Energy R&D and renewable energy integration Ref: The Danish Energy Authorities. Energy Technology Share of Export Ref: The Danish Energy Authorities et. al, 2013. Denmark no. 1 Ref: E-CORDA database per 1. marts 2014. Source: EnergyCamp 2008 Ref: European Commission Joint Research Center, 2013.

Wind Power in Denmark Year 2014 Danish wind power generation: 39.1% of the electricity consumption January 2014 Danish wind power generation: 63.3% of the electricity consumption December 21 th 2013 Danish wind power generation: 102% of the electricity consumption Single hour July 9 th 2015 Danish wind power generation: 140% of the electricity consumption March 11 th 2014 only 9 MW wind power generated out of installed 4,900 MW but 480 MW out of 580 MW solar units supplied the grid Source: Nord Pool Spot and Energinet.dk

Research Challenge addressed by CEE Development of a reliable, cost-efficient and sustainable energy system based on renewable energy Balancing the Power System: 2012 25% wind power Coherent Optimal Energy System: 2020 50% wind power 7000 6000 5000 Demand Wind Power Cost Effective Wind Energy: Demand Wind Power MWh/h 4000 3000 2000 Stability and Reliability: Changed Generation Landscape: 1000 0

Requirements of future distribution network Flexibility to meet customers needs and respond to challenges Provide accessibility for all customers especially for renewable energy sources (RES) Ensure and improve system security and quality of supply Provide an economically competitive system

Changes in production 5000 Without DG With DG 21.8 21.6 Active power flow [kw] 4000 3000 2000 1000 Voltage [kv] 21.4 21.2 21 20.8 20.6 0-1000 20 40 60 80 100 120 140 160 Time [h] 20.4 20.2 20 20 40 60 80 100 120 140 160 Time [h] Power flow through primary transformer Voltage at connection point of wind turbine

Changes in consumption 625 heat pumps added Loading of secondary transformers [%] Minimum voltage of LV networks [V] Time [h] Original Loading of primary transformer [MW]

Policies of electricity network Today networks are always over-dimensioned due to quality of supply obligations and missing possibility to control DERs Some companies are already forced to utilize production curtailment to manage their networks In future more flexibility is needed to integrate more RES and DERs in power system Controllability of distribution network via advanced ICT Decentralization of network management due to scale of the system

Active distribution network The management of network is utilizing active resources Integration of active resources as part of system instead of fit and forget principle is essential Active networks exploit DERs to optimize network asset investments and operational costs Synergy benefits may be achieved by coordinating the operation of DERs from the whole system viewpoint (instead of optimizing their operation individually from a single party s viewpoint)

Vision of future distribution network

Active network management ANM is based on distribution automation (DA) and DERs DA includes control centre information systems, substation automation, secondary substation automation and customer interface (e.g. smart meters) DA realizes the supervision of the network state, control of network breakers and switches, and monitoring and control of secondary substations, direct control of DERs and endcustomers DA also merges information from/to all actors interfaced to the distribution system

Primary technology Reliability enhancement SAIFI: MV cabling, relocation of lines, compensated grounding, over voltage protection, animal shields,... SAIDI: new substations, reclosers, remotely controlled switches Single customer: transfer switch, island operation (backup generator), Network hosting capacity for RES and DER On-load tap changers (MV/MV, MV/LV or LV/LV) FACTS devices Choice of voltage levels: 20 kv 30 kv, 400 V 1 kv MVDC and LVDC Congestion management

Monitoring, protection and control devices Complete network will be monitored Voltages and currents from all substations Fault indicators / locators Advanced Metering Infrastructure (AMI) Power quality meters Fault recorders Phasor measurement units Condition monitoring units New types of sensors (temperature, door position, ) Intelligent Electronic Devices (IEDs) will distribute decision making from control centre and primary substation along the MV and LV networks

Communication Distribution automation applies variety of communication technologies All primary substations are equipped with communication access for SCADA and possibly other IT systems (fibre optics, wireless) The number of secondary substations and MV switching stations including communication is increasing (wireless) Communication to smart meters is realised in principle by two alternative ways: PLC or wireless Ethernet is becoming the prevalent communication standard for all automation devices For substation automation, the most remarkable protocols utilizing Ethernet are IEC 60870-5-104, IEC 61850 GOOSE and MMS, Modbus/TCP and DNP 3.0 over LAN/WAN.

Active resources and aggregator concept DERs consist of distributed generation demand response loads storage micro-grids DSO s units OLTCs STATCOM distribution automation DERs are operated by Commercial aggregator to operate on energy market Technical aggregator to verify technical feasibility of commercial actions and to utilize DERs for network management

Control of DERs from DSO s viewpoint Connection requirements Establish technical capabilities for the control of DERs Grid tariff Incentives to shift net load demand to network off-peak hours DSO s own resources On-load tap changer Reactive power compensation and FACTS Contracted control Non-market based control actions, e.g. voltage control of DG units Flexibility services from Commercial Aggregator Emergency control Control actions before the protection is activated

Ideal Grid for All (IDE4L) Objective: Define, develop and demonstrate active distribution network management Budget: Total budget: 8,012,972.63 Euro Requested budget from EU: 5,750,000.00 Euro Partners: 11 partners from 7 EU countries 3 DSOs involved for demonstration CEE and Østkraft Tasks: Congestion management and optimal voltage control (CEE) Demonstration (Østkraft) Use of PowerLabDK: Real time tests of automation (RTDS) Field demonstration (Bornholm)

Main objectives Demonstrate the automation system and selected use cases for active distribution network Develop an advanced distribution network automation system enabling utilization of flexibility services of DERs and their aggregators Develop advanced functions for monitoring and control of the whole network

From laboratory to field trials Ideas and component integration tested in lab Software and hardware tested in field

Congestion Management in Distribution Networks Congestions in Distribution Networks Power component overloading Over-voltage or under-voltage condition

Congestion Management in Distribution Networks Congestion Management Methods in Distribution Networks Direct control methods 1. Reconfiguration 2. Reactive power control 3. Active power control Over-voltage or under-voltage condition 1. Dynamic tariff 2. Distribution grid capacity market 3. Intro-day shadow price 4. Flexible service market

Congestion Management in Distribution Networks

Congestion Management in Distribution Networks Electric vehicle fleet operator optimization

Congestion Management in Distribution Networks Distribution system operator optimization

Published papers on congestion management 1. N. O Connell, Q. Wu*, J. Østergaard, A. H. Nielsen, S. T. Cha and Y. Ding, Dayahead Tariffs for the Alleviation of Distribution Grid Congestion from Electric Vehicles, Electric Power Systems Research, Vol. 92, pp. 106-114, Nov. 2012. 2. R. Li, Q. Wu*, S. Oren, Distribution Locational Marginal Pricing for Optimal Electric Vehicle Charging Management, IEEE Transactions on Power Systems, No. 1, Vol. 29, pp. 203 211, Jan 2014. 3. W. Liu, Q. Wu*, F. Wen, J. Østergaard, "Day-Ahead Congestion Management in Distribution Systems through Household Demand Response and Distribution Congestion Prices, IEEE Transactions on Smart Grid, vol. 5, no. 6, pp. 2739-2747, Nov. 2014. 4. S. Huang, Q. Wu*, S. Oren, R. Li and Z. Liu, Distribution Locational Marginal Pricing through Quadratic Programming for Congestion Management in Distribution Networks, IEEE Transactions on Power Systems, Vol. 30, No. 4, pp. 2170-2178, Jul. 2015. 5. S. Huang, Q. Wu*, L. Cheng, Z. Liu, Optimal Reconfiguration Based Dynamic Tariff for Congestion Management and Line Loss Reduction in Distribution Networks, IEEE Transactions on Smart Grid, Vol. PP, No. 99, pp. 1-9, April 2015 DOI: 10.1109/TSG.2015.2419080.

37 Corporate Presentation, October 23, 2015 Thank you for your attention