Assessment of Flexible Demand Response Business Cases in

Assessment of Flexible Demand Response Business Cases in the Smart Grid Gerrit Jötten, Anke Weidlich (SAP), Lilia Filipova-Neumann (FZI), Alexander Schuller (KIT) Frankfurt, June 07, 2011 21 st International Conference on Electricity Distribution CIRED

The Project Context

Motivation Electricity generation… … is becoming more decentralized … increasingly relies on fluctuating renewables The consumer… … wants a reliable energy supply … wants to minimize cost and footprint … has flexibility to offer … doesn’t want to be bothered too much, … and wants to decide for herself! © 2011 SAP AG. All rights reserved. 4

Vision of the Smart. House/Smart. Grid Project Energy efficiency through ICTenabled collaborative aggregations of smart houses Customer-interactive in-house technology for energy management Demand side: real-time information, dynamic tariffs Customer as prosumer: generation within the house integrated into the system Interaction with the Smart Grid Distributed control in a decentralized energy world Intelligent agent-based control Web services at the device level and at higher system levels © 2011 SAP AG. All rights reserved. 5

Demand Response Concepts

The Power. Matcher Approach Market mechanism in a multi-agent system Field tested in 25 households in the Netherlands Electricity trading via Power. Matcher protocol Global optimization via market mechanism Local statement of preferences via bids submitted to auctioneer agent © 2011 SAP AG. All rights reserved. 7

The Bi-Directional Energy Management Interface Approach Day-ahead tariff profile as load shifting incentive Field tested in 100 households in Germany Automated optimization of appliance operation No real-time control (extensions for real-time signals planned) Win-win through lower procurement costs and potentially lower tariffs © 2011 SAP AG. All rights reserved. 8

The MAGIC Approach Micro-grid operation in critical grid situations Field tested in in 10 households in Greece Multi-agent system in which households agree on priorities for load shedding Provision of ancillary services such as load shedding support Provides grid cell islanding and black-start support © 2011 SAP AG. All rights reserved. 9

The Three Field Trials All three technologies are tested in the field Dutch trial Focus: scalability tests Finished German trial Focus: usability, user acceptance Running Greek trial Focus: critical grid situations Finished Overall: Enterprise integration and business case analysis © 2011 SAP AG. All rights reserved. 10

Business Case Analysis

Business Cases Involve Several Market Participants Wholesale Market BC 1, 5, 9 DG Operator Energy Retailer Consumer/ Prosumer Energy trade Balancing Energy BC 2, 3, 4 TSO Large Power Producer Commodity subsystem Technical subsystem DSO BC 6, 7, 8 © 2011 SAP AG. All rights reserved. Physical Energy flow 12

Example 1: Balancing the BRP’s Portfolio Applying real-time control instrument BRP portfolio balancing Viable business case if hardware costs are <100 EUR per household Not all households need to participate ~10% smart houses in a cluster can be sufficient to balance a portfolio Another option: Offering reserve at the balancing power market © 2011 SAP AG. All rights reserved. 13

Example 1 – Assumptions Analysis with net present value method Common assumptions Roll-out of smart metering, independently of the business case Usage of existing communication infrastructure (e. g. DSL connection, Wi-Fi, …) Heat-led manageable µCHP units Manageable loads Freezer (runs Ø 8 hours/day with 106 W) Refrigerator (runs Ø 8 hours/day with 140 W) Washing machine (890 Wh per cycle; 141 -245 cycles per year) Dryer (2, 460 Wh per cycle; 102 cycles per year) Dishwasher (1, 190 Wh per cycle; 203 cycles per year) Balancing actions taken in the cluster do not influence overall balancing zone imbalance/price © 2011 SAP AG. All rights reserved. 14

Example 1 – Underlying Data Balance area of a DSO is considered Balance area for differences (Differenzbilanzkreis) Costs for balancing power in specific balancing zone Avoidance of shortage situations (because they are expensive on average) Balancing zone short, balancing area short Stadtwerke Karlsruhe Netz Vattenfall Distribution Berlin Vattenfall Distribution Hamburg Balancing zone short, balancing area long Balancing zone long, balancing area short Overall Balance in case of shortage -1, 725, 251 1, 054, 870 € -208, 761 € 318, 339 € -560, 803 € -1, 406, 912 € -8, 961, 104 € 830, 441 € -235, 014 € -1, 939, 193 € 4, 564, 978 € © 2011 SAP AG. All rights reserved. -762, 647 1, 091, 880 € -7, 273, 797 € -7, 869, 224 € 307, 381 € 2, 170, 519 € -1, 631, 812 € 15

Example 1 – Costs House energy management system One aggregator / router per household (75 €) Substation aggregator One per 100 – 200 households (1, 500 €) Controller for DER devices One chip for per device (1 €) IT solution For integrating Power. Matcher software in the DSOs IT system (500, 000 €) Installation at the households Hourly labor costs for installation: 46 € Four hours installation per household Total ~200 € © 2011 SAP AG. All rights reserved. 16

Example 1 – Results Possible savings per customer (overall, not PM customer): 4. 25

Example 2: Minimizing Procurement Costs Variable tariffs Incentive for customers to switch to low-price times Not feasible for standard load profile customers such as in Germany today Savings per household are modest with current price spreads Integration with additional services is key [EEX 2011] © 2011 SAP AG. All rights reserved. 18

Example 3: Avoiding Blackouts Negotiated load shedding Keeping grid cells in islanding mode with local generation Business case depends on willingness to pay for avoidance of blackouts Viable for systems with low grid reliability Can be combined with peak shaving [Power. Supply. Wiki] © 2011 SAP AG. All rights reserved. 19

Conclusion

Project Objectives Smart. House/Smart. Grid technologies provide business opportunities that have potential to refinance their investments Initial hardware and IT integration investments must be brought down considerably Some Smart. House/Smart. Grid technologies can only be applied if the regulatory framework is changed or the availability of data on current grid situations is enhanced (Real-time) balancing and power supply enhancement are interesting applications for SH/SG technologies It is less interesting to only focus on procurement cost minimization for an energy retailer © 2011 SAP AG. All rights reserved. 21

Thank You! Contact information: Dr. Anke Weidlich Senior Researcher SAP Research Center Karlsruhe +49 (0)6227 7 52550 anke. weidlich@sap. com