assessment of flexible demand response business cases in the smart grid gerrit jötten, anke...

Assessment of Flexible Demand Response Business Cases in the Smart GridGerrit Jötten, Anke Weidlich (SAP), Lilia Filipova-Neumann (FZI), Alexander Schuller (KIT)Frankfurt, June 07, 2011

21st International Conference on Electricity Distribution CIRED

© 2011 SAP AG. All rights reserved. 2

Agenda

The Project Context

Demand Response Concepts

Business Case Analysis

Conclusion

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!


Energy efficiency through ICT-enabled 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

Vision of the SmartHouse/SmartGrid Project

Demand Response Concepts


The PowerMatcher Approach

Market mechanism in a multi-agent system

Field tested in 25 households in the Netherlands Electricity trading via PowerMatcher protocol Global optimization via market mechanism Local statement of preferences via bids submitted to auctioneer agent


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


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


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

Business Case Analysis


Business Cases Involve Several Market Participants

Wholesale Market

DGOperator

DSO

Consumer/Prosumer

EnergyRetailer

TSO Large PowerProducer

Energy trade

Balancing Energy

Commodity subsystem

Technicalsubsystem

Physical Energy flow

BC1,5,9 BC 2,3,4

BC 6,7,8


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


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


Example 1 – Underlying Data

Balancing zone short, balancing area short

Balancing zone short, balancing area long

Balancing zone long, balancing area long

Balancing zone long, balancing area short

Overall Balance

Balance in case of

shortage

Stadtwerke Karlsruhe Netz

-1,725,251 1,054,870 € -208,761 € 318,339 € -560,803 € -1,406,912 €

Vattenfall Distribution Berlin

-8,961,104 € 830,441 € -235,014 € 1,091,880 € -7,273,797 € -7,869,224 €

Vattenfall Distribution Hamburg

-1,939,193 € 4,564,978 € -762,647 307,381 € 2,170,519 € -1,631,812 €

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)


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 PowerMatcher 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 €


Example 1 – Results

4.5)05.01(1.14.310

10

t

tC

Possible savings per customer (overall, not PM customer): 4.25 EUR per year

NPV calculation (in M€)

Sensitivities


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]


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

[PowerSupplyWiki]

Conclusion


SmartHouse/SmartGrid technologies provide business opportunities that have potential to refinance their investments

Initial hardware and IT integration investments must be brought down considerably

Some SmartHouse/SmartGrid 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

Project Objectives

Thank You!

Contact information:

Dr. Anke WeidlichSenior ResearcherSAP Research Center Karlsruhe+49 (0)6227 7 [email protected]

assessment of flexible demand response business cases in the smart grid gerrit jötten, anke...

Documents

sap ag

support slide

business case analysis

project context slide

auctioneer agent slide

lower tariffs slide

energy efficiency

energy management demand