matching renewable energy supply with building demand
TRANSCRIPT
Open Universiteit www.ou.nl
Matching renewable energy supply with building demandprofiles and storage at the neighborhood scaleCitation for published version (APA):
Boesten, S., & Ivens, W. (2019). Matching renewable energy supply with building demand profiles and storageat the neighborhood scale. Poster session presented at European Geosciences Union General Assembly 2019,Vienna, Austria.
Document status and date:Published: 12/04/2019
Document Version:Publisher's PDF, also known as Version of record
Document license:CC BY
Please check the document version of this publication:
• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences betweenthe submitted version and the official published version of record. People interested in the research are advised to contact the author for thefinal version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers.
Link to publication
General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.
• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain• You may freely distribute the URL identifying the publication in the public portal.
If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license above, pleasefollow below link for the End User Agreement:
https://www.ou.nl/taverne-agreement
Take down policyIf you believe that this document breaches copyright please contact us at:
providing details and we will investigate your claim.
Downloaded from https://research.ou.nl/ on date: 07 Jan. 2021
Matching renewable energy supply with building demand profiles and storage at the neighborhood scaleStef Boesten, MSc1; dr. Wilfried Ivens
Fifth generation district heating and cooling systems (5GDHC)Multi-temperature system where demand and supply of heat and cold is matched in time and space using networks and storage technologies at appropriate time and geographical scales.
• Hot water generated close to demand, stored short-term
• Medium temperatures used for space heating within cluster, buffered for few days
• Low temperatures transported between clusters, seasonal storage
• Heat and cold exchange between connected buildings
Context• Natural gas exit in the Netherlands
• Municipal heat visions and neighborhood approaches to be presented 2021
Goal• Generate optimized sizing solutions for insulation, conversion
technologies and storage for 5GDHC
• Developing a tool to assess the applicability of 5GDHC as an alternative to natural gas
MethodsThe tool is based on the energy hub concept, in which input energy flows are converted in an optimized way to meet demands.
• Neighborhood energy demand and characteristics converted into design day profiles
• Peak demand reduction from insulation measures and low-temperature
• Direct exchange of heat and cold between buildings within the cluster possible
• Optimal sizing of storage size, conversion techs, grid capacity
Case studyThe case consists of a specific neighborhood, where 858 dwellings and some local businesses will be connected.
• South of Netherlands, developed by Mijnwater B.V.
• Mixed apartments/ground based and homeowners/tenants
• Mostly existing buildings with natural gas heating
• 100 % connection rate wanted, aim is to exit natural gas
Faculty of Management, Science and TechnologyDepartment of Science
Flows, conversions and storage at different temperatures and spatial scalesThe system allows for heat to be used at each temperature level and spatial scale level. Heat can be cascaded up using heat pumps and down using heat exchangers, depending on where and when the demand takes place.
Conceptual modelFrom generic neighborhood characteristics an energy hub demand profile is created. This is used to optimize for simultaneous demand of heat and cold, using thermal insulation to reduce total demand and peak demand, sizing storage to optimize for self-consumption of heat and cold in the neighborhood, sizing heat pumps to bridge between the different temperature demands at different times and in different places.
Type, age, energy rating
Age, composition, income
Type, size, processes
Ener
gy d
eman
d
Time of day
Neighborhood aggregated energy demand on a typical design day
Heat Cold Electricity
Matching heat and cold demand
Sizing thermal insulation
Sizing storage and heat pumps
0
40
10
30
20
70
60
50
Backbone
Tem
pera
ture
[°C
]
Households and businesses:Final demands
Building and block:Processes and storage
Neighborhood and city:Heat and cold exchange
Heat pump
Heat pump
ATES
Water vessel
Hot water
Space heating
Cooling
Industrial processes
Waste heat
1Corresponding author: [email protected]
Dwellings
Households
Industry
Optimized demand curves, technology and decision support
Return flow
Cluster grid
BufferBuilding thermal mass
Geo-thermal