Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Planning and Operation of Demand-Side Flexibility
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems.ORCID iD: 0000-0001-6870-6104
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Power systems are changing with growing penetration of non-dispatchable renewable generation and increased demand of electric energy. More generation, transmission or distribution capacities are needed to balance the varying production and higher consumption. Demand-side flexibility is a potential solutionto tackle those challenges. By shifting the consumption time and temporarily increase or decrease the power demand, the demand-side flexibility can help to integrate more wind and solar energy in the system, alleviate network congestion and postpone the investment for grid reinforcement. Therefore, technical and regulatory measures are undergoing in many countries to encourage demand response and engage customers.

On the other hand, unlocking the flexibility will introduce more complexityand uncertainty on demand side. This would result in difficulties for different actors in power systems and power markets to make optimal decisionsin their planning and operation. The thesis addresses the problem by proposing methods to support the decision making of actors on demand side. Firstly, it develops models to facilitate residential customers and commercial electric vehicle fleet operators scheduling their shiftable appliances for reducing electricity cost. The willingness of households for responding to time-varying price is taken into account. Results from Stockholm Royal Seaport project are analysed to demonstrate such willingness. Secondly, the thesis develops models for the short-term planning of retailers and balance responsible players. Different approaches are deployed under price-taker and price-maker assumptions respectively. The planning concerns the price sensitivityof end customers and the risk related with certain bidding strategies.Thirdly, the thesis proposes models to coordinate and aggregate the flexible charging power of electric vehicles to provide regulation service on the balancing market. The models encompass the decision process from day-aheadplanning to real-time operation management. The proposed models in the thesis are based on the rules of Nordic electricity market and could be further developed for adapting to other market frameworks. Stochastic programmingis applied to address the uncertainties about consumption and market behaviours.In addition, the thesis discusses the impacts of demand response interms of generation cost, system reliability and market price. It shows that a widely implemented demand response can reduce the total generation cost, improve the reliability of supply and decrease the market price.

Abstract [sv]

Elkraftsystemet förändras med ökad förnybar produktion och ökad efterfrågan på elektrisk energi. Mer produktions-, transmissions- och distributionskapacitet behövs för att balansera varierande produktion och högre konsumtion. Förbrukningsflexibilitet kan vara en del i lösningen på dessa utmaningar. Genom att ändra tid för elanvändningen och tillfälligt öka eller minska lasten kan förbrukningsflexibilitet bidra till att integrera mer vind- och solkraft i systemet, undvika tillfällig överbelastning av nätet och minska behovet av nyinvesteringar i nätet. Därför pågår i många länder en utveckling av både teknik och regelverk för att uppmuntra förbrukningsflexibilitet och engagera konsumenterna.

Å andra sidan medför ökad flexibilitet större komplexitet och osäkerhet på förbrukningssidan. Detta resulterar i svårigheter för olika aktörer i elsystemet och på elmarknaden att fatta optimala beslut om planering och drift. Denna avhandling studerar detta problem genom att föreslå metoder för att stödja beslutsprocessen för aktörer på förbrukningssidan. Till att börja med föreslås modeller för att underlätta planeringen av den flexibla elförbrukningen för hushållskunder och elbilpooler så att kostnaderna minimeras. Hänsyntas till hushållens villighet att anpassa sig till varierande elpriser. Resultat från Norra Djurgårdsstaden i Stockholm analyseras för att få en indikation på kundernas beteende. Vidare utvecklas korttidsplaneringsmodeller för att optimera budgivningen för elhandlare och balansansvariga. Olika metoder föreslås för pristagare respektive prissättare. Planeringen beaktar slutkundernas priskänslighet samt riskerna som är förenade med olika budstrategier. Slutligen föreslås modeller för att koordinera och aggregera laddning av elbilar för att tillhandahålla kapacitet till reglermarknaden. Modellerna omfattar beslutsprocessen från planeringen dagen före till realtid. De föreslagna modellerna baseras på reglerna för den nordiska elmarknaden och kan vidareutvecklas för att anpassas till andra marknadsregler. Stokastisk programmering tillämpas för att hantera osäkerheten om förbrukning och marknadens beteende. Dessutom diskuteras hur förbrukningsflexibilitet påverkar produktionskostnader, systemets tillförlitlighet och marknadspris. Avhandlingen visar att om förbrukningsflexibilitet genomförs i stor skala så kan leveranssäkerheten förbättras och elpriserna reduceras.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2019. , p. 87
Series
TRITA-EECS-AVL ; 2019:70
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-261674ISBN: 978-91-7873-333-0 (print)OAI: oai:DiVA.org:kth-261674DiVA, id: diva2:1359605
Public defence
2019-11-06, Kollegiesalen, Brinellvägen 8, Stockholm, 10:00 (English)
Opponent
Supervisors
Available from: 2019-10-11 Created: 2019-10-09 Last updated: 2019-10-11Bibliographically approved
List of papers
1. Purchase bidding strategy for a retailer with flexible demands in day-ahead electricity market
Open this publication in new window or tab >>Purchase bidding strategy for a retailer with flexible demands in day-ahead electricity market
2017 (English)In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 32, no 3, p. 1839-1850Article in journal (Refereed) Published
Abstract [en]

The paper aims to determine the day-ahead market bidding strategies for retailers with flexible demands to maximize the short-term profit. It proposes a short-term planning framework to forecast the load under dynamic tariffs and construct biding curves. Stochastic programming is applied to manage the uncertainties of spot price, regulating price, consumption behaviors and responsiveness to dynamic tariffs. A case study based on data from Sweden is carried out. It demonstrates that a real-time selling price can affect the aggregate load of a residential consumer group and lead to load shift towards low-price periods. The optimal bidding curves for specific trading periods are illustrated. Through comparing the bidding strategies under different risk factors, the case study shows that a risk-averse retailer tends to adopt the strategies with larger imbalances. The benefit lies in the reduction of low-profit risk. However, the aversion to risk can only be kept in a certain level. A larger imbalance may lead to a quick reduction of profit in all scenarios.

Place, publisher, year, edition, pages
IEEE, 2017
Keywords
bidding curve, dayahead market, Demand response, financial risk, imbalance settlement, retailer
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-198857 (URN)10.1109/TPWRS.2016.2608762 (DOI)000399998000017 ()2-s2.0-85027466668 (Scopus ID)
Note

QCR 20161222

QC 20171023

Available from: 2016-12-21 Created: 2016-12-21 Last updated: 2019-10-09Bibliographically approved
2. Estimating the price elasticity of residential power demand using a bottom-up approach
Open this publication in new window or tab >>Estimating the price elasticity of residential power demand using a bottom-up approach
2016 (English)In: Asia-Pacific Power and Energy Engineering Conference, APPEEC, 2016, Vol. 2016-December, p. 243-247, article id 7779505Conference paper, Published paper (Refereed)
Abstract [en]

The paper aims to estimate the flexibility of a residential consumer group in price-based demand response. It develops a model to simulate consumers' responsiveness to time-varying prices. The model is applied for 500 households under three dynamic prices. The cost saving, change of load curve and price elasticities are computed and compared. Results show that Time-of-Use network tariffs bring more incentives and higher flexibility than the fixed tariff. The setting of peak periods and peak/off-peak price ratio in Time-of-Use tariffs affects the results. Their influence may also vary for different delay options.

Keywords
Battery; Energy storage; Flywheel; Photovoltaic; Physical system modelling; Simulation; Smart grid
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-198856 (URN)10.1109/APPEEC.2016.7779505 (DOI)000391237400048 ()2-s2.0-85009992342 (Scopus ID)9781509054183 (ISBN)
Conference
2016 IEEE PES Asia Pacific Power and Energy Engineering Conference, APPEEC 2016; Empark Grand Hotel19-1#, Jiangong RoadXi'an; China; 25 October 2016 through 28 October 2016
Note

QC 20170201

Available from: 2016-12-21 Created: 2016-12-21 Last updated: 2019-10-09Bibliographically approved
3. Optimized operational management of an EVsharing community integrated with battery energystorage and PV generation
Open this publication in new window or tab >>Optimized operational management of an EVsharing community integrated with battery energystorage and PV generation
2018 (English)In: International Conference on the European Energy Market, EEM 2018, IEEE Computer Society, 2018, article id 8469821Conference paper, Published paper (Refereed)
Abstract [en]

Sharing schemes are emerging in residential and business sectors to reduce the purchase and operation cost of individuals. This paper proposes a framework to support the operational management of a shared EV fleet. An optimization algorithm is developed to coordinate the charging and reservation assignment using mixed integer programming. The integration with local PV production and battery storage is taken into account. A booking algorithm is also developed to determine whether a reservation can be accepted or not. Monte Carlo simulation is performed in the case study to demonstrate an application of the proposed framework with the Swedish travel patterns. The result provides an overview about the utilization rate of the fleet with different number of EVs, which can support the investment decision of an EV sharing community. The result also shows that the EVs and battery are effectively coordinated to minimize the total cost, satisfy the reservations and comply with grid limits.

Place, publisher, year, edition, pages
IEEE Computer Society, 2018
Series
International Conference on the European Energy Market, EEM, ISSN 2165-4077
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-248294 (URN)10.1109/EEM.2018.8469821 (DOI)2-s2.0-85055572394 (Scopus ID)9781538614884 (ISBN)
Conference
15th International Conference on the European Energy Market, EEM 2018; Lodz; Poland; 27 June 2018 through 29 June 2018
Note

QC 20190520

Available from: 2019-04-04 Created: 2019-04-04 Last updated: 2019-10-09Bibliographically approved
4. Price-Maker Bidding in Day-Ahead Electricity Market for a Retailer With Flexible Demands
Open this publication in new window or tab >>Price-Maker Bidding in Day-Ahead Electricity Market for a Retailer With Flexible Demands
2018 (English)In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 33, no 2, p. 1948-1958Article in journal (Refereed) Published
Abstract [en]

This study develops a short-term planning model to determine the bidding curves on a day-ahead market for a price-maker retailer with flexible power demand. It concerns the interactions between the spot price and the flexible demand. Both conditional value-at-risk and volume deviation risk are taken into account. A numerical study using the data from the Nordic electricity market is performed to investigate the influence of risk factors on the retailer's profit, risk levels, average spot price, and total consumption. Three types of price elasticity are compared to show that the retailer can benefit from the flexibility in demand side in some cases. The flexibility also leads to lower spot prices so that the customers in real-time price-based demand response can face a lower electricity price for per-unit power consumption.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Keywords
Bidding curve, demand response, price elasticity, price-maker, retailer, risk
National Category
Economics Energy Systems
Identifiers
urn:nbn:se:kth:diva-224017 (URN)10.1109/TPWRS.2017.2741000 (DOI)000425530300070 ()2-s2.0-85028448673 (Scopus ID)
Note

QC 20180323

Available from: 2018-03-23 Created: 2018-03-23 Last updated: 2019-10-09Bibliographically approved
5. Planning and operation models for an EV sharing community in spot and balancing market
Open this publication in new window or tab >>Planning and operation models for an EV sharing community in spot and balancing market
2019 (English)In: IEEE Transactions on Smart Grid, ISSN 1949-3053, E-ISSN 1949-3061Article in journal, News item (Refereed) Published
Abstract [en]

An EV sharing scheme is emerging in residential and business sector. It enables community members to share EVs and make reservations when they plan to use a car. The paper proposes a framework for planning and operation of a shared EV fleet. The framework coordinates charging and reservation assignment, and supports the community to participate in wholesale electricity market. It includes two stochastic programming models for day-ahead planning and real-time operation management. Bids on spot market are determined in the day-ahead planning. A preliminary plan for the bids on balancing market, the charging schedule of each EV and the assignment of each reservation are also determined in this phase. The preliminary plan is further refined during the real-time operation management. A numerical study based on Swedish driving behaviours and Nordic electricity market rules is performed to demonstrate an application of the proposed framework. Examples of the bidding curves on spot and balancing market are illustrated. Results also show a dynamic assignment for reservations during the planning horizon, while the eventual assignment is determined during the real-time operation management. Comparison with a base case shows that the proposed models enable the community to benefit from participating in the wholesale electricity market.

National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-248293 (URN)10.1109/TSG.2019.2900085 (DOI)
Note

QC 20190520

Available from: 2019-04-04 Created: 2019-04-04 Last updated: 2019-10-09Bibliographically approved
6. Improving the efficiency of a hydro-thermal power system utilizing demand-side flexibility
Open this publication in new window or tab >>Improving the efficiency of a hydro-thermal power system utilizing demand-side flexibility
2015 (English)In: 2015 12TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET (EEM), 2015Conference paper, Published paper (Refereed)
Abstract [en]

Demand response has been identified as a solution to achieve more effective markets and facilitate the integration of more intermittent generations. This paper develops a model to estimate the influence of the potential demand-side flexibility on power generation systems. A case study shows that the exploitation of consumers' flexibility would lead to a reduction in total generation cost through the more efficient dispatch of generation resources. When the penetration of wind and solar power increases, the demand-side flexibility could enable a better utilization of these nondispatchable generation sources.

Series
International Conference on the European Energy Market, ISSN 2165-4077
Keywords
Demand-side flexibility, generation cost, load shift, intermittent generation
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-191044 (URN)10.1109/EEM.2015.7216687 (DOI)000380377200088 ()2-s2.0-84951958461 (Scopus ID)978-1-4673-6692-2 (ISBN)
External cooperation:
Conference
12th International Conference on the European Energy Market (EEM), MAY 19-22, 2015, Lisbon, PORTUGAL
Note

QC 20160825

Available from: 2016-08-25 Created: 2016-08-23 Last updated: 2019-10-09Bibliographically approved
7. Impacts of flexible demand on the reliability of power systems
Open this publication in new window or tab >>Impacts of flexible demand on the reliability of power systems
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Demand response provides flexibility to power systems through adjusting the power consumption. This study investigates the impact of flexible demands on the system reliability with real-time price-based demand response. It assumes that the power demand is sensitive to nodal price and the price is communicated to consumers as soon as it is cleared on market. The uncertainties of nodal price and potential flexibility are considered. Models are proposed for the optimal operation of a power system with and without demand response, respectively. The proposed models are evaluated through application to a 6-bus system using Monte Carlo simulation. The result shows that the reliability indices LOLP and EENS are improved for the system and for each bus when the demand is sensitive to nodal price. Moreover, the nodal prices decrease, reflecting a more efficient operation and a lower electricity price charged on consumers.

National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-250468 (URN)10.1109/ISGT.2018.8403357 (DOI)2-s2.0-85050701617 (Scopus ID)
Conference
2018 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)
Note

QC 20190520

Available from: 2019-04-30 Created: 2019-04-30 Last updated: 2019-10-09Bibliographically approved

Open Access in DiVA

fulltext(1667 kB)84 downloads
File information
File name FULLTEXT01.pdfFile size 1667 kBChecksum SHA-512
27fbf3dc637c7c1fe148138e4064906fb2895ecee0dbfd42f22acbd09fff0c0a32befdf9d59dc91820e242522637225678a43941b567141e97a86219b542a1dc
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Song, Meng
By organisation
Electric Power and Energy Systems
Other Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 84 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 430 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf