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Flexibility prediction, scheduling and control of aggregated TCLs
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.ORCID iD: 0000-0002-4210-8672
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.ORCID iD: 0000-0003-3014-5609
2020 (English)In: Electric power systems research, ISSN 0378-7796, E-ISSN 1873-2046, Vol. 178, article id 106004Article in journal (Refereed) Published
Abstract [en]

There should be a constant balance between the demand and supply of electrical power. In Nordic countries, electricity markets have been formulated in such a way so as to facilitate this balance. These markets enable purchases, through bids, for buying and selling the energy (e.g., the day-ahead market) and the reserves (e.g., the frequency containment reserve for normal operation (FCR-N)). Demand response (DR) has received increased attention in recent years since it can efficiently support bidding in these markets. Aggregators, which act as mediators between end-users and the system operator, play an important role here. The aggregator contracts a large number of end-users for DR programs, and plans and controls their heterogeneous thermostatically controlled loads (TCLs), and offers their load flexibility to the markets. Taking into account the small market value of each contributing unit, the cost for the communication and control system enabling the DR service must be kept at a minimum. In this paper, we propose a framework which is adaptable to pre-existing and newly emerging TCLs, with no need for major re-design of the local control loops. We then design a strategy for the aggregator, to predict, schedule and control the aggregated flexibility of the contracted heterogeneous TCLs, in response to the DR signals and in the presence of end-users’ behavior uncertainties. In this strategy, we have applied a recurrent neural network (RNN) which learns the aggregated consumption of end-users and predict their aggregated load flexibility. The scheduling and control algorithms are then designed with the aim of participation in FCR-N market. We show that uncertainties in the prediction and scheduling are compensated in the control stage by activating back-up resources. A numerical study on 2000 number of detached houses has been conducted, which shows available 500 kW capacity for participation in the FCR-N market.

Place, publisher, year, edition, pages
Elsevier, 2020. Vol. 178, article id 106004
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Energy Technology; Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-244849DOI: 10.1016/j.epsr.2019.106004ISI: 000501654500002Scopus ID: 2-s2.0-85071689991OAI: oai:DiVA.org:kth-244849DiVA, id: diva2:1292819
Note

QC 20190301

Available from: 2019-03-01 Created: 2019-03-01 Last updated: 2024-03-15Bibliographically approved
In thesis
1. Hierarchical energy management in smart grids: Flexibility prediction, scheduling and resilient control
Open this publication in new window or tab >>Hierarchical energy management in smart grids: Flexibility prediction, scheduling and resilient control
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The electric power industry and society are facing challenges and opportunitiesof transforming the present power grid into a smart grid. Energymanagement systems (EMSs) play an important role in smart grids. A generalhierarchical structure for EMSs is considered here, which is composed ofa lower layer and an upper layer.

The first research objective of the thesis is detailed modeling, schedulingand control of flexible loads at the lower layer of EMSs. To do this, a wellstudiedframework has been extended, which focuses on scheduling of staticloads and dynamic loads for home energy management systems (HEMSs).Then, a robust formulation of the framework is proposed, which takes theuser behavior uncertainty into account so that the cost of optimal schedulingof appliances is less sensitive to unpredictable changes in user preferences.Considering that the optimization algorithms in the proposed framework canbe computationally intensive, an efficient plug-and-play policy is proposedand validated through several simulation studies.

The second research objective is to predict, plan, and control the aggregatedflexible load at the upper layer. Here, an iterative distributed approachamong aggregator and HEMSs is designed, to maximize the aggregated profitmade out of the shared energy storage system, while technical and operationalconstraints are satisfied. In addition, a strategy is proposed for flexibilityprediction of aggregated heterogeneous thermostatically controlled loads ina single micro-community of households. Then, algorithms are designed forplanning and control of aggregated flexibility in several micro-communities,to be used for bidding in energy and reserve markets.

To meet these research objectives, the control systems in the hierarchicalEMSs are connected over IT infrastructures and are in interaction with endusers.While this is done to achieve economical and environmental goals,it also introduces new sources of uncertainty in the control loops. Thus,the third research objective is to design policies to make the EMSs resilientagainst uncertainties and cyber attacks. Here, the user behavior uncertaintyhas been modeled, and a robust formulation is designed so that the optimalsolution for scheduling of appliances is more resilient to the uncertainties. Inaddition, fault-tolerant control techniques have been applied to a hierarchicalEMS to mitigate cyber-physical attacks, with no need for major re-designof the local control loops in already existing EMSs. Moreover, stability andoptimal performance of the proposed attack-resilient control policy have been proven.

Abstract [sv]

I samband med den pågående omvandlingen av nuvarande elsystem tillsmarta elnät finns både utmaningar och möjligheter för elkraftindustrin. Såkallade energihanteringssystem (EMS) spelar en viktig roll i smarta elnät. Härbehandlas en generell hierarkisk struktur för EMS, bestående av två lager, ettlägre och ett övre lager.

Det främsta målet i avhandlingen är detaljerad modellering, schemaläggningoch styrning av flexibla laster i det lägre lagret av EMS. Ett tidigarestuderat ramverk som fokuserar på schemaläggning av statiska och dynamiskalaster för hushållens energihanteringssystem (HEMS) har därför vidareutvecklats.Vidare föreslås en robust formulering av ramverket som tarhänsyn till användarens beteendeosäkerhet så att kostnaden för optimal schemaläggningav apparater blir mindre känslig för oförutsägbara förändringar ianvändarpreferenser. Eftersom att optimeringsalgoritmerna kan vara beräkningsintensivaföreslås och valideras en effektiv plug-and-play-metod genomflera simuleringsstudier.

Ett annat syfte har varit att förutsäga, planera och styra den aggregeradeflexibla lasten i det övre lagret i EMS. Därför har ett iterativt distribuerattillvägagångssätt för aggregat och HEMS utformats för att maximera vinstenfrån det delade energilagringssystemet, samtidigt som tekniska och operativabegränsningar uppfylls. Dessutom föreslås en strategi för att förutsägaflexibiliteten hos aggregerade heterogena termostatstyrda belastningar i ettmikrosamhälle bestående av flera hushåll. Vidare utformas algoritmer för planeringoch kontroll av aggregerad flexibilitet i flera mikrosamhällen, som kananvändas för att delta på energi- och reservmarknader.

För att möta dessa forskningsmål kopplas styrsystemen i de hierarkiskaEMS-systemen ihop över IT-infrastruktur och samverkar med slutanvändare. Detta görs för att uppnå ekonomiska och miljömässiga mål, men kan ocksåskapa nya källor till osäkerhet i kontrollslingorna. Det tredje forskningsmåletär således att utforma metoder för att göra EMS motståndskraftiga motosäkerheter och cyberattacker. Här har osäkerheter i användarbeteenden modelleratsoch en robust formulering utformats för att göra schemaläggningav apparater mer motståndskraftig mot osäkerhet. Dessutom har feltolerantakontrolltekniker applicerats på en hierarkisk EMS för att mildra cyber-fysiskaattacker, utan att det behövs någon större förändring av de lokala kontrollslingornai redan befintliga EMS. Vidare har stabilitet och optimal prestandaför den föreslagna attackmotståndskraftiga kontrolltekniken bevisats.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2019. p. 55
Series
TRITA-EECS-AVL ; 2019:20
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Energy Technology
Identifiers
urn:nbn:se:kth:diva-244843 (URN)978-91-7873-123-7 (ISBN)
Public defence
2019-03-22, K1, Teknikringen 56, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

QC 20190301

Available from: 2019-03-01 Created: 2019-02-28 Last updated: 2022-06-26Bibliographically approved

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Paridari, KavehNordström, Lars

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