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Madani Larijani, HatefORCID iD iconorcid.org/0000-0001-7354-6643
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Publications (10 of 57) Show all publications
Shahcheraghian, A., Madani Larijani, H. & Ilinca, A. (2024). From White to Black-Box Models: A Review of Simulation Tools for Building Energy Management and Their Application in Consulting Practices. Energies, 17(2), Article ID 376.
Open this publication in new window or tab >>From White to Black-Box Models: A Review of Simulation Tools for Building Energy Management and Their Application in Consulting Practices
2024 (English)In: Energies, E-ISSN 1996-1073, Vol. 17, no 2, article id 376Article, review/survey (Refereed) Published
Abstract [en]

Buildings consume significant energy worldwide and account for a substantial proportion of greenhouse gas emissions. Therefore, building energy management has become critical with the increasing demand for sustainable buildings and energy-efficient systems. Simulation tools have become crucial in assessing the effectiveness of buildings and their energy systems, and they are widely used in building energy management. These simulation tools can be categorized into white-box and black-box models based on the level of detail and transparency of the model’s inputs and outputs. This review publication comprehensively analyzes the white-box, black-box, and web tool models for building energy simulation tools. We also examine the different simulation scales, ranging from single-family homes to districts and cities, and the various modelling approaches, such as steady-state, quasi-steady-state, and dynamic. This review aims to pinpoint the advantages and drawbacks of various simulation tools, offering guidance for upcoming research in the field of building energy management. We aim to help researchers, building designers, and engineers better understand the available simulation tools and make informed decisions when selecting and using them.

Place, publisher, year, edition, pages
MDPI AG, 2024
Keywords
BES, black-box, building energy, deep learning, machine learning, simulation tool, white-box
National Category
Building Technologies Energy Engineering
Identifiers
urn:nbn:se:kth:diva-343161 (URN)10.3390/en17020376 (DOI)001149088200001 ()2-s2.0-85183330410 (Scopus ID)
Note

QC 20240208

Available from: 2024-02-08 Created: 2024-02-08 Last updated: 2024-02-08Bibliographically approved
Zhang, C., Wu, X., Zhao, S., Madani Larijani, H., Chen, J. & Chen, Y. (2024). Multi-agent simulation of the effects of Japanese electricity market policies on the low-carbon transition. Energy Strategy Reviews, 52, Article ID 101333.
Open this publication in new window or tab >>Multi-agent simulation of the effects of Japanese electricity market policies on the low-carbon transition
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2024 (English)In: Energy Strategy Reviews, ISSN 2211-467X, E-ISSN 2211-4688, Vol. 52, article id 101333Article in journal (Refereed) Published
Abstract [en]

Market policies play a crucial role in facilitating the transition to a low-carbon society by restructuring the electricity market and influencing stakeholder behavior. Policymakers are concerned with how to implement these policies in terms of their intensity, combination, and timing. However, existing research lacks effective simulation tools that can accurately capture the impact of market policies on individual decision-making in the electricity sector, which is essential to represent the complex impacts of the policy mix. To address this gap, we present an agent-based model for analyzing the Low Carbon Transition (LCT) in the electricity sector. Using the Japanese electricity sector as a case study, we design various subsidies, incentives, and liberalization policy scenarios to evaluate the role of market policies in facilitating LCT. We observed that, within the Feed-in Premium (FIP) system, above a subsidy threshold of 2 JPY/kWh or 20% of the electricity cost leads to overcompensation, resulting in a stagnation of LCT promotion. To address this stagnation, it is imperative to not only enhance demand-side incentives, such as carbon taxes but also expedite the advancement of the free trade market to prevent market-induced stagnation. A synergistic implementation of these three policies is crucial for the most efficient progression of LCT.

Place, publisher, year, edition, pages
Elsevier BV, 2024
Keywords
Agent-based model, Electricity sector, Low-carbon transition, Market policy, Quantitative analysis
National Category
Public Administration Studies
Identifiers
urn:nbn:se:kth:diva-344176 (URN)10.1016/j.esr.2024.101333 (DOI)001202779000001 ()2-s2.0-85185845880 (Scopus ID)
Note

QC 20240503

Available from: 2024-03-06 Created: 2024-03-06 Last updated: 2024-05-03Bibliographically approved
Song, Y., Rolando, D., Avellaneda, J. M., Zucker, G. & Madani Larijani, H. (2023). Data-driven soft sensors targeting heat pump systems. Energy Conversion and Management, 279, 116769, Article ID 116769.
Open this publication in new window or tab >>Data-driven soft sensors targeting heat pump systems
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2023 (English)In: Energy Conversion and Management, ISSN 0196-8904, E-ISSN 1879-2227, Vol. 279, p. 116769-, article id 116769Article in journal (Refereed) Published
Abstract [en]

The development of smart sensors, low cost communication, and computation technologies enables continuous monitoring and accumulation of tremendous amounts of data for heat pump systems. But the measurements, especially for domestic heat pump, usually suffer from incompleteness given technical and/or economic barriers, which prevents database of measurements from being exploited to its full potential. To this end, this work proposes a data-driven soft sensor approach for compensating multiple missing information. The soft sensors are developed based on an ANN model, an integrated multivariate polynomial regression model and empirical model by considering different constrains like data and information availability during model establishing process. All the three models have been validated against the data from a field test installation, and showed good performance for all the compensated variables. Of the three models, the ANN model shows the best performance for all soft sensors, but it has the highest requirement for additional resources to collect training data. While the integrated multivariate polynomial regression model demonstrates excellent accuracy for the majority of soft sensors with manufacturers' subcomponent data which needs no extra cost. Even though empirical model is not as accurate as the other two models, it still performs good accuracy with limited information from performance map. The methods developed in the present study paves the way for available measured data in thousands of installations to be fully utilized for innovative services including but not limited to: improved heat pump control strategies, fault detection and diagnosis, and communication with local energy grids.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Data driven, Heat pumps, Soft sensors, ANN, Regression, Database
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-324638 (URN)10.1016/j.enconman.2023.116769 (DOI)000933059100001 ()2-s2.0-85147371380 (Scopus ID)
Note

QC 20230309

Available from: 2023-03-09 Created: 2023-03-09 Last updated: 2023-03-09Bibliographically approved
Song, Y., Peskova, M., Rolando, D., Zucker, G. & Madani Larijani, H. (2023). Estimating electric power consumption of in-situ residential heat pump systems: A data-driven approach. Applied Energy, 352, Article ID 121971.
Open this publication in new window or tab >>Estimating electric power consumption of in-situ residential heat pump systems: A data-driven approach
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2023 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 352, article id 121971Article in journal (Refereed) Published
Abstract [en]

International Energy Agency predicts that the global number of installed heat pumps (HP) will increase from 180 million in 2020 to approximately 600 million by 2030, covering 20% of buildings heating needs. Electric power consumption is one of the main key performance indicators for the heat pump systems from techno-economic perspective. However a common issue prevalent in many existing heat pumps is the lack of electric power measurement. The modern installations might be equipped with electric power measurement sensors but this comes at a higher system cost for the manufacturers and end-users. The primary objective of this work is to propose a virtual measurement for estimating power consumption, thereby eliminating the need for field measurement of power for heat pumps. To achieve the objective, a data-driven approach is proposed. Firstly, the in-situ data is preprocessed through data merging, cleaning, and normalization. Then, input features are pre-selected using Spearman correlation coefficients, and further refined by addressing multicollinearity problem. Following this, Extreme Gradient Boosting (XGBoost) models and polynomial models are developed by considering different features as inputs. All models are finally validated against the in-situ data from multi-units of ground source heat pump (GSHP) and air source heat pump (ASHP) installations. The results showed that the electric power consumption of GSHP can be estimated with high accuracy (99% for R2, 10 W for MAE, and 1% for MAPE) through generic data-driven models using only four easy-to-measure input features. Taking three input features as inputs for ASHP generic model, the accuracy can be reached to 83% for R2, 125 W for MAE, and 9% for MAPE. The method presented in this paper can be applied to estimate power consumption of millions of heat pumps and consequently add a significant value as well as provide different types of services, such as cost-saving benefits for manufacturers and end-users, flexibility services for aggregators and electricity grids.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Data driven, Electric power, Heat pump, Heating, Machine learning, Regression model
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-338357 (URN)10.1016/j.apenergy.2023.121971 (DOI)001086100200001 ()2-s2.0-85172678028 (Scopus ID)
Note

QC 20231115

Available from: 2023-10-20 Created: 2023-10-20 Last updated: 2023-11-15Bibliographically approved
Yang, H., Wu, X., Zhao, S., Madani Larijani, H., Chen, J. & Chen, Y. (2022). An Agent-based Model Study on Subsidy Fraud in Technological Transition. In: Rocha, AP Steels, L VandenHerik, J (Ed.), ICAART: Proceedings Of The 14Th International Conference On Agents And Artificial Intelligence - Vol 1: . Paper presented at 14th International Conference on Agents and Artificial Intelligence (ICAART), FEB 03-05, 2022, ELECTR NETWORK (pp. 353-358). INSTICC
Open this publication in new window or tab >>An Agent-based Model Study on Subsidy Fraud in Technological Transition
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2022 (English)In: ICAART: Proceedings Of The 14Th International Conference On Agents And Artificial Intelligence - Vol 1 / [ed] Rocha, AP Steels, L VandenHerik, J, INSTICC , 2022, p. 353-358Conference paper, Published paper (Refereed)
Abstract [en]

The evolution of a society is inextricably linked to technological transition, which is based on both innovation and dissemination of technologies. To protect the vulnerable new generation of technology, government subsidies are one of the most common and effective tools. However, not all subsidy policies can lead to a healthy development of market shares. Subsidy fraud is one of the most problematic issues that can arise under an imperfect system. This paper identifies an interesting subsidy fraud like phenomenon via a validated agent-based model. After analysing the mechanism of the transition of technology in the model, we drive the condition upon which subsidy fraud could occur.

Place, publisher, year, edition, pages
INSTICC, 2022
Series
ICAART, ISSN 2184-433X
Keywords
Agent-based Model, Technological Transition, Subsidy Fraud, Subsidy Policy, Socio Technical Transitions, Complex System
National Category
Economics
Identifiers
urn:nbn:se:kth:diva-311000 (URN)10.5220/0010887300003116 (DOI)000774749000038 ()2-s2.0-85180773589 (Scopus ID)
Conference
14th International Conference on Agents and Artificial Intelligence (ICAART), FEB 03-05, 2022, ELECTR NETWORK
Note

QC 20220420

Part of proceedings ISBN 978-989-758-547-0

Available from: 2022-04-20 Created: 2022-04-20 Last updated: 2024-01-10Bibliographically approved
Sommerfeldt, N., Lemoine, I. & Madani Larijani, H. (2022). Hide and seek: The supply and demand of information for household solar photovoltaic investment. Energy Policy, 161, 112726, Article ID 112726.
Open this publication in new window or tab >>Hide and seek: The supply and demand of information for household solar photovoltaic investment
2022 (English)In: Energy Policy, ISSN 0301-4215, E-ISSN 1873-6777, Vol. 161, p. 112726-, article id 112726Article in journal (Refereed) Published
Abstract [en]

Buildings provide an ideal platform for solar photovoltaics (PV) towards sustainable development goals, and the decision to invest in PV lies predominantly with building owners. Information delivery is critical for the diffusion of innovations, and this study aims to improve the quality of information for household PV investors in Sweden. A User Journey Mapping approach is applied with a combination of semi-structured interviews and a review of online solar calculators. The results show that despite a rapid growth in the quantity of information there is still a gap between demand and supply due to the lack of clarity and trustworthiness of information. This is clearly demonstrated in the review of online calculators, which show a high variance in results. Payback time, for example, ranged from 7 to 18 years for a single test case. The information gap can be closed by creating neutral, non-commercial online information sources that focus on transparency and education where household investors can validate supplier offers and analyses. The PV industry risks eroding trust in the market, which will likely slow adoption by the early majority and hinder sustainability goals.

Place, publisher, year, edition, pages
Elsevier BV, 2022
Keywords
PV, Prosumers, Techno-economic analysis, Investment behavior, Information asymmetry
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-309302 (URN)10.1016/j.enpol.2021.112726 (DOI)000745980300004 ()2-s2.0-85119910108 (Scopus ID)
Note

QC 20220301

Available from: 2022-03-01 Created: 2022-03-01 Last updated: 2022-06-25Bibliographically approved
Beltran, F., Sommerfeldt, N., Padovani, F., Rolando, D. & Madani Larijani, H. (2022). Solar Heat Pumps and Self-Consumption Can (and should) electricity suppliers encourage thermal storage?. In: 2022 BuildSim Nordic, BSN 2022: . Paper presented at 2022 BuildSim Nordic, BSN 2022, Copenhagen, Denmark, Aug 22 2022 - Aug 23 2022. EDP Sciences, Article ID 06005.
Open this publication in new window or tab >>Solar Heat Pumps and Self-Consumption Can (and should) electricity suppliers encourage thermal storage?
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2022 (English)In: 2022 BuildSim Nordic, BSN 2022, EDP Sciences , 2022, article id 06005Conference paper, Published paper (Refereed)
Abstract [en]

Heat pumps and water tanks can be used to increase PV self-consumption in buildings without any additional equipment, but there is sometimes a lack of economic incentives to maximize it that limits economic gains. Therefore, pricing conditions need to change in order to make self-consumption strategies more interesting for prosumers. This study aims at determining what, if any, unsubsidized market conditions could lead to economically motivated self-consumption control strategies with solar heat pumps. A sensitivity analysis is used on multiple pricing models based on current market conditions for a solar PV and ground source heat pump system for a single-family house in Norrköping, Sweden. The results show that control strategies aimed at maximizing self-consumption have very little impact on net costs, regardless of pricing model or variation in price. Feed-in-bonus is the most important aspect when comparing different pricing schemes, and no other sensitivity comes close.

Place, publisher, year, edition, pages
EDP Sciences, 2022
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-333444 (URN)10.1051/e3sconf/202236206005 (DOI)2-s2.0-85146893366 (Scopus ID)
Conference
2022 BuildSim Nordic, BSN 2022, Copenhagen, Denmark, Aug 22 2022 - Aug 23 2022
Note

QC 20230802

Available from: 2023-08-02 Created: 2023-08-02 Last updated: 2023-08-02Bibliographically approved
Sommerfeldt, N., Lemoine, I. & Madani Larijani, H. (2021). A User-Centered Design Approach to Identify Behavioral Biases in the Adoption of Solar PV by Households. In: Xianli Zhu and Gabriela Prata Dias (Ed.), 6th European Conference on Behaviour Change for Energy Efficiency: . Paper presented at BEHAVE 2020‑2021 (pp. 134-137). Copenhagen
Open this publication in new window or tab >>A User-Centered Design Approach to Identify Behavioral Biases in the Adoption of Solar PV by Households
2021 (English)In: 6th European Conference on Behaviour Change for Energy Efficiency / [ed] Xianli Zhu and Gabriela Prata Dias, Copenhagen, 2021, p. 134-137Conference paper, Oral presentation with published abstract (Refereed)
Place, publisher, year, edition, pages
Copenhagen: , 2021
Keywords
diffusion, communication, design thinking, user-centered design, cognitive biases
National Category
Energy Engineering Media and Communications
Research subject
Energy Technology; Media Technology
Identifiers
urn:nbn:se:kth:diva-294258 (URN)
Conference
BEHAVE 2020‑2021
Funder
Swedish Energy Agency
Note

Part of proceedings: ISBN 9788794094016, QC 20230117

Available from: 2021-05-12 Created: 2021-05-12 Last updated: 2024-03-18Bibliographically approved
Sovacool, B. K., Cabeza, L. F., Pisello, A. L., Colladon, A. F., Madani Larijani, H., Dawoud, B. & Martiskainen, M. (2021). Decarbonizing household heating: Reviewing demographics, geography and low-carbon practices and preferences in five European countries. Renewable & sustainable energy reviews, 139, Article ID 110703.
Open this publication in new window or tab >>Decarbonizing household heating: Reviewing demographics, geography and low-carbon practices and preferences in five European countries
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2021 (English)In: Renewable & sustainable energy reviews, ISSN 1364-0321, E-ISSN 1879-0690, Vol. 139, article id 110703Article in journal (Refereed) Published
Abstract [en]

What commonalities are there in sustainable or unsustainable heating practices in five high-income, high-emitting western European countries? What preferences do a nationally representative sample of the public in these countries hold towards low-carbon options? It is imperative that climate policy researchers and practitioners grapple with the difficulty of decarbonizing heat, which remains the largest single end-use service worldwide and which accounts about half of total final energy consumption. Based on a comparative assessment of five representative national surveys in Germany (N = 2009), Italy (N = 2039), Spain (N = 2038), Sweden (N = 2023), and the United Kingdom (N = 2000), this study explores the demographics and geography of household heat decarbonisation in Europe. By analyzing our country level data as well as our combined sample of 10,109 respondents, it investigates how people conceive of the purposes of low-carbon heat, their preferences for particular forms of heat supply, and their (at times odd) practices of heat consumption and temperature settings. Grounded in its original data, the study organizes its findings inductively across the five themes of literacy (heating knowledge, awareness and control), sustainability (heating practices, dynamics and conflicts), temperature (heating satisfaction and preferences), desirability of change (low-carbon heating priorities, business models and trust), and culture (country and national variation). The study also explores intersections between these dimensions, using multivariate analysis, as well as how preferences differ according to varying types of actors as well as geography and space.

Place, publisher, year, edition, pages
PERGAMON-ELSEVIER SCIENCE LTD, 2021
Keywords
Climate policy, Low-carbon heating, Heat decarbonisation, Household heat, Space heating, Cooling, Energy policy
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-291932 (URN)10.1016/j.rser.2020.110703 (DOI)000618802200003 ()2-s2.0-85099475849 (Scopus ID)
Note

QC 20210329

Available from: 2021-03-29 Created: 2021-03-29 Last updated: 2022-06-25Bibliographically approved
Schreurs, T., Madani Larijani, H., Zottl, A., Sommerfeldt, N. & Zucker, G. (2021). Techno-economic analysis of combined heat pump and solar PV system for multi-family houses: An Austrian case study. Energy Strategy Reviews, 36, Article ID 100666.
Open this publication in new window or tab >>Techno-economic analysis of combined heat pump and solar PV system for multi-family houses: An Austrian case study
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2021 (English)In: Energy Strategy Reviews, ISSN 2211-467X, E-ISSN 2211-4688, Vol. 36, article id 100666Article in journal (Refereed) Published
Abstract [en]

With the increasing amount of building renovations in Austria, the potential increases for replacing conventional national gas heating systems with heat pumps (HP) and thereby reduce CO2 emissions particularly when combined with solar photovoltaics (PV). The Austrian subsidization scheme for HP and PV systems are different for every state, creating confusion and inconstancy for potential adopters. This study provides a parametric technoeconomic analysis of PV + HP systems to identify the critical economic parameters on profitability and make policy recommendations. A case study in Vienna is modelled using demand from the Building Model Generator and black box efficiency models for the HP and PV simulated with hourly time steps. The results show that both air-source and ground source heat pumps are currently profitable with PV under current subsidy schemes. The benefit-to-cost ratio (BCR) is highly influenced by capital costs and subsidies, however natural gas prices have the greatest influence. Increasing natural gas prices by 0.01 euro/kWh, or 17%, is enough to replace all other complicated subsidies for both HP and PV. This is equivalent to a carbon emissions price of 33 euro/ton and could result in a reduction of CO2 emissions in multi-family houses by approximately 45%-60%.

Place, publisher, year, edition, pages
Elsevier BV, 2021
Keywords
Solar energy, Heat pumps, Systems analysis, Sustainable subsidies
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-299695 (URN)10.1016/j.esr.2021.100666 (DOI)000678404500011 ()2-s2.0-85109458890 (Scopus ID)
Note

QC 20210818

Available from: 2021-08-18 Created: 2021-08-18 Last updated: 2022-06-25Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0001-7354-6643

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