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  • 1.
    Kristinsdóttir, Anna Rúna
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology.
    Stoll, Pia
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology.
    Nilsson, Anders
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology.
    Brandt, Nils
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology.
    Description of climate impact calculation methods of the CO2e signal for the Active house project2013Report (Other academic)
  • 2. Lennvall, T.
    et al.
    Rizvanovic, L.
    Stoll, Pia
    KTH.
    Scheduling of electrical loads in home automation systems2015In: IEEE International Conference on Automation Science and Engineering, IEEE Computer Society, 2015, p. 1307-1312Conference paper (Refereed)
    Abstract [en]

    In this paper we propose a novel approach to schedule electric loads with the aim of reducing households' energy cost or CO2 emission with acceptable change in comfort. The approach involves both shifting households' electrical loads to times when the electricity prices or CO2 intensities are low, and reducing households' electrical loads at times when electricity prices or CO2 intensities are high. This approach assumes availability of day ahead hourly data of CO2 emissions and/or electricity cost from the external service provider. We categorize energy loads in two groups; constant and one-shot loads. Constant loads ensure environmental comfort for a consumer (e.g., heating, ventilation), while one-shot loads have a more dynamic nature (e.g., smart appliances, EV charging). Our approach is a best effort approach suitable for resource constrained embedded systems.

  • 3.
    Nilsson, Anders
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Resources, Energy and Infrastructure.
    Stoll, Pia
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering.
    Brandt, Nils
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering.
    Assessing the impact of real-time price visualization on residential electricity consumption, costs, and carbon emissions2015In: Resources, Conservation and Recycling, ISSN 0921-3449, E-ISSN 1879-0658, Vol. 124, p. 152-161Article in journal (Refereed)
    Abstract [en]

    The development of smart grid projects, with demand side management as an integral part, has led to an increased interest of households’ willingness to react to different types of demand response programs. This paper presents a pilot study assessing the impact of real-time price visualization on residential electricity consumption, and its effects on electricity costs and carbon (CO2eq) emissions. We analyze changes in electricity consumption based on a test group and a reference group of 12 households, respectively. To allow for analysis on load shift impact on CO2eq emissions, hourly dynamic CO2eq intensity of the Swedish electricity grid mix is calculated, using electricity generation data, trading data, and fuel-type specific emission factors. The results suggest that, on average, the test households shifted roughly 5% of their total daily electricity consumption from peak hours (of high electricity price) to off-peak hours (of low electricity price) as an effect of real-time price visualization. However, due to the mechanisms of the Swedish electricity market, with a negative relation between spot price and CO2eq intensity, the load shift led to a split effect; electricity costs modestly decreased while CO2eq emissions increased. In addition, any indication of the contribution of real-time spot price visualization to a reduction in overall household electricity consumption level could not be found, as the relative difference in consumption level between the test households and the reference households remained constant during both the baseline period and the test period. 

  • 4.
    Stoll, Pia
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology.
    Residential Demand Response in the Context of European Union Energy Policy2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    In order to achieve energy security, reduce global warming and promote the vision of a common electricity market, the European Union (EU) is transforming the EU electricity grid from a large set of independent hierarchical national grids into one meshed EU-wide grid. For the first time in the history of the electric power industry, residential consumers are being integrated into the grid as active consumers and micro-generators of electricity. In the near future, residential buildings in the EU will have to use much less energy and the right source of energy. If residential consumers want to maintain the same level of energy service, buildings will have to use and produce energy differently. Decentralised energy production from renewable energy sources beside or within residential buildingsis required. Distribution grids will receive more locally produced energy and be more autonomous. Suppliers and distribution system operators will have to change business models from quantity-based to service-based. As residential consumers become more active in the EU, residential system developers need to understand what and how system requirements can support EU energy policy. This thesis therefore interprets EU energy policy concerns in terms of factors influencing the residential demand response system design. To test the viability of the influencing factors, system design was constructed and prototyped. One important influencing factor,the “greenness” of electricity information, was concretised as a dynamic CO2 signal and integrated into the system design as a residential demand response signal. The dynamic CO2 signal was not always correlated with the dynamic price of electricity, but there were strong indications that the CO2 intensity signal can and should be used as a supplement to the price signal in the residential demand response system to increase motivation for energy savings. It was found that a CO2 intensity-driven Time-of-Use tariff can be developed, based on forecasts of the hourly wholesale market price and the CO2 intensity, and that this tariff is beneficial for both supplier and household. The thesis thus demonstrates that it is possible to extract system design-influencing factors from EU energy policy and use these for the design and implementation of a residential demand response system.

  • 5.
    Stoll, Pia
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology.
    Anders, Wall
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology.
    Norström, Christer
    Guiding Architectural Decisions with the Influencing Factors Method2008Conference paper (Refereed)
    Abstract [en]

    The Influencing Factors (IF) method guides the architect through stakeholders’ concerns to architectural decisions in line with current business goals. The result is a set of requirements on software quality attributes and business goals and highlighted trade-offs among software quality attributes and among business goals. The IF method is suitable for sustainable software systems since it allows new concerns, resulting from changes in business goals, stakeholder concerns, technical environment and organization, to be added to existing concerns.

  • 6.
    Stoll, Pia
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology. KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Brandt, Nils
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology.
    Nordström, Lars
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Including dynamic CO2 intensity with demand response2014In: Energy Policy, ISSN 0301-4215, E-ISSN 1873-6777, Vol. 65, p. 490-500Article in journal (Refereed)
    Abstract [en]

    Hourly demand response tariffs with the intention of reducing or shifting loads during peak demand hours are being intensively discussed among policy-makers, researchers and executives of future electricity systems. Demand response rates have still low customer acceptance, apparently because the consumption habits requires stronger incentive to change than any proposed financial incentive. An hourly CO2 intensity signal could give customers an extra environmental motivation to shift or reduce loads during peak hours, as it would enable co-optimisation of electricity consumption costs and carbon emissions reductions. In this study, we calculated the hourly dynamic CO2 signal and applied the calculation to hourly electricity market data in Great Britain, Ontario and Sweden. This provided a novel understanding of the relationships between hourly electricity generation mix composition, electricity price and electricity mix CO2 intensity. Load shifts from high-price hours resulted in carbon emission reductions for electricity generation mixes where price and CO2 intensity were positively correlated. The reduction can be further improved if the shift is optimised using both price and CO2 intensity. The analysis also indicated that an hourly CO2 intensity signal can help avoid carbon emissions increases for mixes with a negative correlation between electricity price and CO2 intensity.

  • 7.
    Stoll, Pia
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology. ABB Corporate Research.
    Rizvanovic, Larisa
    Rossebo, Judith
    Nordström, Lars
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Brandt, Nils
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Designing Household Demand Response System Supporting the EU Energy PolicyManuscript (preprint) (Other academic)
    Abstract [en]

    For reasons of achieving energy security, reducing global warming and promoting the vision of a common electricity market, the European Union (EU) is transforming the EU electricity grid from a large set of independent hierarchical national grids into one meshed EU-wide grid. For the first time in the electric power industry’s history,residential consumers are being integrated into the grid as active consumers as well as micro-generators of electricity. The needs and envisioned actions of end-consumers form part of a set of EU directives targeting increased energy effciency and improved energy performance in buildings, e.g. through technical advances such as residentialdemand response programmes. To fulfil the EU energy policy, technical systems mustbe revised and extended. However, this poses a challenge for developers, since the EUdirectives are not formulated as system requirements. Another issue is whether EU en-ergy policy stipulates system capabilities that contradict development project-specific capabilities. This paper attempts to elicit and implement household demand response system capabilities from EU directives and from project-specific capabilities for the case of the Stockholm Royal Seaport urban smart grid project. We also examined whether EU energy policy capabilities are sufficiently generic to include the project-specific Stockholm Royal Seaport capabilities or whether there are major omissions and what they comprise. We found that the capabilities we extracted from the EU energy policy directives are generally applicable (with the addition of a social acceptance capability) and can be used as the foundation for development work on project-specific household demand response systems.

  • 8.
    Stoll, Pia
    et al.
    KTH, School of Architecture and the Built Environment (ABE), Sustainable development, Environmental science and Engineering, Industrial Ecology. ABB Corporate Research.
    Rossebo, Judith
    Nordström, Lars
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Brandt, Nils
    KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
    Analysing Policy Texts for System CapabilitiesManuscript (preprint) (Other (popular science, discussion, etc.))
    Abstract [en]

    This paper presents a resource-efficient method for identifying system capabilities from policy content using a coding agenda. The method incorporates the influencing factors method for eliciting only those system capabilities with a positive impact on developers’ business goals. The applicability of the method is illustrated using the case of development of a household demand response system for Stockholm RoyalSeaport. In the case study, texts extracted from EU energy policy directives were used to identify household demand response system capabilities. The results showed that the system capabilities extracted were sufficiently generic to host project-specific system capabilities. This would eliminate much of the effort in tailoring system development to every individual project. For the specific case study, it also ensured that demand response system development was aligned with EU energy policy.

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