Real-time Optimization of Energy Flows in a Semi-virtual Nearly Zero-energy Building Emulator

Simo Kilpeläinen, BM Delgado , Reino Ruusu, Ala Hasan

    Research output: Contribution to conferenceConference articleScientificpeer-review

    Abstract

    This paper describes the implementation of an energy management system (EMS) onto a semi-virtual nearly zero-energy building emulator.
    The emulator platform consists of a physical part for energy production (PV panels, micro-wind turbine), storage (electrical battery and hot water tank) and conversion (ground-source heat pump and electric heater) coupled to a virtual single-family house model run in the computer simulation program TRNSYS. Communication between the parts is handled with a LabVIEW-based program.
    The EMS is a Model-predictive Controller (MPC) Matlab-based program which optimizes energy flows in the system based on a successive linear programming (SLP) approach. The EMS is connected to real-time energy pricing and weather forecasts on the Internet and can instruct the emulator how to best utilize locally produced and imported energy.
    In this paper, the performance of the EMS is evaluated by analyzing data from a one-week test period. We chose a representative week from April 2015 with varied energy pricing and weather conditions for this purpose. The actual test was done in June 2018, and hence we replaced the real energy production components with virtual ones to emulate the selected week’s energy generation from sun and wind. For the same reason, we replaced real-time energy pricing data with recorded ones and generated a weather forecast based on actual weather data from the representative week.
    The measurement results indicate that the EMS improved the overall electricity use of the emulator building. It anticipated upcoming price increases by charging the battery and optimized self-consumption by covering the electricity demand with local production during more expensive morning hours and charging the battery with cheap imports during afternoons. The EMS also utilized the hot water tank to improve energy flexibility by allowing the bottom part to cool down during periods of low local generation and high space heating demand, and by heating up the tank during sunny and warm days.
    Original languageEnglish
    Publication statusPublished - 2019
    MoE publication typeNot Eligible
    Event9th International Conference on Sustainable Development in the Building and Environment, SuDBE2019 - University of Reading and University of Cambridge, United Kingdom
    Duration: 22 Jul 201828 Jul 2019
    Conference number: 9
    http://www.sudbeconference.com/

    Conference

    Conference9th International Conference on Sustainable Development in the Building and Environment, SuDBE2019
    Abbreviated titleSuDBE
    CountryUnited Kingdom
    Period22/07/1828/07/19
    Internet address

    Fingerprint

    Energy management systems
    Water tanks
    Electricity
    Geothermal heat pumps
    Costs
    Space heating
    Sun
    Wind turbines
    Linear programming
    Internet
    Heating
    Controllers
    Communication
    Computer simulation

    Keywords

    • nearly zero-energy buildings, energy management, renewables, building emulation

    Cite this

    Kilpeläinen, S., Delgado , BM., Ruusu, R., & Hasan, A. (2019). Real-time Optimization of Energy Flows in a Semi-virtual Nearly Zero-energy Building Emulator. Paper presented at 9th International Conference on Sustainable Development in the Building and Environment, SuDBE2019 , United Kingdom.
    Kilpeläinen, Simo ; Delgado , BM ; Ruusu, Reino ; Hasan, Ala. / Real-time Optimization of Energy Flows in a Semi-virtual Nearly Zero-energy Building Emulator. Paper presented at 9th International Conference on Sustainable Development in the Building and Environment, SuDBE2019 , United Kingdom.
    @conference{a8539d7bc27d460191415af9ce82722e,
    title = "Real-time Optimization of Energy Flows in a Semi-virtual Nearly Zero-energy Building Emulator",
    abstract = "This paper describes the implementation of an energy management system (EMS) onto a semi-virtual nearly zero-energy building emulator. The emulator platform consists of a physical part for energy production (PV panels, micro-wind turbine), storage (electrical battery and hot water tank) and conversion (ground-source heat pump and electric heater) coupled to a virtual single-family house model run in the computer simulation program TRNSYS. Communication between the parts is handled with a LabVIEW-based program. The EMS is a Model-predictive Controller (MPC) Matlab-based program which optimizes energy flows in the system based on a successive linear programming (SLP) approach. The EMS is connected to real-time energy pricing and weather forecasts on the Internet and can instruct the emulator how to best utilize locally produced and imported energy.In this paper, the performance of the EMS is evaluated by analyzing data from a one-week test period. We chose a representative week from April 2015 with varied energy pricing and weather conditions for this purpose. The actual test was done in June 2018, and hence we replaced the real energy production components with virtual ones to emulate the selected week’s energy generation from sun and wind. For the same reason, we replaced real-time energy pricing data with recorded ones and generated a weather forecast based on actual weather data from the representative week.The measurement results indicate that the EMS improved the overall electricity use of the emulator building. It anticipated upcoming price increases by charging the battery and optimized self-consumption by covering the electricity demand with local production during more expensive morning hours and charging the battery with cheap imports during afternoons. The EMS also utilized the hot water tank to improve energy flexibility by allowing the bottom part to cool down during periods of low local generation and high space heating demand, and by heating up the tank during sunny and warm days.",
    keywords = "nearly zero-energy buildings, energy management, renewables, building emulation",
    author = "Simo Kilpel{\"a}inen and BM Delgado and Reino Ruusu and Ala Hasan",
    note = "All accepted papers will be published in the conference proceedings USB disk; 9th International Conference on Sustainable Development in the Building and Environment, SuDBE2019 , SuDBE ; Conference date: 22-07-2018 Through 28-07-2019",
    year = "2019",
    language = "English",
    url = "http://www.sudbeconference.com/",

    }

    Kilpeläinen, S, Delgado , BM, Ruusu, R & Hasan, A 2019, 'Real-time Optimization of Energy Flows in a Semi-virtual Nearly Zero-energy Building Emulator', Paper presented at 9th International Conference on Sustainable Development in the Building and Environment, SuDBE2019 , United Kingdom, 22/07/18 - 28/07/19.

    Real-time Optimization of Energy Flows in a Semi-virtual Nearly Zero-energy Building Emulator. / Kilpeläinen, Simo; Delgado , BM; Ruusu, Reino; Hasan, Ala.

    2019. Paper presented at 9th International Conference on Sustainable Development in the Building and Environment, SuDBE2019 , United Kingdom.

    Research output: Contribution to conferenceConference articleScientificpeer-review

    TY - CONF

    T1 - Real-time Optimization of Energy Flows in a Semi-virtual Nearly Zero-energy Building Emulator

    AU - Kilpeläinen, Simo

    AU - Delgado , BM

    AU - Ruusu, Reino

    AU - Hasan, Ala

    N1 - All accepted papers will be published in the conference proceedings USB disk

    PY - 2019

    Y1 - 2019

    N2 - This paper describes the implementation of an energy management system (EMS) onto a semi-virtual nearly zero-energy building emulator. The emulator platform consists of a physical part for energy production (PV panels, micro-wind turbine), storage (electrical battery and hot water tank) and conversion (ground-source heat pump and electric heater) coupled to a virtual single-family house model run in the computer simulation program TRNSYS. Communication between the parts is handled with a LabVIEW-based program. The EMS is a Model-predictive Controller (MPC) Matlab-based program which optimizes energy flows in the system based on a successive linear programming (SLP) approach. The EMS is connected to real-time energy pricing and weather forecasts on the Internet and can instruct the emulator how to best utilize locally produced and imported energy.In this paper, the performance of the EMS is evaluated by analyzing data from a one-week test period. We chose a representative week from April 2015 with varied energy pricing and weather conditions for this purpose. The actual test was done in June 2018, and hence we replaced the real energy production components with virtual ones to emulate the selected week’s energy generation from sun and wind. For the same reason, we replaced real-time energy pricing data with recorded ones and generated a weather forecast based on actual weather data from the representative week.The measurement results indicate that the EMS improved the overall electricity use of the emulator building. It anticipated upcoming price increases by charging the battery and optimized self-consumption by covering the electricity demand with local production during more expensive morning hours and charging the battery with cheap imports during afternoons. The EMS also utilized the hot water tank to improve energy flexibility by allowing the bottom part to cool down during periods of low local generation and high space heating demand, and by heating up the tank during sunny and warm days.

    AB - This paper describes the implementation of an energy management system (EMS) onto a semi-virtual nearly zero-energy building emulator. The emulator platform consists of a physical part for energy production (PV panels, micro-wind turbine), storage (electrical battery and hot water tank) and conversion (ground-source heat pump and electric heater) coupled to a virtual single-family house model run in the computer simulation program TRNSYS. Communication between the parts is handled with a LabVIEW-based program. The EMS is a Model-predictive Controller (MPC) Matlab-based program which optimizes energy flows in the system based on a successive linear programming (SLP) approach. The EMS is connected to real-time energy pricing and weather forecasts on the Internet and can instruct the emulator how to best utilize locally produced and imported energy.In this paper, the performance of the EMS is evaluated by analyzing data from a one-week test period. We chose a representative week from April 2015 with varied energy pricing and weather conditions for this purpose. The actual test was done in June 2018, and hence we replaced the real energy production components with virtual ones to emulate the selected week’s energy generation from sun and wind. For the same reason, we replaced real-time energy pricing data with recorded ones and generated a weather forecast based on actual weather data from the representative week.The measurement results indicate that the EMS improved the overall electricity use of the emulator building. It anticipated upcoming price increases by charging the battery and optimized self-consumption by covering the electricity demand with local production during more expensive morning hours and charging the battery with cheap imports during afternoons. The EMS also utilized the hot water tank to improve energy flexibility by allowing the bottom part to cool down during periods of low local generation and high space heating demand, and by heating up the tank during sunny and warm days.

    KW - nearly zero-energy buildings, energy management, renewables, building emulation

    M3 - Conference article

    ER -

    Kilpeläinen S, Delgado BM, Ruusu R, Hasan A. Real-time Optimization of Energy Flows in a Semi-virtual Nearly Zero-energy Building Emulator. 2019. Paper presented at 9th International Conference on Sustainable Development in the Building and Environment, SuDBE2019 , United Kingdom.