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Oxizidis, Simeon
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Oxizidis, Simeon
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Oxizidis, Simeon
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Now showing 1 - 9 of 9
- PublicationUtilising time of use surveys to predict water demand profiles of residential building stocks: Irish case study for domestic hot water(The WATEF Network, University of Brighton, 2014-09-11)
; ; ; The prediction of water consumption patterns is a challenge, especially when water metering is not available at scale. The paper focuses on the prediction of analytical domestic hot water (DHW) demand profiles for detailed building archetype models, using an occupant focused approach based on time-of-use survey (TUS) data. Five dwelling types are considered over different construction periods, representative of the majority of the Irish residential stock, which is used here as a case study. They are modelled at room level using EnergyPlus and converted into archetype models. A bottom-up approach is utilised to develop the required operational data at high space and time resolution. That methodology applies Markov Chain Monte Carlo techniques to TUS activity data to develop activity-specific profiles for occupancy and domestic equipment electricity use. It is extended to DHW demand profiles by combining the probability distributions for particular TUS activities with average daily DHW consumptions, depending on the household size, day type and season. The archetype models are found to be 90% accurate with the Irish standard dwelling energy assessment procedure in estimating the annual energy requirements for DHW heating. Moreover, they capture variations in DHW consumption, heat demand and energy usage for DHW heating, on a national scale and a fifteen-minute basis.272 - PublicationUtilising time of use surveys to predict domestic hot water consumption and heat demand profiles of residential building stocks(SCIENCEDOMAIN International, 2016-06)
; ; ; Aims: The prediction of water consumption patterns is a challenge, especially when water metering is not available at scale. The use of time-of-use survey (TUS) data offers an alternative to metering in order to track the general patterns of water consumption across large and representative groups of end-users. The paper focuses on the prediction of analytical domestic hot water (DHW) demand profiles for detailed building archetype models, using an occupant focused approach based on TUS data. The paper illustrates and discusses the resulting capability of dwelling archetypes to capture variations in heat demand and energy usage for water heating on a national scale and at high time resolution. Methodology: Five dwelling types are considered over different construction periods, representative of the majority of the Irish residential stock, which is used here as a case study. They are modelled at room level using EnergyPlus and converted into archetype models. A bottom-up approach is utilised to develop the required operational data at high space and time resolution. That methodology applies Markov Chain Monte Carlo techniques to TUS activity data to develop activity-specific profiles for occupancy and domestic equipment electricity use. It is extended to DHW demand profiles by combining the probability distributions for particular TUS activities with average daily DHW consumptions, depending on the household size, day type and season. Results: The archetype models capture variations in DHW consumption, heat demand and energy usage for DHW heating, on a national scale and a fifteen-minute basis. Moreover, they are found to be 90% accurate with the Irish standard dwelling energy assessment procedure in estimating the annual energy requirements for DHW heating. Conclusion: This study demonstrates the potential for utilising time of use surveys to predict domestic water demand profiles on a national scale and at high time resolution.1014 - PublicationHigh Resolution Space - Time Data: Methodology for Residential Building Simulation Modelling(International Building Performance Simulation Association (IBPSA), 2013-08-28)
; ; ; ; A bottom-up approach is developed for the specification of operational data with a high spacetime resolution, to be used as inputs in multi-zone residential building models. These archetype models will be used to analyse demand modulation of total domestic electricity consumption, thus requiring a detailed knowledge of domestic loads. The approach is based on national Time-Use Survey (TUS) resident activity data. To illustrate the approach, the EnergyPlus simulation platform is used to model a multi-zone case study building. Occupancy profiles, lighting load and disaggregated electrical appliance load profiles, as well as their associated heat gains, are generated and spatially mapped within the building. A good match is seen between synthesised and measured profiles. A greater sharing of electrical appliances, as the household size increases, is also seen. Fifteen-minute resolution of the model outputs is found to be sensible in the context of the current project, due to aggregation.345 - PublicationInvestigation of demand response strategies in a mixed use building(Department of Civil Engineering, Aalborg University, 2016-05-25)
; ; ; This paper investigates demand response measures, using an EnergyPlus simulation model, developed specifically for demand response analysis, in a mixed-used commercial building. The effectiveness of various building pre-conditioning strategies, which were considered for different durations, immediacy and activation time were assessed using the simulation model. Assessment was carried out for a representative summer day and the contribution of the building capacitance as a mechanism for shifting the building electric power demand was evaluated, recording a maximum load reduction of 6.6% of the baseload.247 - PublicationCalibration of a commercial building energy simulation model for demand response analysis(International Building Performance Simulation Association (IBPSA), 2015-12-09)
; ; ; This paper describes the calibration process of an EnergyPlus simulation model, for a multi-purpose commercial building, which has been developed specifically for demand response analysis. Power, gas and air temperature data are collected in fifteen minute intervals as part of the calibration process. Real occupancy data are implemented as well. The results indicate a mean bias error of -1.6% for the annual electricity consumption. Calibration under the scope of demand response at zone and equipment level is also described.355 - PublicationDeveloping building archetypes for electrical load shifting assessment: Analysis of Irish residential stock(CIBSE, 2014-04-04)
; ; ; ; Appropriate use of demand side management (DSM) strategies in residential buildings, when placed in a smart grid environment, can help reduce power supplydemand mismatches by shifting electrical loads, thus leading to better integration of renewable energy sources, particularly wind and solar generation. In the current paper, detailed building energy simulation models of residential stock are developed, using an occupant focused approach. Five archetypes are considered over three construction periods, representative of about 82% of the Irish building stock. The archetype models were found to be accurate to within 10% of the Irish standards, as exemplified using the Dwelling Energy Assessment Procedure (DEAP), for space and water heating energy requirements. The proposed approach was found to be more accurate than DEAP to estimate the electricity consumption. By integrating high resolution models for occupancy and electrical equipment use, it can generate more accurate models of the housing stock and expands previous investigations to include occupant behaviour, electrical load shifting and thermal comfort issues.597 - PublicationThe effect of time-of-use tariffs on the demand response flexibility of an all-electric smart-grid-ready dwellingThe paper is concerned with the development and evaluation of control algorithms for the implementation of demand response strategies in a smart-grid enabled all-electric residential building. The dwelling is equipped with a 12 kW heat pump, a 0.8 m3 water storage tank, a 6 kW photovoltaic (PV) array, solar thermal collectors for domestic hot water heating and an electric vehicle. The building, located in Ireland, is fully instrumented. An EnergyPlus building simulation model of the dwelling was developed and calibrated using monitored data from the building. The developed model is used to assess the effectiveness of demand response strategies using different time-of-use electricity tariffs in conjunction with zone thermal control. A reduction in generation cost (−22.5%), electricity end-use expenditure (−4.9%) and carbon emission (−7.6%), were estimated when DR measures were implemented and compared with a baseline system. Furthermore, when the zone control features were enabled, the efficiency of the control improved significantly giving, an overall annual economic saving of 16.5% for the residential energy cost. The analysis also identified an annual reduction of consumer electricity consumption of up to 15.9%, lower carbon emissions of 27% and facilitated greater utilisation of electricity generated by grid-scale renewable resources, resulting in a reduction of generation costs for the utility of up to 45.3%.
180Scopus© Citations 81 - PublicationImplementation of demand response strategies in a multi-purpose commercial building using a whole-building simulation model approachThis paper exploits a whole-building energy simulation approach to develop and evaluate demand response strategies for commercial buildings. The research is motivated by the increasing penetration of renewable energy sources such as wind and solar, which owing to their stochastic nature, means that enhanced integration of demand response measures in buildings is becoming more challenging and complex. Using EnergyPlus, a simulation model of a multi-purpose commercial building was developed and calibrated. Demand response strategies are evaluated for a number of building zones, which utilise different heating, cooling and ventilation equipment. The results show that for events of varying demand response durations, different strategies should be selected for each zone based on their thermal and usage profiles. Overall, a maximum reduction of 14.7% in electrical power demand was recorded when targeting a centralised chiller load, with smaller reductions for other decentralised building loads.
728Scopus© Citations 41 - PublicationNatural ventilation in residential building archetypes: a stochastic approach based on occupant behaviour and thermal comfort(International Building Performance Simulation Association (IBPSA), 2014-05-10)
; ; ; ; As houses become more energy efficient due to highly thermal resistant fabrics, the impact of natural ventilation on indoor comfort and on transient heating and cooling loads increases. These two constraints must be integrated within building performance simulation models when assessing the potential for electrical load shifting strategies in residential buildings placed in a smart grid environment. A natural ventilation model is developed and implemented for five residential building archetypes. A bottom-up methodology based on occupant behaviour, through the use of time-of-use data, is implemented at room level within EnergyPlus. A stochastic approach determines whether to open or close windows, depending on the occupancy state, the activity type and level, and the thermal comfort experienced. The algorithms proposed consider the main drivers governing window operation within a residential context. Focus is placed on the modelling challenges, and the impacts of the model are assessed using energy performance and thermal comfort.254