http://hdl.handle.net/10197/8394 2017-10-31T10:01:37Z http://hdl.handle.net/10197/9016 Control strategies for building energy systems to unlock demand side flexibility – A review Clauß, John; Finck, Christian; Vogler-Finck, Pierre; Beagon, Paul Conventional key performance indicators (KPI) assessed in building simulation lack specific measures of how the building interacts with the grid and its energy flexibility. This paper aims to provide an overview of specific energy flexibility performance indicators, together with supporting control strategies. If applied correctly, the indicators help improving the building performance in terms of energy flexibility and can enable minimization of operational energy costs. Price-based load shifting, self-generation and self-consumption are among the most commonly used performance indicators that quantify energy flexibility and grid interaction. It has been found that the majority of performance indicators, specific to energy flexibility, are combined with rule-based control. Only a limited amount of specific energy flexibility KPIs are used in combination with optimal control or model predictive control. Both of these advanced control approaches often have a couple of economic or comfort objectives that do not take into account an energy flexibility KPI. There is evidence that recent model predictive control approaches incorporate some aspects of building energy flexibility to minimize operational cost in conjunction with time varying pricing. IPBSA Building Simulation 2017, San Francisco, 7-9 August 2017 2017-08-07T00:00:00Z http://hdl.handle.net/10197/8402 A 34-year simulation of wind generation potential for Ireland and the impact of large-scale atmospheric pressure patterns Cradden, Lucy C.; McDermott, Frank; Zubiate, Laura; Sweeney, Conor; O'Malley, Mark To study climate-related aspects of power system operation with large volumes of wind generation, data with sufficiently wide temporal and spatial scope are required. The relative youth of the wind industry means that long-term data from real systems are not available. Here, a detailed aggregated wind power generation model is developed for the Republic of Ireland using MERRA reanalysis wind speed data and verified against measured wind production data for the period 2001–2014. The model is most successful in representing aggregate power output in the middle years of this period, after the total installed capacity had reached around 500 MW. Variability on scales of greater than 6 h is captured well by the model; one additional higher resolution wind dataset was found to improve the representation of higher frequency variability. Finally, the model is used to hindcast hypothetical aggregate wind production over the 34-year period 1980–2013, based on existing installed wind capacity. A relationship is found between several of the production characteristics, including capacity factor, ramping and persistence, and two large-scale atmospheric patterns – the North Atlantic Oscillation and the East Atlantic Pattern. 2017-06-01T00:00:00Z http://hdl.handle.net/10197/8292 Lumped Parameter Building Model Calibration using Particle Swarm Optimization Andrade-Cabrera, Carlos; Turner, William J. N.; Burke, Daniel J.; Neu, Olivier; Finn, Donal This paper presents a methodology for the automated calibration of deterministic lumped parameter models in building energy simulation using optimization methods. A heterogeneous model topology is proposed to represent a residential building archetype developed in the EnergyPlus simulation environment. The archetype model has previously been used to characterize the domestic building stock in Ireland. The automated calibration problem is solved as a least squares error problem solved using a local optimization method (Sequential Quadratic Programming) and two heuristics methods (Particle Swarm Optimization and Genetic Algorithm). It is shown that Particle Swarm Optimization provides the best performance for this particular problem and provides an inherent robustness under model uncertainty. 3rd Asia conference of International Building Performance Simulation Association (ASim2016), Jeju island, Korea, 27-29 November 2016 2016-11-29T00:00:00Z http://hdl.handle.net/10197/8291 Clustering of household occupancy profiles for archetype building models Buttitta, Giuseppina; Turner, William J. N.; Finn, Donal The continued penetration of renewable energy sources in electricity generation and the de-carbonization of the domestic space heating and hot water sectors is increasing the importance of demand side management (DSM). The development of end-use energy consumption models that can be easily integrated with electricity dispatch models is crucial for the assessment of the integration of supply and demand. The energy consumption of the domestic building stock is highly correlated with occupant behaviour, however the inclusion of occupant behaviour in energy models is challenging due to its highly variable nature. Nevertheless, in order to obtain reliable models of domestic energy consumption at high time resolution, the analysis of occupant behaviour patterns is fundamental. This paper aims to develop a new methodology to generate realistic occupancy patterns that can be representative of large numbers of households. This method is based on the clustering of household occupancy profiles using the UK 2000 Time Use Survey data as a case study. The occupancy profiles that result from this method can be used as input to residential building energy end-use models, thereby giving improved overall model performance. 8th International Conference on Sustainability in Energy and Buildings (SEB-16), Turin, Italy, 11-13 September 2016 2016-01-01T00:00:00Z http://hdl.handle.net/10197/8290 An integrated Building-to-Grid model for evaluation of energy arbitrage value of Thermal Storage Anwar, Muhammad Bashar; Andrade-Cabrera, Carlos; Neu, Olivier; O'Malley, Mark; Burke, Daniel J. Thermal Electric Storage (TES) has emerged as a promising technology for enhancing the flexibility of the built environment to participate in active Demand Side Management (DSM). These devices allow the decoupling of intra-day scheduling of electric power demand from the time of thermal energy end-use. Therefore, if enabled with communication with the grid, these devices can facilitate load shifting and energy arbitrage. This study evaluates the energy arbitrage value of smart TES devices in residential buildings across Ireland. A Building-to-Grid (B2G) model has been developed which integrates the buildings thermal dynamics and end-use constraints with the power systems economic dispatch model. The thermal behavior of the houses and the TES space heater and hot water tank is modeled through linear state space models for three different mid-flat archetypes. The optimization results show the load shifting and arbitrage potential of TES and its impacts on wind curtailment considering various penetration levels of these devices. The International Conference for Students on Applied Engineering (ICSAE), Newcastle, United Kingdom, 20-21 October 2016 2016-10-21T00:00:00Z http://hdl.handle.net/10197/8285 Information gap decision theory approach to deal with wind power uncertainty in unit commitment Soroudi, Alireza; Rabiee, Abbas; Keane, Andrew The renewable energy sources (RES) integration in the electricity supply utilities can reduce the energy procurement costs as well as the environmental concerns. Wind power is the most popular form of RES which is vastly utilized worldwide. This paper proposes a robust model for unit commitment (UC) problem, minimizing the operating costs considering uncertainty of wind power generation. In order to handle the uncertainties arising from volatile nature of wind power, information gap decision theory (IGDT) is utilized, where risk averse (RA) and opportunity seeker (OS) strategies are developed. RA strategy gives a robust decision making tool for handling the severe uncertainty of wind power, whereas the OS strategy makes benefit of possible uncertainties by adjusting the decision variables in a right way. Besides, the impact of demand flexibility (or demand response) on the operation costs is also investigated. The proposed model is examined on the IEEE 118-bus test system, and its benefits over the existing stochastic programming technique is examined. The obtained results demonstrate the applicability of the proposed method to deal with the UC problem with uncertain wind power generation. It is also observed that demand flexibility has positive impacts in both RA and OS strategies. 2017-04-01T00:00:00Z http://hdl.handle.net/10197/8245 Solar PV where the sun doesn’t shine: Estimating the economic impacts of support schemes for residential PV with detailed net demand profiling La Monaca, Sarah; Ryan, L. (Lisa B.) Countries with low irradiation and solar PV adoption rates are increasingly considering policy support for solar PV, though consumer electricity demand and solar generation profiles are often mismatched. This paper presents a methodology for policy makers in countries with such conditions to examine more precisely the financial performance of residential solar PV from the consumer perspective as part of an ex-ante policy assessment. We model a range of prospective policy scenarios and compare policy mechanisms that compensate homeowners for generation, those that reduce their upfront costs, and those that assist with financing, using Ireland as a case study. The results confirm the intuitive notion that more generous financial remuneration schemes provide quicker payback, however, we observe that upfront grants do little to accelerate payback timeframes. We also show the importance of retail tariff structure in consumer payback for a solar PV system, with one-part tariffs generating shorter paybacks than two-part tariff structures, although the latter is more likely to secure revenue for electricity infrastructure investment. Drawing from this analysis, the paper proposes some options for the design of policy supports and tariff structures to deliver a sustainable residential renewable electricity system. 2016-12-01T00:00:00Z http://hdl.handle.net/10197/8200 Emulated Inertial Response from Wind Power: Ancillary Service Design and System Scheduling Considerations Daly, Pádraig; Ruttledge, Lisa; Power, Michael; Flynn, Damian Worldwide, variable-speed wind turbine and solar photovoltaic generation are displacing conventional power plant in market schedules. Committing out-of-merit conventional units to redress system synchronous inertia or primary frequency response shortfalls incurs start-up and production costs, and may also engender additional greenhouse gas emissions and wind/solar curtailment. In order to ensure that future system frequency response requirements are met in a low carbon manner, new sources of frequency stability ancillary services will need to be incentivised or mandated via grid codes. Nonsynchronous devices (batteries, flywheels, variable-speed wind turbines), with appropriate control architectures, can provide a fast frequency response following a system disturbance, i.e. a temporary injection of active power, supplied faster than existing primary frequency response deployment times. Operational considerations relevant to transmission system operators when designing a fast frequency response ancillary service are presented, particularly if sourced from wind power emulated inertial response. It is shown that careful consideration regarding the design of fast frequency response characteristics is required in high wind power systems: the system frequency response behaviour may be degraded if a holistic approach to fast frequency response design is not taken. A method to characterise the system-wide (aggregate) emulated inertial response from wind power is presented, which can be integrated as a form of fast frequency response within unit commitment and economic dispatch. Endogenous incorporation in unit commitment and economic dispatch ensures that non-synchronous fast frequency response sources do not only supplement existing fossil fuel-based spinning reserve provision, but also reduce the need to commit synchronous generators for frequency control reasons. However, given the inherent energy recovery/payback experienced by variable-speed wind turbines providing emulated inertial response when operating below rated output, it is imperative to consider the impact of such negative power trajectories on system primary frequency response requirements. 2016 CIGRE Session, Paris, France, 21-26 August 2016 2016-08-26T00:00:00Z http://hdl.handle.net/10197/8153 Local and Remote Estimations Using Fitted Polynomials on Distribution Systems Murphy, Conor; Keane, Andrew This work describes a technique to define a single parametric equation that estimates remote conditions within a distribution network, in an online setting, without dedicated telemetry. In this novel approach, a departure from conventional state estimation is explored to facilitate a fully decentralized operation. Derived based on fundamental treatment of ac power flow, the electrical behavior of a section of network is defined to a tractable constraint space using regression analysis. In this non-iterative technique, a measurement set consisting of the local voltage magnitude, active and reactive power injections at a single node are the input to pre-computed polynomials. Remote current flow, active power and reactive power flow as well as remote and local voltages and sensitivities are estimated in a direct calculation from period to period. Accurate estimations are also found in the presence of transducer errors. To assess the applicability of this technique at differing voltage levels a range of reactance to resistance ratios are considered. 2016-11-18T00:00:00Z http://hdl.handle.net/10197/8141 Investigation of demand response strategies in a mixed use building Christantoni, Despoina; Oxizidis, Simeon; Flynn, Damian; Finn, Donal 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. CLIMA 2016: 12th REHVA conference, Aalborg, Denmark, 22-25 May 2016 2016-05-25T00:00:00Z http://hdl.handle.net/10197/8125 Probabilistic Security Constrained Fuzzy Power Flow Models Gouveia, Eduardo M.; Costa, Paulo Moisés; Sagredo, Jesus; Soroudi, Alireza In restructured power systems, generation and commercialization activities became market activities, while transmission and distribution activities continue as regulated monopolies. As a result, the adequacy of transmission network should be evaluated independent of generation system. After introducing the constrained fuzzy power flow (CFPF) as a suitable tool to quantify the adequacy of transmission network to satisfy 'reasonable demands for the transmission of electricity' (as stated, for instance, at European Directive 2009/72/EC), the aim is now showing how this approach can be used in conjunction with probabilistic criteria in security analysis. In classical security analysis models of power systems are considered the composite system (generation plus transmission). The state of system components is usually modeled with probabilities and loads (and generation) are modeled by crisp numbers, probability distributions or fuzzy numbers. In the case of CFPF the component’s failure of the transmission network have been investigated. In this framework, probabilistic methods are used for failures modeling of the transmission system components and possibility models are used to deal with 'reasonable demands'. The enhanced version of the CFPF model is applied to an illustrative case. UPEC 2016 - 51st International Universities Power Engineering Conference, Coimbra, Portugal, 6-9 September 2016 2016-09-09T00:00:00Z http://hdl.handle.net/10197/8123 Distribution networks' energy losses versus hosting capacity of wind power in the presence of demand flexibility Soroudi, Alireza; Rabiee, Abbas; Keane, Andrew With the increasing share of renewable energy sources (RES) in demand supply, the distribution network operators (DNOs) are facing with new challenges. In one hand, it is desirable to increase the ability of the network in absorbing more renewable power generation units (or increasing the hosting capacity (HC)). On the other hand,  power injection to the distribution network by renewable resources may increase the active power losses (if not properly allocated) which reduces the efficiency of the network. Thus, the DNO should make a balance between these two incommensurate objective functions. The Demand Response (DR) in context of smart grids can be used by DNO to facilitate this action. This paper provides an approach in which a multi-objective and multi-period NLP optimization model is formulated where the DR is utilized as an effective tool to increase HC and decrease the energy losses simultaneously. In order to quantify the benefits of the proposed method, it is applied on a 69-bus distribution network. The numerical results substantiate that the proposed approach gives optimal locations and capacity of RES, as well as minimum energy losses by load shifting capability provided via DR programs. 2016-01-01T00:00:00Z http://hdl.handle.net/10197/8089 Technical impacts of high penetration levels of wind power on power system stability Flynn, Damian; Rather, Zakir H.; Ardal, A.; et al. With increasing penetrations of wind generation, based on power-electronic converters, power systems are transitioning away from well-understood synchronous generator-based systems, with growing implications for their stability. Issues of concern will vary with system size, wind penetration level, geographical distribution and turbine type, network topology, electricity market structure, unit commitment procedures, and other factors. However, variable-speed wind turbines, both onshore and connected offshore through DC grids, offer many control opportunities to either replace or enhance existing capabilities. Achieving a complete understanding of future stability issues, and ensuring the effectiveness of new measures and policies, is an iterative procedure involving portfolio development and flexibility assessment, generation cost simulations, load flow, and security analysis, in addition to the stability analysis itself, while being supported by field demonstrations and real-world model validation. 2016-01-01T00:00:00Z http://hdl.handle.net/10197/8079 Implementation of demand response strategies in a multi-purpose commercial building using a whole-building simulation model approach Christantoni, Despoina; Oxizidis, Simeon; Flynn, Damian; Finn, Donal This 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. 2016-11-01T00:00:00Z http://hdl.handle.net/10197/8019 Analysing the impact of large-scale decentralized demand side response on frequency stability Qazi, Hassan Wajahat; Flynn, Damian Advances in communications technology, higher penetration rates of renewable energy and an evolution towards smarter electrical grids are enabling a greater role from demand side response (DSR) in maintaining power system security and reliability. The provision of primary operating reserve (POR) from domestic loads through a decentralised, system frequency based approach is discussed. By considering a range of system configurations (generation mix, system generation and load) and control strategies, this paper endeavours to answer critical questions concerning the large-scale roll out of decentralised DSR, including the following: what are the implications of DSR resource seasonal variability on system operation and performance following the loss of a large infeed/load? Do increased load coincidence and energy payback phenomena have the potential to significantly impact system frequency recovery? How do DSR controller hardware characteristics influence the provision and effectiveness of reserve delivery? What are the repercussions of a 'fit and forget' approach to decentralised control from flexible load on frequency stability as the technology penetration increases? Can DSR be directly substituted for conventional reserve sources while recognising its post-event recovery period? Residential customer behaviour, seasonal effects and the diversity of individual device characteristics are recognised in a detailed thermodynamic flexible load model which is integrated with a detailed power system model to perform the analysis. 2016-09-01T00:00:00Z http://hdl.handle.net/10197/8012 Utilising time of use surveys to predict water demand profiles of residential building stocks: Irish case study for domestic hot water Neu, Olivier; Oxizidis, Simeon; Flynn, Damian; Finn, Donal 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. Water Efficiency Conference, Brighton, UK, 9-11 September 2014 2014-09-11T00:00:00Z http://hdl.handle.net/10197/8008 Restoration in a Self-healing Distribution Network with DER and Flexible Loads Ansari, Bananeh; Simoes, Marcelo G.; Soroudi, Alireza; Keane, Andrew This paper develops an algorithm for energy management of a distribution network considering a restorative plan for most possible devastating contingencies in the network. The distribution network is selfhealing and consists of smart meters and remotely controlled automated switches. Distributed energy resources and flexible loads provide the redundant capacity for restoration. Under normal operating conditions, the objective of the energy management system is to minimize the generation cost, while under emergency conditions, the objective is to minimize the amount of shed load, giving priority to critical loads. The energy management problem forms a non-linear programming problem. Simulation results verify the effectiveness of the proposed algorithm in energy management and restoration of a distribution network. 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC 2016), 7-10 June 2016, Florence, Italy 2016-06-10T00:00:00Z http://hdl.handle.net/10197/8007 Utilising time of use surveys to predict domestic hot water consumption and heat demand profiles of residential building stocks Neu, Olivier; Oxizidis, Simeon; Flynn, Damian; Finn, Donal 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. 2016-06-01T00:00:00Z http://hdl.handle.net/10197/7987 Synchronizing Torque Impacts on Rotor Speed in Power Systems Bakhtvar, Mostafa; Vittal, Eknath; Zheng, Kuan; Keane, Andrew Renewables are increasingly replacing power from conventional generators. Renewable power injected through power electronic converters lacks the fundamental electric torque components. Electric torque components have an important role in determining the behavior of conventional machines in the network. The influence of this factor becomes more notable in power systems with reduced inertia. Hence, questions arise on, how can synchronizing torque basically contribute to the rotor speed deviation and eventually the system frequency and if there is a potential for using the steady state synchronizing torque coefficient (STC) to achieve acceptable frequency operating points. This paper calculates the steady state STC matrix by using the multi-machine Heffron-Philips model in conjunction with the network admitance matrix. Accordingly, it investigates the impact of the generator location and reactive power output on the STC matrix. It demonstrates how this impact manifests in the generator rotor speed deviation. Eventually, the significance of the STC from the system frequency perspective is assessed. 2016-01-01T00:00:00Z http://hdl.handle.net/10197/7986 Allocation of Wind Capacity Subject to Long Term Voltage Stability Constraints Bakhtvar, Mostafa; Keane, Andrew Increasing wind capacity integration results in displacement of active power from conventional generators and a reduction in reactive power sources available. As such, voltage stability may become a concern in certain periods for power system operation particularly in weaker areas of the network. Thus, it is of importance to consider the AC constraints for optimal wind generation planning (long term) in order to decrease the possibility of a wind capacity allocation that requires costly remedies from the power system operation perspective (short term). In this work, a procedure is proposed for wind capacity allocation with the aim of benefiting from the potential of an optimal wind capacity allocation for enhancing the voltage stability margin. The procedure is based on a multi operating conditions voltage stability constrained optimal power flow. The wind capacity target is set and the loadability margin is tracked. The results will show the applicability of the proposed procedure and will emphasize the effects of the pattern of wind capacity allocation on the loadability margin. This will result in a wind capacity allocation that enhances the minimum loadability margin among the possible future operating conditions considered for planning. The procedure uses the Maximin concept for this purpose. 2016-05-01T00:00:00Z http://hdl.handle.net/10197/7914 Distribution Network Operation Under Uncertainty Using Information Gap Decision Theory O'Connel, Alison; Soroudi, Alireza; Keane, Andrew The presence of uncertain parameters in electrical power systems presents an ongoing problem for system operators and other stakeholders when it comes to making decisions.Determining the most appropriate dispatch schedule or system configuration relies heavily on forecasts for a number of parameters such as demand, generator availability and more recently weather. These uncertain parameters present an even more compelling problem at the distribution level, as these networks are inherently unbalanced, and need to be represented as such for certain tasks. The work in this paper presents an information gap decision theory based three-phase optimal power flow. Assuming that the demand is uncertain, the aim is to provide optimal and robust tap setting and switch decisions over a 24-hour period,while ensuring that the network is operated safely, and that losses are kept within an acceptable range. The formulation is tested on a section of realistic low voltage distribution network with switches and tap changers present. 2016-08-17T00:00:00Z http://hdl.handle.net/10197/7880 Building Performance Optimisation: A Hybrid Architecture for the Integration of Contextual Information and Time Series Data Hu, Shushan; Corry, Edward; Turner, William J. N.; O'Donnell, James T. Buildings tend to not operate as intended, and a pronounced gap often exists between measured and predicted environmental and energy performance. Although the causes of this ‘performance gap’ are multi-faceted, issues surrounding data integration are key contributory factors. The distributed nature of the Architecture, Engineering and Construction (AEC) industry presents many challenges to the effective capture, integration and assessment of building performance data. Not all building data can be described semantically, nor is it feasible to create adapters between many different software tools. Similarly, not all building contextual data can easily be captured in a single product-centric model. This paper presents a new solution to the problem based upon a hybrid architecture that links data which is retained in its original format. The architecture links existing and efficient relational databases storing time-series data and semantically-described building contextual data. The main contribution of this work is an original RDF syntax structure and ontology to represent existing database schema information, and a new mechanism that automatically prepares data streams for processing by rule-based performance definitions. Two test cases evaluate the concept by 1) applying the hybrid architecture to building performance data from an actual building, and 2) evaluating the efficiency of the architecture against a purely RDF-based solution that also stores all of the time-series data in RDF for a virtual building. The hybrid architecture also avoids the duplication of time-series data and overcomes some of the differences found in database schemas and database platforms. 2016-10-01T00:00:00Z http://hdl.handle.net/10197/7877 Next generation building performance metrics to enable energy systems integration Beagon, Paul; Warren, Joe; Finn, Donal; O'Donnell, James T. Traditional building performance metrics consider a building as a standalone and static utility consumer. Voluntary green building certifications of districts generally aggregate the metrics of standalone and consuming buildings. There is a lack of performance metrics concerning the integration of critical services to a building and the utility networks supplying these critical services of electricity, natural gas and water. In order to achieve integration of energy systems, including storage based demand side management and rain water harvesting, a methodology is modelled for a typical office. The methodology requires building parameters to be combined and manipulated in order to create the proposed performance metrics. The building model is simulated for three periods of interest: a whole year, a winter design day, a summer design day. The proposed metrics enable operational management during peak and standard loads, as well as longer term analysis of the building performance. Operational management includes the role of storage and the responsiveness of a building during demand ramping or shedding. Over the longer term, the metrics indicate efficiency trends and guide design and investment decisions. It is found that electrical storage combined with demand side management reduces energy costs with no service disruptions. Rain water harvesting is also found to significantly reduce financial and energy costs, and given its current dearth of deployment, has high future potential. 12th REHVA World Congress, Aalborg, Denmark, 22-25 May 2016 2016-05-25T00:00:00Z http://hdl.handle.net/10197/7576 Novel Quality Metrics for Power System Diagrams Cuffe, Paul; Keane, Andrew Power network diagrams are typically neither enlightening nor attractive to look at. Encouragingly, though, the visualization of generic complex networks has been an active area of research for the past two decades, and there now exist a number of widely-deployed algorithms that show a network's structure in a revealing and aesthetic way. Additionally, recent work by the present authors has proposed techniques for diagramming power systems that explicitly use meaningful electrical distance metrics. Which is the most effective approach to diagramming? To begin to answer this question, this paper proposes new quality metrics for power system diagrams which seek to quantify how legibly a network layout reveals how power flows through it. IEEE International Energy Conference EnergyCon 2016, Leuven, Belgium, 4-8 April 2016 2016-04-08T00:00:00Z http://hdl.handle.net/10197/7538 Electrical and Thermal Characteristics of Household Appliances: Voltage Dependency, Harmonics and Thermal RC Parameters McKenna, Killian; Keane, Andrew Detailed bottom-up load modelling of the residential sector has become increasingly important to examine the network impacts of both changing load composition due to the introduction of sustainable technologies, and changing load behaviour with increased levels of demand response. An important aspect of these models is the electrical and thermal behaviour of household loads. This paper examines the fundamental electrical and thermal characteristics of common household appliances. Methods to obtain the voltage de endency and equivalent resistive-capacitive (RC) circuit parameters for mode ling thermostatically controlled appliances (TCAs) are presented. The paper also presents the results of laboratory experimental determination of voltage dep endency coefficients, subjecting common appliances to a range of voltages within +/- 10% of the standard supply voltage. The thermal behaviour of TCAs are examined by use of thermocouples and plug-load monitoring devices. Appliances are grouped into into five distinct categories; lighting, motor, power electronic, resistive and wet appliance loads, and both their characteristics and operational behaviour is presented. 2016-02-01T00:00:00Z