Simulation of energy systems and associated thermodynamic domains is very powerful in delivering precise information at high resolution. Modelling software requires detailed information about the energy system. The specialised user usually has questions about specific aspects of the energy system and may not be interested in the complete set of outputs available from simulation results. Similarly the specialised user may only be concerned about a subset of the inputs provided to the software. This suggests an opportunity to develop an input / output scheme tailored for the specialised user. The power of simulation can be accessed through the use of simplified interfaces. Although these restrict flexibility in terms of model input / output data the specialised user is only interested in a subset of the capability of the underlying simulation tool. Robust results rely on a consistent underlying simulation context, this restricted interface ensures that only the parameters of interest to the users are modifiable and that other simulation parameters remain fixed ensuring a consistent and repeatable output. One such example of limited user interaction for both output and input is the ADEPT interface to whole building and plant dynamic modelling and simulation suite ESP-r (ESRU 2002). The interface was developed in the context of the UK domestic heating market. This paper describes the development of the ADEPT tool and associated spreadsheet templates in order to provide a readily usable platform for the study of domestic heating systems and controls for plant and control components manufacturers, regulatory authorities and research organisations.

Assessments based on CFD snapshots of stable conditions within strongly transient domains do not address many aspects of performance associated with occupant interventions, control actions or changing climate. Such domains (e.g. double skin façades) are characterised by transient flow patterns due to changing weather patterns, actuation of dampers intermittent opening of façade windows and operation of building environmental systems. Importing boundary conditions from whole building simulation is an improvement but it discounts the impact of the flow predictions on the building domain. A transient approach is suggested which is fully coupled to flow and thermal solvers for the building fabric, environmental control systems and air flow regime. The paper reviews a number of patterns of flow evolution in strongly transient domains in response to changes in ambient conditions, damper actuation, façade openings and intermittent flow from mechanical ventilation systems.

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Future urban electrical loads are of interest to a range of stakeholders from utilities to network planners. In this paper, a pragmatic approach to the modelling of urban electrical demands using archetype models and simulated building demand profiles is described. The profiles can be scaled, transformed and combined to produce time-series electrical loads for multiple buildings connected to a substation in a distribution network. The modelling approach has been verified against measured demand data. Possible changes in future peak urban electrical demand were quantified for a sample of substations in Glasgow, UK, using four future demand scenarios. The picture emerging was complex, with peak demand increasing in some cases where electric vehicles and electrified heating combine. However, there were many situations where a combination of improved energy efficiency and microgeneration lead to reduced peak demand.

Heating loads for modern houses are lower than older houses with a larger proportion used to service domestic hot water (DHW). Electric heating systems, e.g. air source heat pumps (ASHP) and underfloor heating, offer load shifting possibilities with solar thermal DHW systems providing further opportunities. Other dynamic effects such as heat loss from water tank and stochastic demand need to be considered too. Hence integrated dynamic simulation is adopted to look at building thermal interactions with explicit plant representation and linked network mass flow and power flow solutions. Stochastic DHW use patterns characteristic of the UK are investigated. Different time controlled heating profiles are simulated to investigate demand shifting. Findings show user behaviour strongly influences water heating requirements, solar DHW system effectiveness and consequentially load shifting potential.

A building simulation tool and electric vehicle (EV) charging algorithm were used to investigate the impact of electrified home heating and EV charging on the electrical demand characteristics of a net-zero-energy UK dwelling. A range of strategies by which EV charging and electrified heating could be controlled in order to minimise peak demands were tested, including off-peak load shifting, fast and slow vehicle charging, demand limited charging and heating, and bi-directional battery operation. These were compared to a base case without electrified heating and EV charging. The results indicate that the most effective operating strategy to minimise the impact of electrification on the mean peak household electrical demand was slow vehicle charging, coupled with off-peak heat pump operation. However, heat pump load shifting had an adverse impact on indoor temperatures. Off-peak-load-shifting of both the vehicle charging and heat pump operation proved counterproductive as this inadvertently synchronised both loads, resulting in high peak demands. The most successful strategy proved to be a combination of bi-directional battery operation, coupled with load controlled charging and heat pump operation this approach limited average and absolute peak demands and almost eliminated the difference in absolute peak demands seen between fast and slow charging. (C) 2015 Elsevier B.V. All rights reserved.

Distributed, small-scale energy storage has been identified as a means of improving load factors for intermittent renewable generation and displacing the need for fossil-based backup. Domestic electric storage heaters operating within a smart grid offer high density, controllable energy storage at low cost, allowing the network operator to shift demand by charging heaters to dispose of excess supply. This paper reports monitoring outcomes and simulation studies on the first field trials of such a system, in which heaters are capable of responding to instructions from the grid to vary charging level at 15-min intervals, as well as to occupant-set controls on power output. Monitoring found significant unexpected out-of-schedule power draw and under-utilisation of storage capacity. Alternative approaches to scheduling were tested using simulations, and evaluated using metrics to quantify schedule following as well as other aspects of performance to give a balanced view of system performance to the network operator. Modern insulated storage heaters are capable of supporting load shifting for up to 48 h with minimal impact on room temperatures or demand, and with high confidence that charging schedules will be followed. However, where device controllers compete with centrally generated charge scheduling, the network will experience significant out-of-schedule power draw while occupants will experience either lower temperatures or increased cost.

Traditional modelling approaches have treated building and plant systems as existing in distinct domains, with quasi-steady state assumptions typically applied on the plant side. This paper discusses the benefits of treating the building/plant system as a single, integrated, high-resolution domain thereby adding plant-side thermal mass within the building and enabling the application of key physical process models that are already available for building models to plant components - such as explicit radiation exchange and fluid movement modelling. The approach taken is to establish a high-resolution building/plant model suitable for simulation by the ESP-r program in order to illustrate the performance appraisals then enabled. By applying simplifications that represent modelling approaches as generally practiced, the paper draws attention to the benefits of the unified, highresolution approach. The contention is that tool users need to demand better support for high-resolution building modelling, while tool developers need to agree mechnisms to provide this support. The paper concludes by briefly discussing the implications of high-resolution modelling for future extension of the building information model to support life cycle performance appraisal, and for the maintenance of compatibility with the design process given the increased computational burden.

The next 30 years could see dramatic changes in domestic energy use, with increasingly stringent building regulations, the uptake of building-integrated microgeneration, the possible electrification of heating (e.g. heat pumps) and the use of electric vehicles (EV). In this paper, the ESP-r building simulation tool was used to model the consequences of both the electrification of heat and EV charging on the electrical demand characteristics of a future, net-zero-energy dwelling. The paper describes the adaptation of ESP-r so that domestic electrical power flows could be simulated at a temporal resolution high enough to calculate realistic peak demand. An algorithm for EV charging is also presented, along with the different charging options. Strategies by which EV charging and electrified heating could be controlled in order to minimise peak household electrical demand were assessed. The simulation results indicate that uncontrolled vehicle charging and the use of electrified heating could more than double peak household power demand. By contrast, a more intelligent, load-sensitive heating and charging strategy could limit the peak demand rise to around 40% of a base case with no vehicle or electrified heating. However, overall household electrical energy use was still more than doubled.

In future low-energy buildings, electrical power and hot water use will feature prominently in the overall energy demand. Unlike space heating, these demand constituents are intermittent and vary rapidly over a few seconds. However, most building simulation tools operate at a longer time resolutions, utilising hourly climate data and so may be unable to properly capture the electrical or hot water demand characteristics. This paper demonstrates means by which electrical demand/generation and hot water draws can be modelled at higher time resolutions (1-minute) than is usually done at present. An approach to generating high-resolution climate data is also presented. An illustrative simulation highlighted different outcomes when modelling future buildings at low and high time resolutions. This showed that (in this case) although the overall energy demands and yields were similar, there discrepancies between the two temporal resolutions for import, export and self-consumption of electricity of up to 25%.

Implementing the smart grid requires coordinating competing objectives and constraints from multiple engineering domains. This paper explores the challenges involved in scheduling flexible demand according to objectives in two: the power system and household heat domains. The context is the Northern Isles New Energy Solutions project on the Shetland Islands, UK, where Active Network Management is being used to schedule flexible electric storage and immersion heaters. The study highlights that simplifications and assumptions in both domains must be coordinated to understand the overall effectiveness of a scheme. In the case study, customer facing objectives such as home comfort levels are prioritised over the power system objective of reducing fossil fuel generation. Power system operation aggregates houses into a small number of groups to allow practical scheduling. Modelling results show that this prioritisation and aggregation achieves a reduction in fossil fuel generation of 0.71GWh; 65% of that achieved if customer facing objectives are not prioritised.

With the present drive to add renewable generation capacity to existing electrical networks, utility providers are seeking ways to store electrical energy as a means of prioritising renewable sources against an unfavourable load profile. One way to do this is through electrical storage heaters and hot water systems within the domestic sector. This approach requires that the control of such devices be externalised and enacted on the basis of parameters relating to renewable energy availability and network power quality.This paper reports the simulation-related aspects of a project involving the roll-out of this approach across a large estate of houses in Lerwick on the Shetland Islands, UK. The paper describes the implementation of network sensitive equipment models for space and water heating within the ESPr system, the calibration of these models using monitored data, and the application of the outcome to identify an effective approach to equipment control and to develop a demand forecaster to enable the scheduling of network generation assets.

Integrated building performance simulation (IBPS) provides an appropriate means to appraise the performance of low energy communities featuring cooperating technologies for demand management and low carbon heat/power delivery. Only by addressing such communities in a holistic and dynamic manner can the performance characteristics of the individual technologies be discerned and overall, well-found solutions established.This paper addresses a major issue confronting the utilisation of IBPS in such a role: how to generate the initial input model in terms of the capacity levels of each technology that are likely to give an effective demand/supply match in practice. In the described work this is accomplished by using a search engine to locate the best quantitative match between demand (which could be represented by actual or anticipated data) and potential supply profiles and then using the outcome to synthesise an ESP-r model for use to ensure that the identified hybrid supply will perform well in practice. The approach outlined ensures that the final design to emerge is arrived at through a rational process as opposed to the refinement of some initial design hypothesis based on arbitrary sizing considerations.