Solar radiation data validation

This paper describes and applies a procedure for the quality control and validation of solar radiation data for two independent co-located measurement systems based at Loughborough University, United Kingdom. An assessment of the measurement error of simultaneous data from four pyranometers was undertaken over a range of averaging periods. A data filter of 0-1500W/m2 was found to reduce measurement errors by a factor of between 2 and 4 with observed hourly, daily and monthly errors of approximately 9%, 5% and 3.5% respectively for all sensors. These errors were greater than those found in the literature, indicating the possible presence of a systematic component of error. Analysis of the temporal variation of measurement error and its relationship with incident irradiance indicated the presence of an inter-system discrepancy in sensor offset. The close proximity of the two systems indicated that this was due to differences in system calibration, maintenance or response rather than environment and the results can therefore be used for future system re-calibration and to improve data accuracy. This paper demonstrates that straightforward validation procedures can yield meaningful results and greater emphasis on data validation is recommended for the solar community as a whole

Impact of wind curtailment and storage on the Irish power system 2020 renewable electricity targets: a free open-source electricity system balancing and market (ESBM) model

The All-island power system, representing the electrical grids of the Republic of Ireland and Northern Ireland, has a target of supplying 37% of electricity with wind power by 2020. This presents a considerable integration challenge, in particular associated with the increasing number of periods when there is too much wind power and not enough demand on the system, requiring wind power to be turned off or ‘curtailed’. The authors previously estimated potential curtailment on the All-island system in 2020 using a novel model. The model was validated using actual wind output and curtailment data from 2011, and produced results for 2020 indicating curtailment levels ranging from 5.6% to 8.5% - consistent with previously published estimates. This paper expands the previously published model to include: simulation of dispatch of conventional generation based on merit order; a representation of variable prices within a wholesale electricity market; and the operation of electrical energy storage within the system. The model is used to estimate the installed wind capacity required to supply 37% of electrical demand and the potential for storage to reduce the capacity required to meet this target. Finally, the model has been adapted to MS Excel and made available to download for free

Domestic photovoltaic systems, battery storage, and the economic impact of time-of-use electricity pricing

Time-of-use electricity pricing is characterised by high 'peak' prices, generally throughout the day and evening, and low 'off-peak' prices, generally at night. Consumers can benefit from time-of-use pricing provided their ratio of peakto- off-peak electricity consumption is less than a ratio of the relative prices of the two tariffs. To alter their consumption ratio, consumers can time-shift their demand, known as demand response. Consumers with grid-connected PV systems, however, already have reduced net demand during the day-time peak, due to the PV generation. The first question of interest to this paper is whether consumers with PV systems would benefit financially from switching to timeof- use pricing even if they do not engage in demand response. There remains the concern, however, of high prices during the evening peak, when the PV is not generating. Consumers unwilling or unable to engage in demand response during these periods can install battery storage systems, which are charged during the day and discharged during the evening. Two additional questions are therefore: what is the additional financial benefit of battery storage to PV systems with time-ofuse pricing and are batteries financially viable for domestic consumers with PV? These questions are answered using data from real dwellings with PV in the UK and simulating power flows using a published lead-acid battery model. Economic impacts are measured for a range of time-of-use pricing tariffs from the UK and Ireland. Results indicate that PV has little effect on the financial benefit of time-of-use pricing with day period prices that are similar to the flat rate price. For tariffs where the day period price is greater than the flat rate price, PV improves the benefit, but not enough to make it an economic choice for the average consumer. Battery storage improves the financial return, but this is not enough to make the business case positive. Even using optimistic assumptions, such as lossless batteries and high electricity price increase, system costs need to be lowered by at least 33.5% for lead-acid systems, and 195% for lithium ion systems

Demand response behaviour of domestic consumers with photovoltaic systems in the UK: an exploratory analysis of an internet discussion forum

Background: Domestic consumers with photovoltaic (PV) systems in the UK can benefit financially by time-shifting their electricity demand to coincide with the output of the PV. This behaviour is a form of demand response and can provide insights into demand response behaviour more generally. This paper investigates whether people with PV in the UK engage in demand response, what appliances are used, and whether benefitting from free, self-produced electricity appears to influence their behaviour. Methods: To achieve this, the approach presented here consists of an exploratory text analysis of an internet discussion forum frequented by consumers with PV in the UK. Results: Data was gathered on 105 forum participants with PV, of which 45 mentioned engaging in demand response, for example by changing cooking or cleaning practices. Washing machines, dishwashers and electric space and water heaters were the most commonly used appliances for demand response. Six participants engaged in demand response and yet received no direct financial benefit from this behaviour, while 14 participants specifically mentioned the influence of free electricity. Conclusions: The results illustrate novel demand response behaviour compared to previous studies and indicate that while price may be an effective initiator for demand response, there are additional factors beyond price that can enhance responses. The discussion considers the application of these factors to the development of innovative demand tariffs for low-carbon futures

Impact of wind curtailment and storage on the Irish power system 2020 renewable electricity targets: a free open-source electricity system balancing and market (ESBM) model

The All-island power system, representing the electrical grids of the Republic of Ireland and Northern Ireland, has a target of supplying 37% of electricity with wind power by 2020. This presents a considerable integration challenge, in particular associated with the increasing number of periods when there is too much wind power and not enough demand on the system, requiring wind power to be turned off or ‘curtailed’. The authors previously estimated potential curtailment on the All-island system in 2020 using a novel model. The model was validated using actual wind output and curtailment data from 2011, and produced results for 2020 indicating curtailment levels ranging from 5.6% to 8.5% - consistent with previously published estimates. This paper expands the previously published model to include: simulation of dispatch of conventional generation based on merit order; a representation of variable prices within a wholesale electricity market; and the operation of electrical energy storage within the system. The model is used to estimate the installed wind capacity required to supply 37% of electrical demand and the potential for storage to reduce the capacity required to meet this target. Finally, the model has been adapted to MS Excel and made available to download for free

Keep it simple: time-of-use tariffs in high-wind scenarios

Price signals have been suggested to bring about greater demand side flexibility and thus support the integration of variable sources of energy, such as wind. A conflict exists between keeping these signals simple for consumers, while making responses appropriate for increasingly complex supply–demand balancing dynamics in future. This study reviews some of the demand responses observed in time-of-use (ToU) tariff trials and assesses their effectiveness in scenarios with higher levels of wind. The authors simulate wholesale real-time prices for high-wind scenarios as a benchmark tariff. Simple tariff structures are compared against real-time prices for the extent to which they can ‘nudge’ demand in the ‘right direction’. They present results which suggest that even in high-wind scenarios, simple ToU tariffs could have a beneficial effect on overall system costs. The load shifting and reduction behaviour observed under ToU trials could lower energy costs by between 4 and 6% without the need for complex price signals

End-use demand in commercial office buildings: case-study and modelling recommendations

While considerable progress has been made on developing high-resolution stochastic models of electricity demand for the domestic sector, non-domestic models remain relatively undeveloped. This paper provides general recommendations about how such models might be structured for commercial offices, based on detailed analysis of high-resolution end-use demand data for a single multi-tenanted office building. The results indicate that modelling of commercial office buildings could be viewed as analogous to modelling a group of dwellings with partial residency (to represent individual office units within the building), with communal heating and communal spaces, a limited number of work related appliances, and occupant activities restricted to those related to work

Time-step analysis of the DECC 2050 calculator pathways

An hour-by-hour time-step analysis is presented of United Kingdom (UK) electricity grid balancing in low-carbon energy pathways from the DECC 2050 Calculator. The detailed modelling uses the Future Energy Scenario Assessment (FESA) tool, which uses real weather data and real electricity demand data from year 2001 to model future supply and demand profiles, suitably adjusted to reflect technology uptakes. The paper describes the linking of the DECC 2050 Calculator with FESA and many of the detailed considerations within the modelling. The calculation of net demand (total demand less intermittent renewables and inflexible portions of other electricity generation) reveals the magnitude and duration of peaks and troughs throughout the year and this allows quantification of required peaking plant, energy storage, demand response or a combination of these. The results indicate that the grid balancing challenge is much greater than is apparent from the DECC 2050 Calculator, with significant excess power from renewables and less flexible generators needing to be exported or curtailed, and, at other times of the year, a significant amount of additional conventional generation being required. FESA also indicates significantly lower capacity factors for despatchable generators than indicated in the DECC 2050 Calculator. The results underline the value of energy storage and flexible demand, particularly in the high-renewables pathways, but also that much of that storage and flexibility needs to be available for days or even weeks rather than hours

Short-run impact of electricity storage on CO2 emissions in power systems with high penetrations of wind power: a case-study of Ireland

This article studies the impact on CO2 emissions of electrical storage systems in power systems with high penetrations of wind generation. Using the Irish All-Island power system as a case-study, data on the observed dispatch of each large generator for the years 2008 to 2012 was used to estimate a marginal emissions factor of 0.547 kgCO2/kWh. Selected storage operation scenarios were used to estimate storage emissions factors – the carbon emissions impact associated with each unit of storage energy used. The results show that carbon emissions increase in the short-run for all storage technologies when consistently operated in ‘peak shaving and trough filling’ modes, and indicate that this should also be true for the GB and US power systems. Carbon emissions increase when storage is operated in ‘wind balancing’ mode, but reduce when storage is operated to reduce wind power curtailment, as in this case wind power operates on the margin. For power systems where wind is curtailed to maintain system stability, the results show that energy storage technologies that provide synthetic inertia achieve considerably greater carbon reductions. The results highlight a tension for policy makers and investors in storage, as scenarios based on the operation of storage for economic gains increase emissions, while those that decrease emissions are unlikely to be economically favourable. While some scenarios indicate storage increases emissions in the short-run, these should be considered alongside long-run assessments, which indicate that energy storage is essential to the secure operation of a fossil fuel-free grid

Can practice make perfect (models)? Incorporating social practice theory into quantitative energy demand models

Demand response could be increasingly valuable in coping with the intermittency of a future renewables-dominated electricity grid. There is a growing body of work being done specifically on understanding demand response from a people and practices point of view. This paper will start by introducing some of the recent research in this area and will present social practice theory (SPT) as a useful way of looking at the flexibility and timing of energy-use practices. However, for the insights gained from SPT to have value for the electricity supply industry it is important to be able to represent this flexibility in quantitative energy demand models. This requires an interdisciplinary conversation that allows SPT and modelling concepts to be mapped together. This paper presents an initial step in trying to achieve this. Drawing on empirical data from a recent SPT study into flexible energy-use practices, it will experiment with modelling flexible demand in such a way as to take account of the complexity of practices; not just their ‘stuff’ but also some of the images and skills involved in their competent performance. There are several reasons this is a useful enterprise. It encourages interdisciplinary insights which are valuable both to social practice theory and to energy demand modelling, it highlights new ways of intervening in flexible demand and it establishes a research agenda for social practice theorists and modellers which will eventually result in a set of requirements that can be used to build an energy demand model based on practice theory. This area of research is in its early stages and so the conceptual mapping is necessarily speculative but, hopefully, also stimulating