A review of the costs and benefits of demand response for electricity in the UK

The recent policy discussion in the UK on the economic case for demand response (DR) calls for a reflection on available evidence regarding its costs and benefits. Existing studies tend to consider the size of investments and returns of certain forms of DR in isolation and do not consider economic welfare effects. From review of existing studies, policy documents, and some simple modelling of benefits of DR in providing reserve for unforeseen events, we demonstrate that the economic case for DR in UK electricity markets is positive. Consideration of economic welfare gains is provided.

Demand response from the non-domestic sector: early UK experiences and future opportunities

Demand response is believed by some to become a major contributor towards system balancing in future electricity networks. Shifting or reducing demand at critical moments can reduce the need for generation capacity, help with the integration of renewables, support more efficient system operation and thereby potentially lead to cost and carbon reductions for the entire energy system. In this paper we review the nature of the response resource of consumers from different non-domestic sectors in the UK, based on extensive half hourly demand profiles and observed demand responses. We further explore the potential to increase the demand response capacity through changes in the regulatory and market environment. The analysis suggests that present demand response measures tend to stimulate stand-by generation capacity in preference to load shifting and we propose that extended response times may favour load based demand response, especially in sectors with significant thermal loads.

Controlling market power of vertically integrated firms in electricity networks: demand response of aggregator agents

This article reports the results of an experiment that examined how demand aggregators can discipline vertically-integrated firms - generator and distributor-retailer holdings-, which have a high share in wholesale electricity market with uniform price double auction (UPDA). We initially develop a treatment where holding members redistribute the profit based on the imposition of supra-competitive prices, in equal proportions (50%-50%). Subsequently, we introduce a vertical disintegration (unbundling) treatment with holding-s information sharing, where profits are distributed according to market outcomes. Finally, a third treatment is performed to introduce two active demand aggregators, with flexible interruptible loads in real time. We found that the introduction of responsive demand aggregators neutralizes the power market and increases market efficiency, even beyond what is achieved through vertical disintegration.

Privatisation and cross-border electricity trade: from internal market to European Supergrid?

he perspective European Supergrid would consist of an integrated power system network, where electricity demands from one country could be met by generation from another country. This paper makes use of a bi-linear fixed-effects model to analyse the determinants for trading electricity across borders among 34 countries connected by the European Supergrid. The key question that this paper aims to address is the extent to which the privatisation of European electricity markets has brought about higher cross-border trade of electricity. The analysis makes use of distance, price ratios, gate closure times, size of peaks and aggregate demand as standard determinants. Controlling for other standard determinants, it is concluded that privatisation in most cases led to higher power exchange and that the benefits are more significant where privatisation measures have been in place for a longer period.

Using proxies to calculate the carbon impact of investment into electricity network assets

Replacement and upgrading of assets in the electricity network requires financial investment for the distribution and transmission utilities. The replacement and upgrading of network assets also represents an emissions impact due to the carbon embodied in the materials used to manufacture network assets. This paper uses investment and asset data for the GB system for 2015-2023 to assess the suitability of using a proxy with peak demand data and network investment data to calculate the carbon impacts of network investments. The proxies are calculated on a regional basis and applied to calculate the embodied carbon associated with current network assets by DNO region. The proxies are also applied to peak demand data across the 2015-2023 period to estimate the expected levels of embodied carbon that will be associated with network investment during this period. The suitability of these proxies in different contexts are then discussed, along with initial scenario analysis to calculate the impact of avoiding or deferring network investments through distributed generation projects. The proxies were found to be effective in estimating the total embodied carbon of electricity system investment in order to compare investment strategies in different regions of the GB network.

Analysis and clustering of residential customers energy behavioral demand using smart meter data

Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

Post-neoliberal electricity market ‘re-reforms’ in Argentina: Diverging from market prescriptions?

This paper focuses upon the policy and institutional change that has taken place within the Argentine electricity market since the country’s economic and social crisis of 2001/2. As one of the first less developed countries (LDCs) to liberalise and privatise its electricity industry, Argentina has since moved away from the orthodox market model after consumer prices were frozen by the Government in early 2002 when the national currency was devalued by 70%. Although its reforms were widely praised during the 1990s, the electricity market has undergone a number of interventions, ostensibly to keep consumer prices low and to avert the much-discussed energy ‘crisis’ caused by a dearth of new investment combined with rising demand levels. This paper explores how the economic crisis and its consequences have both enabled and legitimised these policy and institutional amendments, while drawing upon the specifics of the post-neoliberal market ‘re-reforms’ to consider the extent to which the Government appears to be moving away from market-based prescriptions. In addition, this paper contributes to sector-specific understandings of how, despite these changes, neoliberal ideas and assumptions continue to dominate Argentine public policy well beyond the postcrisis era.

Case-based analysis in user requirements modelling for knowledge construction

Context: Learning can be regarded as knowledge construction in which prior knowledge and experience serve as basis for the learners to expand their knowledge base. Such a process of knowledge construction has to take place continuously in order to enhance the learners’ competence in a competitive working environment. As the information consumers, the individual users demand personalised information provision which meets their own specific purposes, goals, and expectations. Objectives: The current methods in requirements engineering are capable of modelling the common user’s behaviour in the domain of knowledge construction. The users’ requirements can be represented as a case in the defined structure which can be reasoned to enable the requirements analysis. Such analysis needs to be enhanced so that personalised information provision can be tackled and modelled. However, there is a lack of suitable modelling methods to achieve this end. This paper presents a new ontological method for capturing individual user’s requirements and transforming the requirements onto personalised information provision specifications. Hence the right information can be provided to the right user for the right purpose. Method: An experiment was conducted based on the qualitative method. A medium size of group of users participated to validate the method and its techniques, i.e. articulates, maps, configures, and learning content. The results were used as the feedback for the improvement. Result: The research work has produced an ontology model with a set of techniques which support the functions for profiling user’s requirements, reasoning requirements patterns, generating workflow from norms, and formulating information provision specifications. Conclusion: The current requirements engineering approaches provide the methodical capability for developing solutions. Our research outcome, i.e. the ontology model with the techniques, can further enhance the RE approaches for modelling the individual user’s needs and discovering the user’s requirements.

Time patterns in UK demand for alcohol and tobacco: an application of the EM algorithm

Capturing the pattern of structural change is a relevant task in applied demand analysis, as consumer preferences may vary significantly over time. Filtering and smoothing techniques have recently played an increasingly relevant role. A dynamic Almost Ideal Demand System with random walk parameters is estimated in order to detect modifications in consumer habits and preferences, as well as changes in the behavioural response to prices and income. Systemwise estimation, consistent with the underlying constraints from economic theory, is achieved through the EM algorithm. The proposed model is applied to UK aggregate consumption of alcohol and tobacco, using quarterly data from 1963 to 2003. Increased alcohol consumption is explained by a preference shift, addictive behaviour and a lower price elasticity. The dynamic and time-varying specification is consistent with the theoretical requirements imposed at each sample point. (c) 2005 Elsevier B.V. All rights reserved.

Life cycle analysis of UK coal fired power plants

This paper examines the life cycle GHG emissions from existing UK pulverized coal power plants. The life cycle of the electricity Generation plant includes construction, operation and decommissioning. The operation phase is extended to upstream and downstream processes. Upstream processes include the mining and transport of coal including methane leakage and the production and transport of limestone and ammonia, which are necessary for flue gas clean up. Downstream processes, on the other hand, include waste disposal and the recovery of land used for surface mining. The methodology used is material based process analysis that allows calculation of the total emissions for each process involved. A simple model for predicting the energy and material requirements of the power plant is developed. Preliminary calculations reveal that for a typical UK coal fired plant, the life cycle emissions amount to 990 g CO2-e/kWh of electricity generated, which compares well with previous UK studies. The majority of these emissions result from direct fuel combustion (882 g/kWh 89%) with methane leakage from mining operations accounting for 60% of indirect emissions. In total, mining operations (including methane leakage) account for 67.4% of indirect emissions, while limestone and other material production and transport account for 31.5%. The methodology developed is also applied to a typical IGCC power plant. It is found that IGCC life cycle emissions are 15% less than those from PC power plants. Furthermore, upon investigating the influence of power plant parameters on life cycle emissions, it is determined that, while the effect of changing the load factor is negligible, increasing efficiency from 35% to 38% can reduce emissions by 7.6%. The current study is funded by the UK National Environment Research Council (NERC) and is undertaken as part of the UK Carbon Capture and Storage Consortium (UKCCSC). Future work will investigate the life cycle emissions from other power generation technologies with and without carbon capture and storage. The current paper reveals that it might be possible that, when CCS is employed. the emissions during generation decrease to a level where the emissions from upstream processes (i.e. coal production and transport) become dominant, and so, the life cycle efficiency of the CCS system can be significantly reduced. The location of coal, coal composition and mining method are important in determining the overall impacts. In addition to studying the net emissions from CCS systems, future work will also investigate the feasibility and technoeconomics of these systems as a means of carbon abatement.

A model for comparative analysis of inventory costs of JIT and EOQ purchasing in the ready mixed concrete industry

A model for comparing the inventory costs of purchasing under the economic order quantity (EOQ) system and the just-in-time (JIT) order purchasing system in existing literature concluded that JIT purchasing was virtually always the preferable inventory ordering system especially at high level of annual demand. By expanding the classical EOQ model, this paper shows that it is possible for the EOQ system to be more cost effective than the JIT system once the inventory demand approaches the EOQ-JIT cost indifference point. The case study conducted in the ready-mixed concrete industry in Singapore supported this proposition.

An investigation of the impact of time of generation on carbon savings from PV systems in Great Britain

PV only generates electricity during daylight hours and primarily generates over summer. In the UK, the carbon intensity of grid electricity is higher during the daytime and over winter. This work investigates whether the grid electricity displaced by PV is high or low carbon compared to the annual mean carbon intensity using carbon factors at higher temporal resolutions (half-hourly and daily). UK policy for carbon reporting requires savings to be calculated using the annual mean carbon intensity of grid electricity. This work offers an insight into whether this technique is appropriate. Using half hourly data on the generating plant supplying the grid from November 2008 to May 2010, carbon factors for grid electricity at half-hourly and daily resolution have been derived using technology specific generation emission factors. Applying these factors to generation data from PV systems installed on schools, it is possible to assess the variation in the carbon savings from displacing grid electricity with PV generation using carbon factors with different time resolutions. The data has been analyzed for a period of 363 to 370 days and so cannot account for inter-year variations in the relationship between PV generation and carbon intensity of the electricity grid. This analysis suggests that PV displaces more carbon intensive electricity using half-hourly carbon factors than using daily factors but less compared with annual ones. A similar methodology could provide useful insights on other variable renewable and demand-side technologies and in other countries where PV performance and grid behavior are different.

Continental shift? An analysis of convergence trends in European real estate equities

European economic and political integration have been recognised as having implications for patterns of performance in national real estate and capital markets and have generated a wide body of research and commentary. In 1999, progress towards monetary integration within the European Union culminated in the introduction of a common currency and monetary policy. This paper investigates the effects of this ‘event’ on the behaviour of stock returns in European real estate companies. A range of statistical tests is applied to the performance of European property companies to test for changes in segmentation, co-movement and causality. The results suggest that, relative to the wider equity markets, the dispersion of performance is higher, correlations are lower, a common contemporaneous factor has much lower explanatory power whilst lead-lag relationships are stronger. Consequently, the evidence of transmission of monetary integration to real estate securities is less noticeable than to general securities. Less and slower integration is attributed to the relatively small size of the real estate securities market and the local and national nature of the majority of the companies’ portfolios.

Eliciting consumer preferences for certified animal-friendly foods: can elements of the theory of planned behavior improve choice experiment analysis?

Models used in neoclassical economics assume human behaviour to be purely rational. On the other hand, models adopted in social and behavioural psychology are founded on the ‘black box’ of human cognition. In view of these observations, this paper aims at bridging this gap by introducing psychological constructs in the well established microeconomic framework of choice behaviour based on random utility theory. In particular, it combines constructs developed employing Ajzen’s theory of planned behaviour with Lancaster’s theory of consumer demand for product characteristics to explain stated preferences over certified animal-friendly foods. To reach this objective a web survey was administered in the largest five EU-25 countries: France, Germany, Italy, Spain and the UK. Findings identify some salient cross-cultural differences between northern and southern Europe and suggest that psychological constructs developed using the Ajzen model are useful in explaining heterogeneity of preferences. Implications for policy makers and marketers involved with certified animal-friendly foods are discussed.

Winners and losers from industry reforms in the developing world: experiences from the electricity and mining sectors

The reform of previously state-owned and operated industries in many Less Developed Countries (LDCs) provide contrary experiences to those in the developed world, which have generally had more equitable distributional impacts. The economic reform policies proposed by the so-called 'Washington Consensus' state that privatisation provides governments with opportunities to raise revenues through the sale of under-performing and indebted state industries, thereby reducing significant fiscal burdens, and, at the same time, facilitating influxes of foreign capital, skills and technology, with the aim of improving operations and a "trickle-down" of benefits. However, experiences in many LDCs over the last 15-20 years suggest that reform has not solved the problem of chronic public-sector debt, and that poverty and socio-economic inequalities have increased during this period of 'neo-liberal' economics. This paper does not seek to challenge the policies themselves, but rather argues that the context in which reform has often taken place is of fundamental significance. The industry-centric policy advice provided by the IFIs typically causes a 'lock-in' of inequitably distributed 'efficiency gains', providing minimal, if any, benefits to impoverished groups. These arguments are made using case study analysis from the electricity and mining sectors.