Retail Electricity Competition

We explore the implications of load profiling of consumers whose traditional meters do not allow for measurement of their real time consumption. We find the competitive equilibrium does not support the Ramsey two-part tariff. By contrast, when consumers are billed on real time prices and consumption, retail competition yields the Ramsey prices even when consumers can only partially respond to variations in real time prices. We then examine the incentive competitive retailers have to install one of two types of advanced metering equipment. Competing retailers overinvest in real time meters compared to the Ramsey optimum, but investment incentives are constrained optimal given load-profiling and retail competition. Finally, we consider the effects of physical limitations on the ability of system operators to cut off individual customers. Competing retailers have no incentive to determine the aggregate value of non-interruption of consumers, preferring instead to free-ride on other retailers serving the same zone

Retail Electricity Competition

We analyze a number of unstudied aspects of retail electricity competition. We first explore the implications of load profiling of consumers whose traditional meters do not allow for measurement of their real time consumption, when consumers are homogeneous up to a scaling factor. In general, the combination of retail competition and load profiling does not yield the second best prices given the non price responsiveness of consumers. Specifically, the competitive equilibrium does not support the Ramsey two-part tariff. By contrast, when consumers have real time meters and are billed based on real time prices and consumption, retail competition yields the Ramsey prices even when consumers can only partially respond to variations in real time prices. More complex consumer heterogeneity does not lead to adverse se1ection and competitive screening behavior unless consumers have real time meters and are not rational. We then examine the incentives competitive retailers have to install one of two types of advanced metering equipment. Competing retailers overinvest in real time meters compared to the Ramsey optimum, but the investment incentives are constrained optimal given load-profiling and retail competition. Finally effects of physical limitations on the ability of system operators to cut off individual customers. Competing retailers have no incentive to determine the aggregate value of non-interruption of consumers in the zones they serve instead to free ride on other retailers serving consumers in the same zones.

Enhanced load profiling for residential network customers

Anticipating load characteristics on low voltage circuits is an area of increased concern for Distribution Network Operators with uncertainty stemming primarily from the validity of domestic load profiles. Identifying customer behavior makeup on a LV feeder ascertains the thermal and voltage constraints imposed on the network infrastructure; modeling this highly dynamic behavior requires a means of accommodating noise incurred through variations in lifestyle and meteorological conditions. Increased penetration of distributed generation may further worsen this situation with the risk of reversed power flows on a network with no transformer automation. Smart Meter roll-out is opening up the previously obscured view of domestic electricity use by providing high resolution advance data; while in most cases this is provided historically, rather than real-time, it permits a level of detail that could not have previously been achieved. Generating a data driven profile of domestic energy use would add to the accuracy of the monitoring and configuration activities undertaken by DNOs at LV level and higher which would afford greater realism than static load profiles that are in existing use. In this paper, a linear Gaussian load profile is developed that allows stratification to a finer level of detail while preserving a deterministic representation

A review of electricity load profile classification methods

With the electricity market liberalisation in Indonesia, the electricity companies will have the right to develop tariff rates independently. Thus, precise knowledge of load profile classifications of customers will become essential for designing a variety of tariff options, in which the tariff rates are in line with efficient revenue generation and will encourage optimum take up of the available electricity supplies, by various types of customers. Since the early days of the liberalisation of the Electricity Supply Industries (ESI) considerable efforts have been made to investigate methodologies to form optimal tariffs based on customer classes, derived from various clustering and classification techniques. Clustering techniques are analytical processes which are used to develop groups (classes) of customers based on their behaviour and to derive representative sets of load profiles and help build models for daily load shapes. Whereas classification techniques are processes that start by analysing load demand data (LDD) from various customers and then identify the groups that these customers' LDD fall into. In this paper we will review some of the popular clustering algorithms, explain the difference between each method

A three-dimensional model of residential energy consumer archetypes for local energy policy design in the UK

This paper reviews major studies in three traditional lines of research in residential energy consumption in the UK, i.e. economic/infrastructure, behaviour, and load profiling. Based on the review the paper proposes a three-dimensional model for archetyping residential energy consumers in the UK by considering property energy efficiency levels, the greenness of household behaviour of using energy, and the duration of property daytime occupancy. With the proposed model, eight archetypes of residential energy consumers in the UK have been identified. They are: pioneer greens, follower greens, concerned greens, home stayers, unconscientious wasters, regular wasters, daytime wasters, and disengaged wasters. Using a case study, these archetypes of residential energy consumers demonstrate the robustness of the 3-D model in aiding local energy policy/intervention design in the UK

Forecast-informed power load profiling: A novel approach

Power load forecasting plays a critical role in the context of electric supply optimization. The concept ofload characterization and profiling has been used in the past as a valuable approach to improve forecasting performance as well as problem interpretability. This paper proposes a novel, fully fledged theoretical framework for a joint probabilistic clustering andregression model, which is different from existing models that treat both processes independently. The clustering process is enhanced by simultaneously using the input data and the prediction targets during training. The model is thus capable of obtaining better clusters than other methods, leading to more informativedata profiles, while maintaining or improving predictive performance. Experiments have been conducted using aggregated load data from two U.S.A. regional transmission organizations, collected over 8 years. These experiments confirm that the proposed model achieves the goalsset for interpretability and forecasting performance.This work is partially supported by the National Science Foundation EPSCoR Cooperative Agreement OIA-1757207 and the SpanishMINECO grants TEC2014-52289-R and TEC2017-83838-R

Distributed generation on rural electricity networks - a lines company perspective : a thesis presented in partial fulfillment of the requirements for the degree of Master of Engineering in Energy Management at Massey University

CD held with Reference copyA number of electricity assets used in rural New Zealand yield a very low return on investment. According to the provisions of the Electricity Act 1992, after 01 April 2013, lines companies may terminate supply to any customer to whom they cannot provide electricity lines services profitably. This research was undertaken to assist the policy makers, lines companies, rural investors on the viability of distributed generation in a rural setting from the point of view of the lines company and the investor as well as to provide recommendations to the problem areas. A dynamic distributed generation model was developed to simulate critical distributed generation scenarios relevant to New Zealand, such as diverse metering arrangements, time dependent electricity prices, peak shaving by load control, peak lopping by dispatchable distributed generation and state subsides, which are not addressed in commercial software. Data required to run the model was collected from a small rural North Island sheep and beef farming community situated at the end of a 26km long radial distribution feeder. Additional operational data were also collected from the community on distributed resources such as solar hot water systems. A number of optimum distributed generation combinations involving a range of technologies under different metering arrangements and price signals were identified for the small and the medium investor. The effect of influencing factors, such as state initiatives and technological growth, on the investor and the lines companies were discussed. Recommendations for future implementation in order to integrate distributed generation on to rural networks were also given. Several key research areas were identified and discussed including low cost micro hydro, wind resource assessment, diversification of the use of the induction generators, voltage flicker and dynamic distributed generation techno-economic forecasting tools

Demand Reduction and Responsive Strategies for Underground Mining

This thesis presents a demand reduction and responsive strategy for underground mining operations. The thesis starts with a literature review and background research on global energy, coal mining and the energy related issues that the mining industry face everyday. The thesis then goes on to discuss underground mine electrical power systems, data acquisition, load profiling, priority ranking, load shedding and demand side management in mining. Other areas presented in this thesis are existing energy reduction techniques, including: high efficiency motors, motor speed reduction and low energy lighting. During the thesis a data acquisition system was designed and installed at a UK Coal colliery and integrated into the mines existing supervisory control and data acquisition (SCADA) system. Design and installation problems were overcome with the construction of a test meter and lab installation and testing. A detailed explanation of the system design and installation along with the data analysis of the data from the installed system. A comprehensive load profile and load characterisation system was developed by the author. The load profiling system is comprehensive allows the definition of any type of load profile. These load profiles are fixed, variable and transient load types. The loads output and electrical demand are all taken into consideration. The load characterisation system developed is also very comprehensive. The LC MATRIX is used with the load profiles and the load characteristics to define off-line schedules. A set of unique real-time decision algorithms are also developed by the author to operate the off-line schedules within the desired objective function. MATLAB Simulation is used to developed and test the systems. Results from these test are presented. Application of the developed load profiling and scheduling systems are applied to the data collected from the mine, the results of this and the cost savings are also presented