Causal responsibility and peak load pricing

This article clarifies the basis for peak load pricing when some customers have a steady demand and others have a specific peak period demand. Causal responsibility for peak capacity rests on both types of customers. Peles, in this journal, has proposed that electricity consumption beyond the off-peak period monthly average be priced at a higher rate than other consumption. Customers consuming only on the peak would face higher prices than those who consumed relatively less during the peak. However, such a price structure can discourage economic off-peak consumption and encourage uneconomic peak period consumption. Both steady and nonsteady demanders must face the same price signal during peak periods for the achievement of efficiency, so long as each group imposes the same costs on the system.     

Price,environment and security: Exploring multi-modal motivation in voluntary residential peak demand response

Peak demand on electricity grids is a growing problem that increases costs and risks to supply security. Residential sector loads often contribute significantly to seasonal and daily peak demand. Demand response projects aim to manage peak demand by applying price signals and automated load shedding technologies. This research investigates voluntary load shedding in response to information about the security of supply, the emission profile and the cost of meeting critical peak demand in the customers’ network. Customer willingness to change behaviour in response to this information was explored through mail-back survey. The diversified demand modelling method was used along with energy audit data to estimate the potential peak load reduction resulting from the voluntary demand response. A case study was conducted in a suburb of Christchurch, New Zealand, where electricity is the main source for water and space heating. On this network, all water heating cylinders have ripple-control technology and about 50% of the households subscribe to differential day/night pricing plan. The survey results show that the sensitivity to supply security is on par with price, with the emission sensitivity being slightly weaker. The modelling results show potential 10% reduction in critical peak load for aggregate voluntary demand response.     

Flexible demand response programs modeling in competitive electricity markets

In recent years, extensive researches have been conducted on implementation of demand response programs (DRPs), aimed to electricity price reduction, transmission lines congestion resolving, security enhancement and improvement of market liquidity. Basically, DRPs are divided into two main categories namely, incentive-based programs (IBPs) and time-based rate programs (TBRPs). Mathematical modeling of these programs helps regulators and market policy makers to evaluate the impact of price responsive loads on the market and system operational conditions. In this paper, an economic model of price/incentive responsive loads is derived based on the concept of flexible price elasticity of demand and customer benefit function. The mathematical model for flexible price elasticity of demand is presented to calculate each of the demand response (DR) program’s elasticity based on the electricity price before and after implementing DRPs. In the proposed model, a demand ratio parameter has been introduced to determine the appropriate values of incentive and penalty in IBPs according to the level of demand. Furthermore, the importance of determining optimum participation level of customers in different DRPs has been investigated. The proposed model together with the strategy success index (SSI) has been applied to provide an opportunity for major players of the market, i.e. independent system operator (ISO), utilities and customers to select their favorite programs that satisfy their desires. In order to evaluate the performance of the proposed model, numerical studies are conducted on the Iranian interconnected network load profile on the annual peak day of the year 2007.     

The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use: A review

Peak demand for electricity in North America is expected to grow, challenging electrical utilities to supply this demand in a cost-effective, reliable manner. Therefore, there is growing interest in strategies to reduce peak demand by eliminating electricity use, or shifting it to non-peak times. This strategy is commonly called “demand response”. In households, common strategies are time-varying pricing, which charge more for energy use on peak, or direct load control, which allows utilities to curtail certain loads during high demand periods. We reviewed recent North American studies of these strategies. The data suggest that the most effective strategy is a critical peak price (CPP) program with enabling technology to automatically curtail loads on event days. There is little evidence that this causes substantial hardship for occupants, particularly if they have input into which loads are controlled and how, and have an override option. In such cases, a peak load reduction of at least 30% is a reasonable expectation. It might be possible to attain such load reductions without enabling technology by focusing on household types more likely to respond, and providing them with excellent support. A simple time-of-use (TOU) program can only expect to realise on-peak reductions of 5%.     

Fostering economic demand response in the Midwest ISO

The Midwest Independent System Operator (MISO) runs the power grid in 14 states and one Canadian province and has a peak demand of some 116,000 MW. Its operational area is richly supplied with reliability-triggered demand response programs such as direct load control of residential appliances and curtailable/interruptible rates for commercial and industrial customers. However, economic demand response programs are lacking. This paper discusses three different ways in which such programs can be introduced in the wholesale energy markets run by MISO. These include, first, an approach in which utilities and load serving entities move retail customers to dynamic pricing and other time-based pricing rates; second, an approach in which these same entities and possibly third-parties bid price responsive demand curves into the wholesale market; and third, an approach in which demand response is bid as a supply resource into the wholesale market.     

峰谷分时电价对用户满意度影响的系统动力学分析

峰谷分时电价作为电力需求侧管理的一种有效调峰手段,其实施会对用户的用电方式满意度和电费支出满意度产生一定的影响,从而最终影响用户对峰谷分时电价的综合满意度。从系统和运动的观点出发,分析了不同影响因素间的因果关系,基于系统动力学方法构建了峰谷分时电价对用户满意度影响的系统流程图,从峰谷电量变化、用户电费节约及用户满意度3个方面分析了峰谷分时电价对用户满意度的影响,并对不同峰谷电价比和响应敏感型用户进行了敏感性分析。结果表明,模型合理、有效。     

Analyzing the impact of the 5CP Ontario peak reduction program on large consumers

Peak reduction is an important problem in the context of the electricity grid and has led to conservation programs in various jurisdictions. For example, in Ontario, Canada, residential customers are charged higher prices during peak times, while large industrial and commercial customers pay heavy surcharges that depend on their load during Ontario’s five peak-demand days. Reducing these surcharges is a challenging problem for large consumers due to the difficulty of predicting peak days in advance.We study the impact of this peak reduction program, called 5 Coincident Peaks (5CP), on consumers by analyzing the difficulty of predicting peak-demand days and peak hours on those days. We find that even the state-of-the art peak-prediction algorithms require consumers to curtail load ten or more times, and even then, they may not identify all five peak-demand days. We also analyze alternative policies that cold help reduce peak demand in Ontario.     

Demand response modeling considering Interruptible/Curtailable loads and capacity market programs

Recently, a massive focus has been made on demand response (DR) programs, aimed to electricity price reduction, transmission lines congestion resolving, security enhancement and improvement of market liquidity. Basically, demand response programs are divided into two main categories namely, incentive-based programs and time-based programs. The focus of this paper is on Interruptible/Curtailable service (I/C) and capacity market programs (CAP), which are incentive-based demand response programs including penalties for customers in case of no responding to load reduction. First, by using the concept of price elasticity of demand and customer benefit function, economic model of above mentioned programs is developed. The proposed model helps the independent system operator (ISO) to identify and employ relevant DR program which both improves the characteristics of the load curve and also be welcome by customers. To evaluate the performance of the model, simulation study has been conducted using the load curve of the peak day of the Iranian power system grid in 2007. In the numerical study section, the impact of these programs on load shape and load level, and benefit of customers as well as reduction of energy consumption are shown. In addition, by using strategy success indices the results of simulation studies for different scenarios are analyzed and investigated for determination of the scenarios priority.     

Cost-reflective electricity pricing: Consumer preferences and perceptions

In Australia, residential electricity peak demand has risen steeply in recent decades, leading to higher prices as new infrastructure was needed to satisfy demand. One way of limiting further infrastructure-induced retail price rises is via ‘cost-reflective’ electricity network pricing that incentivises users to shift their demand to non-peak periods. Empowering consumers with knowledge of their energy usage is critical to maximise the potential benefits of cost-reflective pricing. This research consulted residential electricity consumers in three Australian states on their perceptions and acceptance of two cost-reflective pricing scenarios (Time-of-Use and Peak Capacity pricing) and associated technologies to support such pricing (smart meters, in-home displays and direct load control devices). An energy economist presented information to focus groups on the merits and limitations of each scenario, and participants’ views were captured. Almost half of the 53 participants were agreeable to Time-of-Use pricing, but did not have a clear preference for Peak Capacity pricing, where the price was based on the daily maximum demand. Participants recommended further information to both understand and justify the potential benefits, and for technologies to be introduced to enhance the pricing options. The results have implications for utilities and providers who seek to reduce peak demand.     

Air-conditioning Australian households: The impact of dynamic peak pricing

International mandates for smart metering are enabling variable and real-time pricing regimes such as dynamic peak pricing (DPP), which charges 10–40 times the off-peak rate for electricity during short periods. This regime aims to reduce peak electricity demand (predominantly due to increase in residential air-conditioning usage) and curb greenhouse gas emissions. Although trials indicate that DPP can achieve significant demand reductions, particularly in summer, little is known about how or why households change their cooling practices in response to this strategy. This paper discusses the outcomes of a small qualitative study assessing the impact of a DPP trial on household cooling practices in the Australian state of New South Wales. The study challenges common assumptions about the necessity of air-conditioning and impact of price signals. It finds that DPP engages households as co-managers of their cooling practices through a series of notification signals (SMS, phone, in-home display, email, etc.). Further, by linking the price signal to air-conditioning, some householders consider this practice discretionary for short periods of time. The paper concludes by warning that policy makers and utilities may serve to legitimise air-conditioning usage and/or negate demand reductions by failing to acknowledge the non-rational dynamics of DPP and household cooling practices.     

基于短期均衡模型的动态电价经济效率研究

针对动态电价是实现电力市场资源优化配置的重要途径问题,基于微观经济学理论建立了动态电价的短期均衡模型,通过实际算例分析了峰荷、用电总量、用户用电成本、消费者剩余、生产者剩余及社会剩余对动态电价的经济有效性。结果表明,动态电价能有效反映供电成本,引导用户有序用电,减少用电成本,具有良好的经济效率。     

Examination of optimum benefits of customer and LSE by incentive and dynamic price-based demand response

ABSTRACT

The balancing approach of electricity generation and consumption is an essential part of a reliable power system. The mismatch between supply and demand may also cause fluctuation in the power system. This study proposes an incentive and penalty-based demand response (I&P-DR) program for improving the profitability of both LSE and customers. First, we use a parameter that weighs the financial benefits of LSE and customers and provides considerable economic benefits to both sides. Second, an incentive and penalty (I&P) price scheme have been employed to recompense and penalize customers and reduce the electricity demand at peak hours. Finally, the study analyzes the importance of (I&P-DR) and its impact on customers’ sensitivity during peak intervals. Simulation results showed that the flexibility to consumption can be brought through the application of the proposed (I&P-DR) program and also provide the financial benefits to both, customers and LSEs.     

Optimal real time pricing in an agent-based retail market using a comprehensive demand response model

In this paper, a weighted combination of different demand vs. price functions referred to as Composite Demand Function (CDF) is introduced in order to represent the demand model of consuming sectors which comprise different clusters of customers with divergent load profiles and energy use habitudes. Derived from the mathematical representations of demand, dynamic price elasticities are proposed to demonstrate the customers’ demand sensitivity with respect to the hourly price. Based on the proposed CDF and dynamic elasticities, a comprehensive demand response (CDR) model is developed in this paper for the purpose of representing customer response to time-based and incentive-based demand response (DR) programs. The above model helps a Retail Energy Provider (REP) agent in an agent-based retail environment to offer day-ahead real time prices to its customers. The most beneficial real time prices are determined through an economically optimized manner represented by REP agent’s learning capability based on the principles of Q-learning method incorporating different aspects of the problem such as price caps and customer response to real time pricing as a time-based demand response program represented by the CDR model. Numerical studies are conducted based on New England day-ahead market’s data to investigate the performance of the proposed model.     

基于分布式算法的实时电价策略研究

在智能电网中,实时电价(RTP)是解决智能电网供需平衡的理想手段。通过分析国内外实时电价机制发展现状,将家庭用户负荷分为四类,综合考虑用户间的不同用电特性,构建了相应的用电效益优化模型,采用分布式算法,结合某地区的具体数据,并针对不同的需求响应方案、蓄电池成本、系统大小对模型进行仿真。结果表明,基于分布式算法的需求响应实时电价策略可使社会用电效益最大化。     

Short- and long-run time-of-use price elasticities in Swiss residential electricity demand

This paper presents an empirical analysis on the residential demand for electricity by time-of-day. This analysis has been performed using aggregate data at the city level for 22 Swiss cities for the period 2000−2006. For this purpose, we estimated two log–log demand equations for peak and off-peak electricity consumption using static and dynamic partial adjustment approaches. These demand functions were estimated using several econometric approaches for panel data, for example LSDV and RE for static models, and LSDV and corrected LSDV estimators for dynamic models. The attempt of this empirical analysis has been to highlight some of the characteristics of the Swiss residential electricity demand. The estimated short-run own price elasticities are lower than 1, whereas in the long-run these values are higher than 1. The estimated short-run and long-run cross-price elasticities are positive. This result shows that peak and off-peak electricity are substitutes. In this context, time differentiated prices should provide an economic incentive to customers so that they can modify consumption patterns by reducing peak demand and shifting electricity consumption from peak to off-peak periods.     

Demand side management program evaluation based on industrial and commercial field data

Demand Response is increasingly viewed as an important tool for use by the electric utility industry in meeting the growing demand for electricity. There are two basic categories of demand response options: time varying retail tariffs and incentive Demand Response Programs. Electricity Saudi Company (ESC) is applying the time varying retail tariffs program, which is not suitable according to the studied load curves captured from the industrial and commercial sectors. Different statistical studies on daily load curves for consumers connected to 22 kV lines are classified. The load curve criteria used for classification is based on peak ratio and night ratio. The data considered here is a set of 120 annual load curves corresponding to the electric power consumption (the western area in the King Saudi Arabia (KSA)) of many clients in winter and some months in the summer (peak period). The study is based on real data from several Saudi customer sectors in many geographical areas with larger commercial and industrial customers. The study proved that the suitable Demand Response for the ESC is the incentive program.     

The effect of sociodemographic diversity of residential customers on the financial risk experienced in the retail electricity market

The sociodemographic diversity of residential customers can affect the level of financial risk that an electricity provider experiences in the retail market. To demonstrate the relationship between sociodemographic diversity and financial risk, electricity consumption data drawn from the United Kingdom Power Networks ‘Low Carbon London’ project was analyzed to explore the relationship between sociodemographic diversity and financial risk experienced by electricity retailers. The results show that when increasing the sociodemographic diversity amongst a group of residential customers the effect on financial risk depends on the electricity consumption patterns of individual customers and the relationship of consumption patterns between residential customers. Increasing sociodemographic diversity amongst residential customers with very distinct energy consumption patterns can decrease the overall financial risk associated with the aggregated revenue received from these customers. However, the results showed that adding customers to a customer base without consideration for their sociodemographic background can cause the overall financial risk associated with the aggregated revenue received to change erratically. Whilst previous studies have considered customer diversity and its influence on peak electricity demand, this research advances the state-of-the-art by showing the importance of customer diversity to the financial quantity risk experienced by electricity retailers. This finding has serious implications for electricity providers seeking to mitigate financial risk in the retail electricity market.     

The residential demand for electricity by time-of-use: A survey of twelve experiments with peak load pricing

Information on customer response to time-of-use (TOU) rates plays a major part in utility resource planning, particularly in the design of cost-based rate structures and cost-effective load management programs. Several elasticity concepts have been used by economists to analyze customer response to TOU rates. We discuss the interrelationships between various concepts and show that total uncompensated price elasticities are the appropriate measure of customer response.Evidence from twelve pricing experiments involving about 7000 customers indicates that residential peak-period electricity consumption is generally price-sensitive. TOU rates generally reduce peak period electricity use, as well as daily use. Response is generally higher for high use customers.Short-run own-price elasticities of peak consumption range from nil to ?0.45. Off-peak elasticities lie in a similar range, but are less statistically significant. This wide range indicates that elasticities are not fixed constants but vary parametrically with several conditioning variables such as level of total (daily) electricity use, composition of appliance portfolio and duration of pricing periods. If proper allowance is made for these interactions, it may be possible to transfer elasticities between utility service areas, thus obviating the expensive and time-consuming need for every utility to conduct its own experiment.     

Automated demand response system in lighting for optimization of electricity cost

Daylighting is an important factor in improving visual comfort and energy efficiency. Lighting control using daylighting can reduce energy consumption in buildings. This thesis proposes an automatic demand response system for lighting based on wireless sensor networks (WSN) in order to reduce the peak electricity demand according to the stage of electricity rate with real-time pricing (RTP), time of use pricing (TOUP), and critical peak pricing (CPP). The proposed system automatically controls the slat angle of the venetian blind with a cut-off angle according to the altitude of the sun, automatically executing light dimming according to measured current luminance to remove an unpleasant glare caused by daylighting. The target illuminance of area at this time is set at a minimum illuminance required for the work execution in the office during the time zone where the electricity load is high to save the lighting energy cost, while a maximum illuminance is set during the time zone where the electricity load is low according to the real-time electricity pricing stages obtained through the advanced metering infrastructure (AMI) in order to improve the work efficiency of the occupants. In this study, two testbeds having the same environments, as well as a control system targeting a fixed illuminance per price system, were established. The illuminance energy consumption and cost were then measured and the effect of the proposed illuminance system was evaluated.     

A comparative analysis of time-of-use electricity rate effects: The Arizona experiment

To date, analyses of the data from the Arizona time-of-use (TOU) electricity pricing experiment have failed to find a significant relationship between electricity usage and electricity price. Results indicated that if the TOU rates had an effect on usage, the effect was virtually identical for each TOU rate. In this study, usage in 1976 under the TOU rates is compared to usage in 1975 under the existing (declining block) rate to determine whether or not there was an effect.It is found that peak period usage was reduced under TOU rates by 7–16% after adjusting for differences in weather between the two years. To a lesser extent, customers reduced their usage during the intermediate period and shifted some consumption to the base period. Total consumption appears to have decreased slightly. It is emphasized that these effects of the TOU rates cannot be discovered in demand analyses that do not utilize the baseline year data.