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%.     

The benefits of combining utility-controlled demand response with residential zoned cooling

This paper evaluates the effectiveness of combining direct load control with a residential zoned-cooling technology in meeting the objectives of reducing peak demand and maintaining home comfort level. In contrast, the traditional approach has been for utilities to smooth summer peak cooling loads, by controlling the cooling load of the whole house. While accounting for weather, dwelling characteristics and demographics, with detailed field data, we are able to develop empirical models to evaluate the benefits of utility control of cooling loads for a residential zoned cooling system during summer peak-demand periods and to compare with non-zoned systems. A zoned house allows for an upper floor cooling interruption without affecting the comfort on the main floor. An upper floor interruption for a full 4 h during the day leads to an average peak air conditioning change of ?0.52 kW, approximately 1.6 times the reduction from the curtailment of cooling by cycling the air conditioning serving the whole house.     

Beyond the end-consumer: how would improvements in residential energy efficiency affect the power sector in Saudi Arabia?

Energy efficiency in buildings has garnered significant attention in Saudi Arabia. This paper outlines the potential effects of higher residential efficiency on electricity load profiles in the Kingdom. It further presents the associated benefits that could have been realized by the local utilities in 2011. To perform the analysis, we designed an integrated methodology in which an engineering-based residential electricity demand model is used within an economic equilibrium framework. The modeling approach allows us to capture the physical interactions arising from higher efficiency and the structural changes that could occur in the economy beyond the end-consumers. Raising the average air-conditioner energy efficiency ratio (EER) to 11 British thermal unit (BTU)/(Wh) from its 2011 average would have saved 225,000 barrels/day of crude oil in electricity generation. Alternatively, increasing the share of insulated homes from 27 to 64 % would have allowed the power sector to lower its use of the fuel by 158,000 barrels/day. Combining both measures in a single simulation yields incremental yet not additive reductions. All alternative scenarios reduce costs to the utilities and improve the average thermal efficiency for the electricity generated. The studied efficiency options shift the load curve downward during the peak load segment when the least efficient turbines would be used. We additionally show how efficiency improvements in end-uses can affect the decisions of other sectors in the economy.     

Electric utility energy conservation and load management programmes: R & D opportunities

During recent years, electric utilities have begun a variety of new programmes to manage their future load growth. In many cases, these conservation and load management (C/LM) programmes serve as alternatives to traditional electricity supply resources. Additional development of planning, analysis and evaluation methods is needed before utilities can fully rely on these C/LM programmes as legitimate electric system resources. This paper discusses several important research topics. These topics include better use of data from evaluations of C/LM programmes to improve demand forecasting models, development of models to predict participation in future utility C/LM programmes, review of existing integrated resource planning models, assessment of alternative regulatory treatment of C/LM programmes by state public utility commissions, and identification of better ways to disseminate results on effective C/LM programmes among utilities.     

Load management in the Indian power sector using US experience

India has a scarcity of electric power during peak-use periods. Most Indian utilities resort to load shedding (LS) to manage the peak demand. A review of US experience with direct load control and interruptible or time-of-use (TOU) tariffs shows successful programs. Direct load control of agricultural pumps, commercial air conditioners and interruptible or TOU tariffs in the industrial sector are identified as useful options for India. Implementation strategies for these are suggested. Load management (LM) by Indian utilities may provide a better solution to the current peak power shortage than mandatory LS.     

A demand-side planning approach for the commercial sector of developing countries

A methodology is proposed for collecting end-use demand data for devising demand-side management programs in the commercial sector of developing countries. The characteristics of electricity end-uses in this sector are diverse. The end-use data have been collected in one or two segments of the commercial sector for simplicity and to save time and money. In the case of Northern Cyprus, hotels, a segment of this sector, have a high potential for utility load reduction. A survey was conducted in which questions were asked about the installed capacities of water and space heating, cooling, lighting and refrigeration and their time of use. Typical end-use load curves were obtained for the winter and summer seasons. It is estimated that summer peak could be reduced by approximately 11% if the DSM programs, costing just over half-a-million dollars, are adopted.     

Building air conditioning system using fuel cell: Case study for Kuwait

Air conditioning machines in Kuwait consume more than 75% of electric energy generated at peak load time. It is in the national interest of Kuwait to decelerate the continuous increase of peak electric power demand. One way to do this is to install for new complexes or high-rise apartments buildings distributed utilities (isolated small power plants), mainly for air conditioning A/C systems. Fuel cells are among the alternatives considered for distributed utilities.This paper discusses the use of commercially available phosphoric acid fuel cell PAFC, known as ONSI P25 to operate air conditioning systems for big buildings in Kuwait.The proposed fuel cell, which is usually delivered with built-in heat exchanger for hot water, is operated by natural gas and uses a propylene glycol-water loop to recover thermal energy. The PAFC has 200 kW nominal electric power capacity, and produces thermal energy of 105 kW thermal energy at 120 °C, and 100 kW at 60 °C.The performance characteristics for the proposed fuel cell are very well documented. In the present study, it is suggested that the fuel cell operates combined mechanical vapor compression and absorption water chillers to utilize the fuel cell full output of electric power and waste heat. Also, to meet the required A/C cooling capacity system by the limited fuel cell power output, it is proposed to use cold storage technique. This allows fuel cell power output to supply the needed energy for average as well as peak A/C system capacity.     

The effects of combining dynamic pricing, AC load control, and real-time energy feedback: SMUD’S 2011 Residential Summer Solutions Study

The 2011 Residential Summer Solutions Study compared the hourly load effects of three different real-time information treatments and two program options. The information treatments included: Baseline information (no real-time data), real-time Home information (whole-house data), and real-time Appliance information (data for the whole house plus three individual appliances). Compared to the Baseline group, real-time Home information lowered overall energy use by about 4 %. Real-time information at both the Home and Appliance levels had a significant effect on non-event peak loads: compared to the Baseline group, real-time Home data lowered peak load by 5 %, while Appliance data lowered peak load by 7 %. All three information treatments averaged a 1-kW (40 %) load shed during events. The customer-chosen program options included a dynamic time-of-use rate and a load control incentive program. Customers were more likely to sign up for the dynamic rate, and those who did saved significantly more peak load on both event days (>50 % savings) and non-event days (>20 % savings) than did those on the load control program alone. In addition, those on the dynamic rate saved twice as much on their summer bills as did those who chose to remain on the standard tiered rate. At the end of the summer, more than 90 % of participants signed up to participate again the following year.     

Simulation of disaggregated load profiles and development of a proxy microgrid for modelling purposes

The deployment of small‐scale renewable energy technologies affects the electricity grid depending on the local resource potential as well as on the regional composition of consumers. Spatially explicit renewable energy supply data and spatially disaggregated load profiles of consumers are usually not available to modellers. These data are, however, necessary to better account for the particularities of electricity systems with high levels of distributed renewable production. We present a methodology to estimate the load profile for the distribution grid of household and commercial consumers at 1 km pixel resolution for Austria. Consequently, we combine statistical data on the distribution of electricity consumers with standardized load profiles. Additionally, we present a model that allows allocating theoretical transformers to pixels allowing constructing proxy microgrids. We validate the load generation methodology for three different days and seasons. Hence, we use recently measured load profiles from the federal state of Vorarlberg. The proxy microgrids are validated using data on transformer locations from the federal state of Upper Austria. The modelling approach allows reproducing the historically measured load profiles and the number and location of transformers in the distribution grid with reasonable accuracy. The validation results show that about 80–91% of the variance of the modelled demand data can be explained by the variance of the measured data. In addition, about 78% of the transformer locations can be replicated. Copyright © 2014 John Wiley & Sons, Ltd.     

The mitigating effect of strategic behavior on the net benefits of a direct load control program

Demand response is an important tool for utilities to manage load during peak periods. While the effects of demand response programs on peak load reductions are well studied and intuitive, assessments typically fail to recognize the potential for off-peak behavioral responses that may mitigate the total benefits of the program. Using smart meter consumption data on residential air conditioning units enrolled in a direct load control program, this paper examines the changes in consumption prior to and after curtailment events. The results suggest substantial increases in off-peak consumption, which reduce energy, monetary, and environmental benefits of the program by over 40%.     

Evaluating rammed earth walls: a case study

The following research has been undertaken as a response to the recent controversy regarding the suitability of rammed earth wall construction as an effective building envelope in regard to its thermal performance. The R-value for rammed earth walls is low hence they might be expected to conduct heat into a building during summer. However the large mass of these walls and the associated thermal lag in heat transfer from outside to inside may result in the walls performing satisfactorily in a building which is only occupied during working hours. Internal rammed earth walls may act as moderators of large diurnal temperature swings helping to produce an even comfortable temperature within a building. Empirical (in situ) measurements of temperature and heat flux were taken on the walls of an existing rammed earth office building in New South Wales, Australia during the summer. An analysis was performed which established a methodology to measure the heat flow associated with the walls, floor, ceiling, windows and infiltration for one office during occupied hours and the net energy transferred between the office and these elements was established. During this time the earth walls performed well. External walls were found to transmit comparatively little heat to the office and the internal walls absorbed heat during this time. Diffuse sky radiation transmitted by the window and infiltration are both likely to be important factors in the summer heat load.     

The behaviour of publicly owned utilities in wholesale electricity markets : The case of the Pacific Northwest

Seemingly unrelated regression techniques are used to estimate wholesale demand functions for three public utilities purchasing power from a federal agency between 1981 and 1983. From hourly data, three separate goods are defined: intrapeak maximum demand, peak period energy consumption and off-peak energy consumption. Explanatory variables include normalized peak period price, retail load served by the utilities, hydroelectric energy potential and opportunity cost of own resources. These utilities are shown to respond quickly and predictably to changes in the relative cost of purchased power, and to act in manners consistent with cost-minimization.     

Economic impact of integrating photovoltaics with conventionalelectric utility operation

The parameters which impact the value of photovoltaics (PV) to the electric utility is examined. High, medium, and low-load days in winter (January) and summer (July) are studied. The daily peak load is varied from 5838 MW to 9712 MW. These six days are studied for reference (no PV), high, medium, low, and intermittent-PV output cases. Results from these 30 case studies are summarized. In order to study the impact of operating PV systems on the electric utility production cost (fuel and variable operation and maintenance), the load profile of a southeastern utility and the PV output data from solar test facilities in Virginia and North Carolina are used. The performance analysis shows that, while the total production (fuel and variable O&M) cost savings are higher for higher solar days, the increase is not proportional to the amount of PV energy output. It is shown that the high solar day never produced the highest per-unit PV energy value. The highest per-unit PV energy values for both winter and summer days are found to be for the low solar days     

A comparison of the solar-gas and solar-electric interface

Solar energy has several distinguishing features that bear heavily upon the eventual interfacing with gas and electric utility systems. Chief among these is its intermittent or diurnal nature, which presents differing considerations and challenges for use in conjunction with gas and electric utilities.Gas utilities provide for a winter peaking by producing year-round and storing natural gas in large underground formations, principally aquifers. Electric utilities produce on demand and rely on reserve capacity to meet summer peaks. The gas production-pipeline-storage-distribution system is chemical in nature and relatively tolerant to addition of gas of varying composition and nature. Electric systems are dynamic in nature and relatively intolerant ot the introduction of off-specification energy forms, and thus require elaborate interface protection. The storability of natural gas complements the noncontinuous aspect of solar energy and makes gas-augmented solar systems attractive. These systems can, and in many cases must, be located near the end-use site. Dispersed solar systems are attractive for electrical energy production and consumption at remote locations, for example, for irrigation water pumping. Solar electric systems that are grid connected must be of sufficient magnitude to justify the interface costs with the national grid.Solar-gas systems are preferable for space and water conditioning for homes and institutional buildings. Solar-electric systems can be either dispersed or grid connected, but the scale of technology required is considerably different in these two applications.     

Residential PV capacity estimation and power disaggregation using net metering measurements

As the intermittency and uncertainty of photovoltaic (PV) power generation poses considerable challenges to the power system operation, accurate PV generation estimates are critical for the distribution operation, maintenance, and demand response program implementation because of the increasing usage of distributed PVs. Currently, most residential PVs are installed behind the meter, with only the net load available to the utilities. Therefore, a method for disaggregating the residential PV generation from the net load data is needed to enhance the grid-edge observability. In this study, an unsupervised PV capacity estimation method based on net metering data is proposed, for estimating the PV capacity in the customer’s premise based on the distribution characteristics of nocturnal and diurnal net load extremes. Then, the PV generation disaggregation method is presented. Based on the analysis of the correlation between the nocturnal and diurnal actual loads and the correlation between the PV capacity and their actual PV generation, the PV generation of customers is estimated by applying linear fitting of multiple typical solar exemplars and then disaggregating them into hourly-resolution power profiles. Finally, the anomalies of disaggregated PV power are calibrated and corrected using the estimated capacity. Experiment results on a real-world hourly dataset involving 260 customers show that the proposed PV capacity estimation method achieves good accuracy because of the advantages of robustness and low complexity. Compared with the state- of-the-art PV disaggregation algorithm, the proposed method exhibits a reduction of over 15% for the mean absolute percentage error and over 20% for the root mean square error.     

Magnetically Confined Kinetic-Energy Storage Ring using Attractive Levitation

A design concept is presented for a magnetically confined kinetic-energy storage ring (MCKESR) using attractive levitation. Key features of the design include passive ring orbital stability by the method of alternating gradients, a continuous ring to minimize major loading fluctuations, and an external dump chamber that preserves the stationary components in case of loss of confinement. The rotating ring acts as a rotor of a synchronous motor/generator, with permanent magnets mounted on the ring interacting with copper coils that are connected to a cycloconverter to provide power input/output. For a MCKESR device capable of providing diurnal load leveling to utilities, material costs appear reasonable.     

A model for generating household electricity load profiles

Electricity consumption data profiles that include details on the consumption can be generated with a bottom‐up load models. In these models the load is constructed from elementary load components that can be households or even their individual appliances. In this work a simplified bottom‐up model is presented. The model can be used to generate realistic domestic electricity consumption data on an hourly basis from a few up to thousands of households. The model uses input data that is available in public reports and statistics. Two measured data sets from block houses are also applied for statistical analysis, model training, and verification. Our analysis shows that the generated load profiles correlate well with real data. Furthermore, three case studies with generated load data demonstrate some opportunities for appliance level demand side management (DSM). With a mild DSM scheme using cold loads, the daily peak loads can be reduced 7.2% in average. With more severe DSM schemes the peak load at the yearly peak day can be completely levelled with 42% peak reduction and sudden 3 h loss of load can be compensated with 61% mean load reduction. Copyright © 2005 John Wiley & Sons, Ltd.     

Evaluation of a community-Based electricity load management program

During the summer of 1980, Davis (CA) undertook a program to encourage residents to reduce peak electricity use. The program was initiated by the local utility company and carried a collective financial incentive: for every 1% reduction in peak electricity use, the utility would reward the city $10,000 up to a maximum of $100,000. This paper discusses the program and evaluates its effects during the first experimental summer of operation.Most of the strategies developed in Davis to reduce peak load also indirectly encouraged conservation during off-peak hours, and the program evolved, in effect, as a conservation program. Total electricity use for the Davis residential sector, adjusted for weather and prices, was reduced by about 7%, and the reduction of peak load was somewhat greater. The program was economically rewarding to residents, the city, and the utility. In addition, the program had other, intangible impacts on general energy consciousness and community spirit.     

Insulation and bivalent heating system optimization: Residential housing retrofits and time-of-use tariffs for electricity

Time-of-use tariffs, which reflect the cost of producing one extra unit of electricity, will be more common in the future. In Sweden the electricity unit price will be high during the winter and cheaper during the summer. A bivalent heating system, where an oil-fired boiler takes care of the peak load, when the electricity price is high, and a heat pump the base load, may decrease the cost of space heating substantially. However, insulation retrofits are also likely to reduce the peak space-heating load in a building. This paper shows how a bivalent heating system can be optimized while also considering the insulation measures. The optimization is elaborated by the use of a mixed integer programming model and the result is compared with a derivative optimization method used in the OPERA (optimal energy retrofit advisory) model. Both models use the life-cycle cost (LCC) as a ranking criterion, i.e. when the lowest LCC for the building is achieved, no better retrofit combination exists for the remaining life of the building.     

A systems approach for sizing a stand-alone residential PEMFC power system

Polymer electrolyte membrane fuel cells (PEMFCs) show great promise in portable, automotive, and stationary applications. They have reached the test and demonstration phase in automotive and power markets today. This paper is focused on a stand-alone residential PEMFC power system that provides the electricity needs of the house. A novel stochastic sizing methodology is developed that considers both fuel cell system dynamics and residential load dynamics in overall system sizing for the stand-alone residential fuel cell power system. Understanding the nature of demand side is critical in stand-alone system sizing. Thus, experimental measurements have been completed to capture the load side dynamics in detail. No such data is found in the current literature. The Threshold Bootstrap method is used to model the residential load demand and to produce many realistic load profiles. Matlab/Simulink is used to run system simulations to determine system sizes based on parameters defined through a designed experiment. Comparison between the proposed sizing method and a possible worst case scenario sizing is given. The new sizing methodology can be used together with sophisticated demand analysis programs to obtain customized sizing for each user as stand-alone power systems become more viable.