Energy impacts of a municipal conservation policy

An analysis of one of the oldest residential conservation programs in the United States (i.e., the Davis, California Energy Conservation Building Code) reveals a 15% reduction in electricity consumption in the first 41 months of implementation. This reduction, which has been corrected for weather effects, energy-price changes, and non-local policies, is attributed to both the structural features of the code and to the energy conserving behavior of the residents of the city.     

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.     

The potential for electricity conservation and peak load reduction in the residential sector of Brazil

This paper summarizes the methodological approach and the results of a study aimed at assessing the potential for electricity conservation and peak load reduction in the Brazilian residential sector. The study splits the residential sector into 15 subsectors, considering five different geographical regions and three household income classes. Technical, economic and market potentials are determined both for electrical energy conservation and peak load reduction in the period from 2000 to 2020. The main findings show an electricity conservation technical potential for the residential sector of 28%, an economic potential of 14% and market potentials of 12% and 8%. The corresponding results found for the peak load reduction in 2020 were a technical potential of 21%, an economic potential of 4% and market potentials of 3% and 2%, with the large reduction in percentage savings for peak demand in the economic and market scenarios explained in particular by the omission of solar water heating from those scenarios. Finally, carbon dioxide emission reductions associated with the electricity conservation potentials and peak load reductions are also estimated.     

Demonstration of the environmental and demand-side management benefits of grid-connected photovoltaic power systems

This study investigated the pollutant emission reduction and demand-side management potential of 16 photovoltaic (PV) systems installed across the US during 1993 and 1994. The US Environmental Protection Agency (EPA) and 11 electric power companies sponsored the project. This article presents results of analyses of each PV system's ability to offset power plant emissions of sulfur dioxide (SO₂), nitrogen oxides (NO_x), carbon dioxide (CO₂) and particulates and to provide power during peak demand hours for the individual host buildings and peak load hours for the utility. The analyses indicate a very broad range in the systems' abilities to offset pollutant emissions, due to variation in the solar resource available and the emission rates of the participating utilities' load following generation plants. Each system's ability to reduce building peak demand was dependent on the correlation of that load to the available solar resource. Most systems operated in excess of 50% of their capacity during building peak load hours in the summer months, but well below that level during winter peak hours. Similarly, many systems operated above 50% of their capacity during utility peak load hours in the summer months, but at a very low level during winter peak hours.     

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%.     

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.     

Effect of apartment building energy renovation on hourly power demand

ABSTRACT

Optimal energy renovations of apartment buildings in Finland have a great impact on annual energy demand. However, reduction of energy demand does not necessarily translate into similar changes in peak power demand. Four different types of apartment buildings, representing the Finnish apartment building stock, were examined after optimal energy retrofits to see the influence of retrofitting on hourly power demand. Switching from district heating to ground-source heat pumps reduced emissions significantly under current energy mix. However, the use of ground-source heat pumps increased hourly peak electricity demand by 46–153%, compared to district heated apartment buildings. The corresponding increase in electrical energy demand was 30–108% in the peak month of January. This could increase the use of high emission peak power plants and negate some of the emission benefits. Solar thermal collectors and heat recovery systems could reduce purchased heating energy to zero in summer. Solar electricity could reduce median power demand in summer, but had only a little effect on peak power demand. The reduction in peak power demand after energy retrofits was less than the reduction in energy demand.     

Cost minimization for a local utility through CHP,heat storage and load management

The energy-system optimization model MODEST is described, especially heat storage and electricity load management. Linear programming is used for minimization of capital and operation costs. MODEST may be used to find the optimal investments and when to make them. The period under study can be divided into several linked subperiods which may consist of an arbitrary number of years. MODEST is here applied to a municipal electricity and district-heating system during three five-year periods. Each year is divided into three seasons. Demand peaks, as well as weekly and diurnal variations of, for example, costs are considered. The electricity demand is divided into the three sectors households, industries, and service. The electricity demand may be reduced by energy conservation, replacement of electric heating and load management. The profitability of load management, as well as cogeneration with and without heat storage at different prices of purchased power is calculated. At traditional Swedish electricity prices, the local utility should build a woodchips-fired steam-cycle CHP (combined heat and power) plant. Consumers would find it beneficial to reduce their electricity use by conservation and switching from electric heating to oil and biofuel. If just marginal power production costs are paid, the utility should introduce biomass-fired heat-only boilers instead. Electricity conservation is smaller at these lower prices. Load management is mainly profitable at the first price scheme which includes output-power-related charges. The heat storage should be used threefold: to cover demand peaks, as well as to enable increased CHP output when it is limited by the heat demand or to run heat pumps at cheap night electricity instead of in the daytime. © 1998 John Wiley & Sons, Ltd.     

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.     

An economic welfare analysis of demand response in the PJM electricity market

We analyze the economic properties of the economic demand-response (DR) program in the PJM electricity market in the United States using DR market data. PJM's program provided subsidies to customers who reduced load in response to price signals. The program incorporated a “trigger point”, at a locational marginal price of $75/MWh, at or beyond which payments for load reduction included a subsidy payment. Particularly during peak hours, such a program saves money for the system, but the subsidies involved introduce distortions into the market. We simulate demand-side bidding into the PJM market, and compare the social welfare gains with the subsidies paid to price-responsive load using load and price data for year 2006. The largest economic effect is wealth transfers from generators to non price-responsive loads. Based on the incentive payment structure that was in effect through the end of 2007, we estimate that the social welfare gains exceed the distortions introduced by the subsidies. Lowering the trigger point increases the transfer from generators to consumers, but may result in the subsidy outweighing the social welfare gains due to load curtailment. We estimate that the socially optimal range for the incentive trigger point would be $66–77/MWh.     

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.     

Photovoltaic grid-connection system as load-shaving tool in Riyadh,Saudi Arabia

A photovoltaic grid-connected (PVGC) system has been installed at the Solar Village in Riyadh. Because a PVGC system can use the utility grid as a store, the PVGC system does not need storage batteries.This will result in an initial cost reduction by about 40% as compared with an equivalent PV stand-alone system. The electric power is supplied from the PV generator or utility grid, or from both the PV generator and utility grid simultaneously. During the day time and if the load near the PVGC system is turned OFF, all the available power generated by the PV generator is supplied to the grid. The utility peak load during hot weather in the Riyadh region coincides with the maximum incident solar radiation, and hence the PVGC system produces the highest power, which can be used for load shaving and fossil-fuel conservation.     

A procedure to group residential air-conditioning load profiles during the hottest days in summer

A methodology is proposed whereby residential customers can be grouped by their diurnal air-conditioner use profiles during the hottest days in summer. The procedure, illustrated with data from a load experiment study, involves three phases. The first is to form a subset of electricity use data corresponding solely to days when utilities are likely to face summer peaking problems. The second phase is to identify a characteristic diurnal A/C load profile for each customer which adequately represents his day-to-day behavior during these peak days. The final phase is to cluster these diurnal A/C load profiles into physically consistent discrete groups. The eventual practical applications of this methodology are that it could assist utilities in better planning and implementing cost-effective peak shaving strategies.     

Adaptation to electricity crisis: Businesses in the 2011 Great East Japan triple disaster

Electricity crises can spur improvements in electricity conservation that would be unachievable under normal circumstances. This paper investigates how businesses adapted to electricity shortages following the March 11, 2011, Great East Japan earthquake, tsunami, and nuclear disaster. In summer 2011, mandatory and voluntary electricity conservation measures affected nearly all of Japan, and peak hour electricity consumption was reduced by a remarkable 18% in the Tokyo region. Using statistical data from 14 business surveys conducted in 2011 and 2012, this paper identifies patterns with regard to type of adaptation, conservation requirements, economic sector, and timeframe. Results indicate that behavioral adaptations (e.g., reduction of illumination or air conditioning) were much more common than schedule adaptations (e.g., shifting production times) or hardware adaptations (e.g., installing energy-efficient devices or private generators). Adaptation patterns were very similar between mandatory and voluntary conservation areas. Manufacturing companies were more likely to implement schedule adaptations than other companies. Certain types of adaptations persisted into 2012, especially reduction of illumination and air conditioning, and installation of energy-efficient devices. These insights may be useful for informing electricity conservation policies in non-crisis contexts.     

Peak-load management in steel plants

Mini steel-plants in India, using electric-arc furnaces for steel manufacturing, are highly energy intensive. In the context of increasing electricity prices and the introduction of time varying electricity rates by utilities, mini steel-plants can reschedule their operations to reduce their electricity bills. This paper presents a load model, which incorporates the characteristics of batch-type loads common to any type of process industry. The model is coupled with an optimisation formulation utilising integer programming for minimising the total electricity-cost satisfying production, process flow and storage constraints for different tariff structures. The methodology proposed can be used for determining the optimal response for any industry under time varying tariffs. The case study of a steel plant shows that significant reductions in peak-period demand (about 50%) and electricity cost (about 5.7%) are possible with optimal-load schedules. The utility can also get significant reduction in the peak coincident demand if large industries optimally reschedule their productions in response to time-of-use (TOU) tariff.     

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.     

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.     

Conservation and deferral potentials of demand side management programmes: A case study

Demand side management options (DSMO) can reduce the peak electricity demand for utilities. This reduction in demand is helpful to the utility in at least two ways: first, it minimizes the penalty costs of not being able to meet the peak demand and thus it has the potential to reduce costs; second, it also can defer the need for building new power plants and hence it can release, at least for some period of time, the scarce capital (which is especially important for the developing countries) for use in development activities elsewhere. These two benefits have been considered in detail in the paper. An analytical model has been developed to estimate the conservation potential of the DSM programmes. The model is then used to illustrate the benefit derived by deferring the construction of a new power plant. The model has been applied to the Maharashtra State Electricity Board, an electric utility in India, as a case study. Several scenarios have been constructed to account for different levels of the DSM possibilites. A sensitivity analysis has been carried out to tackle some of the uncertainties associated with the assumptions in the analysis.     

Smart metering for residential energy efficiency: The use of community based social marketing for behavioural change and smart grid introduction

Community-based social marketing (CBSM) has shown to be very effective at inducing behavioural change due to its pragmatic approach. It has been found that nonintegrated intensive approaches towards changing individual's behaviour, such as education and economic self-interest are not successful.This paper will explain how a large urban electricity meter replacement program can achieve a reduction in peak demand and overall energy consumption through the use of advanced metering infrastructure (AMI or ‘smart meters’) coupled with CBSM, which in turn enables the progression towards a ‘smart grid’. In order to measure success the following targets were set:

• •Peak demand reduction (peak lopping) of 20% from the households participating in the Behaviour Change Programs (BCPs).
• •Peak demand shifting (load shifting) to reduce energy consumption during ‘super peak’ by 10% in BCP participating households.
• •Average total energy use reduction of 10% in BCP participating households.

The energy efficiency actions discussed with householders during eco-coaching, and other feedback communications, are identified by utilising the information regarding barriers and benefits generated from the research phase prior to coaching. These actions can include referral to other initiatives such as the provision of reduced cost solar PV power systems, direct load control devices for domestic air-conditioners, the time-of-use pricing product, the provision of in-home-displays (IHD) and other devices necessary for development of a ‘smart grid’.     

Structural-behavioral determinants of residential energy use: Summer electricity use in Davis

Engineering models of the physical processes of energy use in individual houses are quite complex. We investigate simple statistical models of summer electricity use and compare them to engineering models. Our data include interviews, energy audits, and utility billings for a random sample of residences in Davis, California. We predict summer kWh using appliance and cooling-load models. The appliance model is based on manufacturers' or published data on average annual kWh used by major appliances; refinements for appliance location, seasonality and frequency of use have mixed success. The cooling-load model includes the major variables used in the DOE 2.1A simulation; coefficients estimated by a multiple regression model closely resemble interpolation parameters derived from DOE 2.1A. The appliance and cooling-load models explain over 50% of the variation in summer kWh in single-family detached houses. Using the appliance model and only two variables from the cooling-load model, house area and self-reported frequency of air-conditioner use, we explain nearly 60% of summer kWh in houses. The simple interview question on frequency of air-conditioner use captures most of the effects of structural features such as insulation and glazing. Finally, the appliance and cooling-load models are applied successfully to other house types (common-wall houses and apartments).