Time-of-use Rates Research Articles

Time-of-use based electricity demand response for sustainable manufacturing systems

As required by the Energy Policy Act of 2005, utility companies across the U.S. are offering TOU (time-of-use) based electricity demand response programs. The TOU rate gives consumers opportunities to manage their electricity bill by shifting use from on-peak periods to mid-peak and off-peak periods. Reducing the amount of electricity needed during the peak load times makes it possible for the power grid to meet consumers' needs without building more costly backup infrastructures and help reduce GHG (greenhouse gas) emissions. Previous research on the applications of TOU and other electricity demand response programs has been mainly focused on residential and commercial buildings while largely neglected industrial manufacturing systems. This paper proposes a systems approach for TOU based electricity demand response for sustainable manufacturing systems under the production target constraint. Key features of this approach include: (i) the electricity related costs including both consumption and demand are integrated into production system modeling; (ii) energy-efficient and demand-responsive production scheduling problems are formulated and the solution technique is provided; and (iii) the effects of various factors on the near-optimal scheduling solutions are examined. The research outcome is expected to enhance the energy efficiency, electricity demand responsiveness, and cost effectiveness of modern manufacturing systems.

The Efficacy of Electric Vehicle Time-of-Use Rates in Guiding Plug-in Hybrid Electric Vehicle Charging Behavior

This paper presents a series of analyses whose goal is to understand the effectiveness with which time-of-use (TOU) rates can economically incent off-peak charging in plug-in hybrid electric vehicles (PHEV). The total cost of fueling PHEV under modeled and real-world TOU rates is compared to the total cost of fueling PHEV under constant rates. Time-resolved vehicle energy consumption and fueling cost is derived for a variety of PHEV designs from travel survey data and charging behavior models. A decision tree model of PHEV consumer choices is proposed with effectiveness and cost metrics defined at each decision point. Results show that gasoline PHEV that charge off-peak incur higher gasoline costs than PHEV that charge at-will. These additional fueling costs reduce the magnitude of the economic incentives for off-peak charging that TOU rates can provide to PHEV consumers. These results are then used to compare and evaluate the effectiveness of model and real-world TOU rates and to discuss implications for modeling PHEV total fueling cost.

전기자동차의 충전부하 모델링 및 충전 시나리오에 따른 전력계통 평가

Electric Vehicles(EVs) and Plug-in Hybrid Electric Vehicles(PHEVs) which have the grid connection capability, represent an important power system issue of charging demands. Analyzing impacts EVs charging demands of the power system such as increased peak demands, developed by means of modeling a stochastic distribution of charging and a demand dispatch calculation. Optimization processes proposed to determine optimal demand distribution portions so that charging costs and demand can possibly be managed. In order to solve the problems due to increasing charging demand at the peak time, alternative electricity rate such as Time-of-Use(TOU) rate has been in effect since last year. The TOU rate would in practice change the tendencies of charging time at the peak time. Nevertheless, since it focus only minimizing costs of charging from owners of the EVs, loads would be concentrated at times which have a lowest charging rate and would form a new peak load. The purpose of this paper is that to suggest a scenario of load leveling for a power system operator side. In case study results, the vehicles as regular load with time constraints, battery charging patterns and changed daily demand in the charging areas are investigated and optimization results are analyzed regarding cost and operation aspects by determining optimal demand distribution portions.

台湾住宅时间电价与节电奖励制度之评析

本文探讨住宅用户“时间电价”与“节电奖励制度”之利弊得失，采用Kolmogorov-Smirnov统计量检定台电目前住宅时间电价尖、离峰的划分方式能否真实反映实际负载分布之情况。现行的住宅时间电价尖离峰价差是否能有效率地反映出尖、离峰之发电成本差异，亦是本文探讨的焦点。此外，已造成台电公司相当亏损的“节电奖励制度”的实施成效亦值得检讨，本研究发现，如何让住户在适当的时间以及地理区位上节省电力消费，提升节能效益，是未来的改进方向。 Over the past several years, the Taiwan Power Company has launched two smart pricing programs to assess the demand response of residential customers. Namely, the Time-of-Use (TOU) rate scheme de- signed for smart meter customers and the Demand Reduction Incentive (DRI) scheme for the residential sec- tor are typical examples. This paper discusses these two programs and evaluates their respective perform- ances. Our study adopts two-sample Kolmogorov-Smirnov test to evaluate the appropriateness of current par- titions in the electricity load profiles and develops an efficient approach based on marginal cost pricing to re- design the TOU rate scheme for effective load management. Although the DRI scheme performs well, further improvements in energy saving and carbon reduction is necessary to reach an efficient win-win solution among customers, the utility and society. This can be achieved via a careful design of incentive tariff dis- counts to take account of the time-of-use or location-specific features of the power supply/demand condition.

The importance of marginal cost electricity pricing to the success of greenhouse gas reduction programs

The efficient reduction of GHG emissions requires appropriate retail pricing of off-peak electricity. However, off-peak electricity for residential consumers is priced at 331% above its marginal cost in the United States as a whole (June 2009). Even for the 1% of residences that are on some form of time-of-use (TOU) rate schedule, the off-peak rate is almost three times higher than the marginal cost. A barrier to marginal-cost based TOU rates is that less than 9% of U.S. households have the “smart” meters in place that can measure and record the time of consumption. Policies should be put in place to achieve full deployment. Another important barrier is consumer concern about TOU rate design. Two TOU rate designs (baseline and two-part tariff) are described that utilize marginal-cost based rates, ensure appropriate cost recovery, and minimize bill changes from current rate structures. A final barrier is to get residences on to these rates. Should a marginal-cost based TOU rate design remain an alternative for which residences could “opt-in,” or become the default choice, or become mandatory? Time-invariant rates are a historical anachronism that subsidize very costly peak-period consumption and penalize off-peak usage to our environmental detriment. They should be phased out.

Wind-photovoltaic capacity coordination for a time-of-use rate industrial user

As the capacity of wind and photovoltaic (PV) generation systems increases, wind-PV capacity coordination for a time-of-use (TOU) rate industrial user may become an important problem. This coordination can maximise the economic benefits of investing in a wind generation system and a PV generation system. An evolutionary particle swarm optimisation approach to solve the wind-PV capacity coordination for a TOU rate industrial user is proposed. A benefit-cost ratio (BCR) is used to evaluate the economic benefit of investing in wind and PV generation systems for a TOU rate industrial user. The optimal contract capacities and the optimal installed capacities of the wind and PV generation systems for a TOU rate industrial user are obtained. The BCR of investing in wind and PV generation systems are maximised. Test results illustrate the merits of the proposed approach and help determine the impact of changes in electricity cost and capital cost on wind-PV capacity coordination for a TOU rate industrial user.

The effect of the programs for demand response incentives in competitive electricity markets

AbstractThe special features of electricity such as non‐storability and lack of good substitutes, the network related market power and the demand inelasticity result in high volatile electricity prices in pool markets, especially during peak hours. Demand response (DR) programs with the aid of distributed energy resources (DER) provide the means to increase demand elasticity and, as a consequence, to counteract the effect of market power.This paper aims to assess the effectiveness of DR programs and try to answer to what extend DR programs will increase the demand elasticity and to what degree it will reduce the market power. Two DR programs, that is, time of use (TOU) rate and economic load response program (ELRP) are considered in this paper and the possible price responsiveness of load is modeled as linearly correlated to the difference of day and night TOU rate and the compensation price of load curtailment in order to determine the demand elasticity frontier. Game theory is employed to model the strategic bidding of generation companies (GenCos) and the Lerner index is used to quantify the market power. The proposed model is applied in Italian electricity market for numerical study. Copyright © 2008 John Wiley & Sons, Ltd.

Operating Schedule of Battery Energy Storage System in a Time-of-Use Rate Industrial User With Wind Turbine Generators: A Multipass Iteration Particle Swarm Optimization Approach

This paper presents a new algorithm for the solution of nonlinear optimal scheduling problems. This algorithm is called ldquomultipass iteration particle swarm optimizationrdquo (MIPSO). A new index called ldquoiteration bestrdquo is incorporated into ldquoparticle swarm optimizationrdquo (PSO) to improve solution quality. The concept of multipass dynamic programming is applied to further modify the PSO to improve computation efficiency. The MIPSO algorithm is used to solve the optimal operating schedule of a battery energy storage system (BESS) for an industrial time-of-use (TOU) rate user with wind turbine generators (WTGs). The effects of wind speed uncertainty and load are considered in this paper, and the resulting optimal operating schedule of the BESS reaches the minimum electricity charge of TOU rates users with WTGs. The feasibility of the new algorithm is demonstrated by a numerical example, and MIPSO solution quality and computation efficiency are compared to those of other algorithms.

Iteration particle swarm optimization for contract capacities selection of time-of-use rates industrial customers

This paper presents a new algorithm for solving the optimal contract capacities of a time-of-use (TOU) rates industrial customer. This algorithm is named iteration particle swarm optimization (IPSO). A new index, called iteration best is incorporated into particle swarm optimization (PSO) to improve solution quality and computation efficiency. Expanding line construction cost and contract recovery cost are considered, as well as demand contract capacity cost and penalty bill, in the selection of the optimal contract capacities. The resulting optimal contract capacity effectively reaches the minimum electricity charge of TOU rates users. A significant reduction in electricity costs is observed. The effects of expanding line construction cost and contract recovery cost on the selection of optimal contract capacities can also be estimated. The feasibility of the new algorithm is demonstrated by a numerical example, and the IPSO solution quality and computation efficiency are compared to those of other algorithms.

Simultaneous attainment of energy goals by means of green certificates and emission permits : Jensen, S. G. and Skytte, K. Energy Policy, 2003, 31, (1), 63–71

The efficient reduction of GHG emissions requires appropriate retail pricing of off-peak electricity. However, off-peak electricity for residential consumers is priced at 331% above its marginal cost in the United States as a whole (June 2009). Even for the 1% of residences that are on some form of time-of-use (TOU) rate schedule, the off-peak rate is almost three times higher than the marginal cost. A barrier to marginal-cost based TOU rates is that less than 9% of U.S. households have the “smart” meters in place that can measure and record the time of consumption. Policies should be put in place to achieve full deployment. Another important barrier is consumer concern about TOU rate design. Two TOU rate designs (baseline and two-part tariff) are described that utilize marginal-cost based rates, ensure appropriate cost recovery, and minimize bill changes from current rate structures. A final barrier is to get residences on to these rates. Should a marginal-cost based TOU rate design remain an alternative for which residences could “opt-in,” or become the default choice, or become mandatory? Time-invariant rates are a historical anachronism that subsidize very costly peak-period consumption and penalize off-peak usage to our environmental detriment. They should be phased out.

Optimal Contract Capacities for Time-of-Use Rate Industrial Customers Using Stochastic Search Algorithms

This paper presents two stochastic search algorithms for optimizing the contract capacities of time-of-use (TOU) rate industrial customers. The proposed genetic algorithm (GA) and evolutionary algorithm (EA) are used to search the optimal contract capacities for the TOU rate customers to minimize the summation of demand and penalty charges. Because of the global search capabilities of the GA and EA, the proposed algorithms can optimize the solutions of the complicated, nondifferentiable, optimal contract capacity problem. The proposed algorithms have been tested on a three-section TOU rate industrial customer of Taipower system and are compared with the existing method. The test results demonstrate that the proposed algorithms can efficiently optimize the contract capacities for TOU rate customers.

The Hopkinson tariff alternative to TOU rates in the Israel Electric Corporation

AbstractThis paper determines three alternative Hopkinson tariffs to replace the Israel Electric Corporation's time‐of‐use (TOU) energy rate. The first apportions any system residual revenue requirement between customer classes, based on their respective historic peak demands. The second collects the same revenue as the current TOU rates. The third allocates generation revenue requirements for base‐load and peaking generation plants in proportion to the base‐load and peak‐period energy consumption of each class, and allocates transmission and distribution revenue requirements in proportion to the connected load of each class. We show that a Hopkinson tariff with demand subscription is an attractive alternative to TOU rates, especially when quantity rationing is essential to maintaining a balance between the provision of energy and the demand for it. Copyright © 2002 John Wiley & Sons, Ltd.

Application of evolutionary programming to optimal operational strategy cogeneration system under time-of-use rates

This paper presents the application of Evolutionary Programming (EP) to optimal operational strategy of cogeneration systems under Time-of-Use (TOU) rate. The fuel consumption and steam generation will first be measured and the Input–Output (I/O) curve derived using the regression method. The operational model developed also considers the connection of the cogeneration system with the utility company in terms of TOU rate and various fuel consumptions. EP was adopted to decide the optimal fuel dispatch, steam output of boiler, and generation output subjective to satisfying all the operation constraints. The Newton–Raphson based method has been implemented to show that EP does have the tendency of getting the global optimum. The proposed methodology could provide a practical model for both the utility company and the cogeneration industry to follow.

Smart meter, customer choice and profitable time-of-use rate option

We describe the results of a time-of-use (TOU) rate option experiment which demonstrates that offering a TOU option can be profitable to a utility. The option's profitability is attributable to: (1) smart meters; (2) large price differentials between TOU periods that minimize the adverse selection problem of free-riders; and (3) the success of marketing efforts that enhance customer acceptance. This finding refutes the common belief that rate options are necessarily unprofitable to a utility and unwanted by small users. We explore the significance and relevance of our findings in the emerging world or retail access. TOU rate options will continue to be useful to unregulated energy suppliers, regulated wires companies and electricity consumers.

Residential response to voluntary time-of-use electricity rates

The response of residential households to voluntary Time-of-Use (TOU) electricity rates is estimated using data from a recent experiment at Midwest Power Systems of Iowa. The study's design allows us to examine both the participation decision and the customer's load pattern changes once the TOU rate structure was in effect. Substitution elasticities between on-peak and off-peak electricity usage are estimated and compared to those obtained in earlier mandatory programs, indicating whether program volunteers are more responsive to TOU pricing than the typical household. Attitudinal questionnaires allow us to examine the role of usage perceptions in program participation.

Optimal load clipping with time of use rates

We present four heuristic algorithms and one suboptimal method based on dynamic programming for limiting the overload in electricity consumption. The dynamic successive programming method has developed to work with “time of use rates”, i.e., hourly buying and selling rates of electricity. Our dynamic programming method optimizes one load at a time and uses states sparingly. Gained time savings are 50–90%, depending on the difficulty in the clipping situation, compared to dynamic programming methods not using state saving. The heuristic methods are still very much faster than the methods based on dynamic programming. Tests show that these algorithms are well suited for their purpose.

The Bias in Price Elasticity Estimates Under Separability Between Electricity and Labor in Studies of Time-of-Use Electricity

Most time-of-use(TOU) studies of electricity use in the business sector have found little overall response, as measured by price elasticities, to TOU rates. These studies employed the assumption of weak separability between electricity and all other inputs. Here, we use the generalized Leontief cost function to show that when labor is included in the estimation, the electricity price elasticities are larger, in absolute values, than when labor is erroneously excluded. This result is demonstrated with data on electricity and labor for about 400 Israeli business customers. We also show that the omission of labor from the estimation may cause serious underestimation of the net welfare gains that result from changing a flat electricity price to a TOU rate.

Time-of-use rates vs. Hopkinson tariffs redux: An analysis of the choice of rate structures in a regulated electricity distribution company

Recent proposals to restructure the electricity industry in North America may effect the disintegration of a vertically integrated company into several smaller entities, including distribution companies (DISCOs). We explore whether time-of-use (TOU) pricing or a Hopkinson tariff would be more suitable for a regulated DISCO. Focusing on the economic efficiency of these alternative rate structures, we argue that a Hopkinson tariff with demand subscription is superior to TOU rates, as it can better handle the limited load diversity of local transmission and distribution (TD) demands made on the contemporary DISCO, while finessing the problem of endogenous marginal costs of local TD capacity.

Minimal Adjustment Costs and the Optimal Choice of Inputs Under Time-of-Use Electricity Rates

In Time-of-Use(TOU) pricing schemes, utilities charge rates that depend on the time of day and the season of the year at which electricity is used. Estimates of the effects of TOU rates on business customers in the U.S. and Israel demonstrate that most firms do not appear to respond at all to newly introduced TOU rates, but those that do respond make substantial adjustments. In this paper we show that adjustment costs associated with changing the level of employment can explain the observed pattern of behavior in the U.S. and Israel. We apply our model to large industrial firms in Israel and show that it predicts their actual responses to TOU rates quite well.

The impacts of optional time-of-use prices: a case study

We examine customers' time-of-use (TOU) demand for electricity and their choice between standard and TOU rate schedules. We specify an econometric model in which the customer's demand curves determine the customer's choice of rate schedule. We estimate the model on data from Pacific Gas and Electric Company's experiment with optional TOU prices in the residential sector. With the model, we compare the TOU consumption and price elasticities of customers who chose TOU rates with those who chose standard rates. We also estimate the impact of the TOU rates on the utility's revenues and costs. The analysis suggests that all but one of the TOU rates offered under PG and E's experiment decreased PG and E's profits and hence contributed to higher general rate levels. The model can be used, however, to design optional TOU rates that increase profits and lower general rate levels.