Residential Electricity Rates Research Articles

Performance Improvement of Industrial Gas Turbine for Power Augmentation in the Nigeria Oil and Gas Sector

This paper provides a comprehensive overview of the electricity supply situation in Nigeria, focusing specifically on enhancing the performance of industrial gas turbines, GE GT13E2 (Afam Power Plant owned by FIPL) in Port Harcourt. The study encompasses two primary aspects. Firstly, it involves an examination of the nominal operating conditions of a combined cycle system and explores their dynamic performance through advanced simulations. Secondly, the research introduces a supplementary burner into the combined system and conducts a comparative analysis, considering factors such as system efficiency and power output. The power plant configurations are simulated using Gasturb14. The analysis is carried out by establishing the maximum attainable temperature in the Heat Recovery Steam Generator (HRSG), which determines the number of stages of supplementary firing that can be implemented. The results presented in this paper unveil the substantial potential for power generation with the addition of supplementary burners, indicating a remarkable increase in power output, yielding approximately 187.444 MW. However, this significant boost in power generation comes with an associated trade-off, wherein the overall system efficiency experiences a reduction. From an economic perspective, the additional power generated by the afterburner translates directly into increased revenue from electricity sales. Considering the average residential electricity rate in the U.S. as of February 2023, the calculated additional revenue from the afterburner amounted to approximately $25,641.58 per hour.

To adopt rooftop solar or not along with electric vehicles? Exploring the factors influencing Co-adoption decisions among electric vehicle owners in California

Co-adoption of electric vehicles (EV) and photovoltaic (PV) technology can boost the environmental benefits of the two “green” technologies for society as well as the cost-saving benefits for co-adopters. This study contributes to the literature on this topic by investigating the factors influencing the co-adoption decision among EV owners in California, a leading market for the two complementary technologies. Analyzing data from a cohort survey of EV owners in California, using statistical analyses and logistic regression, we find that there are differences between co-adopters and EV-only households in terms of sociodemographic characteristics like dwelling type, income, and household size; economic factors like residential electricity rate plan; EV type, and electric range; and access to charging capabilities at home and work. Most of these factors also influence the intention of current only EV-owners to adopt PV or not in the future. These findings raise important policy questions regarding incentive needs to improve affordability and address equity issues as well as the need for pricing mechanisms at the utility level and by charging service providers to encourage co-adoption among EV owners.

Do Two Electricity Pricing Wrongs Make a Right? Cost Recovery, Externalities, and Efficiency

Economists favor pricing pollution in part so that consumers face the full social marginal cost (SMC) of goods and services. But even absent externalities, retail electricity prices typically exceed private marginal cost, due to a utility’s need to cover average costs. Furthermore, the SMC of electricity can fluctuate widely hour-to-hour, while retail prices do not. We show that residential electricity rates exceed average SMC in most of the US, but there is large geographic and temporal variation. This finding has important implications for pass-through of pollution costs, as well as for policies promoting dynamic pricing, alternative energy, and reduced electricity consumption. (JEL D62, L94, L98, Q42, Q53)

The changing effectiveness of financial incentives: Theory and evidence from residential solar rebate programs in California

Financial incentives, such as rebate programs, are widely used to promote the adoption of residential solar photovoltaic systems. This paper studies the changing effectiveness of rebate programs as the solar market evolves. We develop a theoretical model to first characterize individual treatment effects then aggregate them to regional effect, and hypothesize that the aggregate treatment effect of rebates first increases and then decreases with declining costs and increasing net metering rate. We empirically test our hypotheses by estimating the treatment effect of rebate rate in California from 2006 to 2017 and its interaction terms with installation cost and residential electricity rate. Results confirm our hypotheses and identify an installation cost of $8.84/W and a residential electricity rate of 22.36c/kWh as the turning points where rebate impacts start to decline. Our findings suggest that front-loaded rebate rate design can be an effective and efficient tool at promoting residential solar adoption.

Residential Electricity Rate Plans and Their Selections Based on Statistical Learning

Demand response (DR) is one of the major benefits that utility companies can derive from the advanced metering infrastructure (AMI). In particular, the dynamic rate plan with DR is attracting attention as an electricity rate system suitable for the future power environment. In order for electricity consumers to select an appropriate electricity rate plan, it is necessary to provide information such as whether electricity bills are reduced by the plan and the estimated amount of electricity bill savings. In this paper, we first comparatively analyze the current progressive rate plan and a dynamic rate plan of the time-of-use (TOU). We next propose several prediction methods for households to provide information on whether the electricity bill amount can be reduced in advance when changing to the TOU rate plan from the progressive rate plan by using only the current monthly electricity usages and bills. In order to develop three different prediction methods based on statistical learning, we use the support vector machine, linear regression, and deep neural network techniques. As a ground truth training sequence, we use hourly electricity usages and bills obtained from ten apartment complexes through AMI, and an apartment complex is used for testing the designed methods. The decision accuracy for the test complex was more than 0.98 and the root mean square error of the saving prediction was 1.7%.

Electricity Rates and the Funding of Municipal Broadband Networks: An Empirical Analysis

Most Government-Owned Broadband Networks (“GONs”) are typically subsidized by city finances in some way to stay financially viable. In cases where a city has both a GON and a government-run electric utility, a popular method of cross subsidization is to shift costs of the GON onto the captive ratepayers of the municipally operated electric utility. This shift of broadband costs to the electric utility can be expected to increase electricity rates. In this BULLETIN, a Differences-in-Differences approach quantifies the effect on electric rates from a utility-funded GON. A GON increases residential and commercial electricity rates by about 5% when the utility funded model is used, but rates are unaffected for alternative funding arrangements.

Determining the Relationship between Residential Electricity Consumption and Factors: Case of Seoul

This paper aims to determine the relationship between residential electricity consumption and other factors by analyzing the correlation and multiple regression between residential electricity consumption and three variables which are known as the factors affecting residential electricity consumption. We used the electricity consumption, income, number of household members, and age of 25 autonomous districts in Seoul as data for analysis, assuming that the socio-demographic characteristics vary from district to district in Seoul. The results showed that the electricity consumption and the three variables each had a significant correlation. However, multiple regression analysis results showed that the income and the number of household members have an effect on electricity consumption, but the average age is not a factor influencing electricity consumption. The results of this study would be useful for understanding the characteristics of urban residential electricity consumption in situations where the needs for an increase in residential electricity rates are continuously coming out.

The impact of wildfires and beneficial electrification on electricity rates in PG&E’s service territory

Building and transport electrification, an essential strategy to California’s carbon reduction goals, requires affordable electricity for customer adoption. We estimate the costs borne by the electric sector for its involvement in the 2017 and 2018 wildfires in Northern California to be significant and cause residential electric rates in PG&E territory to increase from 23 cents/kWh (2018) to 42 cents/kWh (2030). This rate increase could be limited to 35 cents/kWh through proactive transportation and building electrification.

The Efficiency and Distributional Effects of Alternative Residential Electricity Rate Designs

Electricity tariffs typically charge residential users a volumetric rate that covers the bulk of energy, transmission, and distribution costs. The resulting prices, charged per unit of electricity consumed, do not reflect marginal costs and vary little across time and space. The emergence of distributed energy resources—such as solar photovoltaics and energy storage—has sparked interest among regulators and utilities in reforming electricity tariffs to enable more efficient utilization of these resources. The economic pressure to redesign electricity rates is countered by concerns of how more efficient rate structures might impact different socioeconomic groups. We analyze the bill impacts of alternative rate plans using interval metering data for more than 100,000 customers in the Chicago, Illinois area. We combine these data with granular Census data to assess the incidence of bill changes across different socioeconomic groups. We find that low-income customers would face bill increases on average in a transition to more economically efficient electricity tariffs. However, we demonstrate that simple changes to fixed charges in two-part tariffs can mitigate these disparities while preserving all, or the vast majority, of the efficiency gains. These designs rely exclusively on observable information and could be replicated by utilities in many geographies across the U.S.

A simulation study for residential electricity user behavior under dynamic variable pricing with demand charge

ABSTRACTAttempting to increase energy efficiency and improve system load factors in an electricity distribution system, Demand Response (DR) has long been proposed and implemented as a form of load management. Various pricing structures incentivizing consumers to shift energy consumption from on-peak to off-peak periods are evident in this field. Most DR methods currently used in practice belong to static variable pricing (e.g., Time of Use, Critical Peak Pricing) and the impact of such tariffs has been well established. However, dynamic variable pricing in general is less studied and much less practiced in the field, due to the lack of understanding of consumer behavior in response to price uncertainty. In this article, we study a novel dynamic variable pricing scheme that uses the coincident demand charge to reduce load consumption during peak events. We employ a multi-attribute utility function and model predictive control to simulate consumer behavior of utility maximization in home energy consumption. We use a conditional Markov chain to model and predict the system peak. Effects of the proposed residential electricity rate based on coincident demand charge are compared with other pricing schemes through simulation validated with real-world residential load profiles. Finally, we extend the simulations to study the impact of integrating renewable solar production in a DR program.

Price volatility and residential electricity decisions: Experimental evidence on the convergence of energy generating source

The recent trend in most developed countries has been toward greater reliance on renewable or “green” energy sources. This paper investigates how price volatility in residential electricity rates impacts consumers' preferences for green power. Using a choice-based experiment, we present respondents with choice scenarios that feature two electric utility plans: (i) a conventional plan where electricity is generated from either coal or natural gas, and (ii) a green plan where electricity is generated renewably from either wind or solar. We then systematically vary the monthly price volatility of each plan across choice scenarios. Our results suggest that price volatility in monthly rates significantly impacts respondents' plan choices and, specifically, their decision to adopt the green power plan. In particular, increased volatility in the green power plan reduces the likelihood of respondents choosing the green plan, while increased volatility in the conventional plan increases the likelihood of respondents choosing the green plan. Moreover, the documented effects of price volatility are robust across different price premiums for the green power plan.

The distributional impacts of residential demand charges

Demand charges have recently emerged as an important feature in many proposals to reform residential electricity rates. Relying on load and income data for more than 1,000 utility customers, the authors provide an assessment of the impact this rate design could have on residential customer bills and examine the potential for home energy storage to enhance bill savings. One encouraging finding: demand charges do not disproportionately impact low-income customers relative to the rest of the sample.

Distributed Generation: How Green? How Efficient? How Well-Priced?

A close look at the details of state and local programs in support of distributed generation raises some questions about the whether the promotion of green DG actually advances environmental objectives, especially when it takes place in a context of ‘net metering’ and flat residential electricity rates. It is time to reassess where we are going and to calibrate our pricing and policies to make certain that our efforts are carrying us in the right direction.

Restructuring and the retail residential market for power in Pennsylvania

In January 2010 electricity retail residential rate caps expired in a large part of Pennsylvania, allowing consumers to shop for electricity in the retail market. In this paper we employ customer-level data from the relevant territory to analyze what residential customer and community characteristics impacted the decision of whether or not to switch to an alternative electricity provider, and when to make the switch.Results show that customers with higher usage levels (especially around the time of the program's introduction), electric heating, and those living in more urban and more educated communities with lower unemployment rates and higher median household incomes were both more likely to switch, and more likely to do so faster. Lower switching rates and a slower switching response was observed from customers with more variable month to month usage (perhaps this made them unsure of future benefits from switching), those on alternative residential electricity rates (time-of-day and thermal storage programs), and those new to the relevant area (perhaps due to lack of information about the residential choice program).Critics of retail electricity competition have suggested that it disadvantages poor and elderly ratepayers. Our results do not support this contention. Customers living in communities with higher poverty rates were actually more likely to switch (and do so faster) than middle-income consumers. Communities with higher shares of senior population were not found to have lower switching rates from younger communities.

Did residential electricity rates fall after retail competition? A dynamic panel analysis

A key selling point for the restructuring of electricity markets was the promise of lower prices. There is not much consensus in earlier studies on the effects of electricity deregulation in the U.S., particularly for residential customers. Part of the reason for not finding a consistent link with deregulation and lower prices was that the removal of transitional price caps led to higher prices. In addition, the timing of the removal of price caps coincided with rising fuel prices, which were passed on to consumers in a competitive market. Using a dynamic panel model, we analyze the effect of participation rates, fuel costs, market size, a rate cap and switch to competition for 16 states and the District of Columbia. We find that an increase in participation rates, price controls, a larger market, and high shares of hydro in electricity generation lower retail prices, while increases in natural gas and coal prices increase rates. We also find that retail competition makes the market more efficient by lowering the markup of retail prices over wholesale costs. The effects of a competitive retail electricity market are mixed across states, but generally appear to lower prices in states with high participation rates.

Did Residential Electricity Rates Fall After Retail Competition? A Dynamic Panel Analysis

A key selling point for the restructuring of electricity markets was the promise of lower prices, that competition among independent power suppliers would lower electricity prices to retail customers. There is not much consensus in earlier studies on the effects of electricity deregulation, particularly for residential customers. Part of the reason for not finding a consistent link with deregulation and lower prices was that the removal of the transitional price caps led to higher prices. In addition, the timing of the removal of price caps coincided with rising fuel prices, which were passed on to consumers in a competitive market. Using a dynamic panel model, we analyze the effect of participation rates, fuel costs, market size, a rate cap and a switch to competition for 16 states and the District of Columbia. We find that an increase in participation rates, price controls, a larger market, and high shares of hydro in electricity generation lower retail prices, while increases in natural gas and coal prices increase rates. The effects of a competitive retail electricity market are mixed across states, but generally appear to lower prices in states with high participation and raise prices in states that have little customer participation.

Change in consumer sensitivity to electricity prices in response to retail deregulation: A panel empirical analysis of the residential demand for electricity in the United States

About ten years have passed since the deregulation of the U.S. retail electricity market, and it is now generally accepted that the available data is adequate to quantitatively assess and compare conditions before and after deregulation. This study, therefore, estimates the changes in price elasticity in the residential electricity market to examine the changes, if any, in household sensitivity (as a result of retail electricity market deregulation policies) to residential electricity rates. Specifically, six types of panel data are prepared, based on three cross-sections—all states (except for Alaska and Hawaii) and the District of Columbia, deregulated states, and non-deregulated states—and two time series—the period before deregulation and the period after deregulation. The panel empirical analysis techniques are used to determine whether or not the variables are stationary, and to estimate price elasticity. We find that there is no substantial difference in the price elasticity between deregulated and non-deregulated states for both periods—before deregulation and after deregulation. Thus, it can be said that the deregulation of the retail electricity market has not made consumers more sensitive to electricity rates and that retail deregulation policies are not the cause of price elasticity differences between deregulated and non-deregulated states.

"We Can Wait. We Should Wait." Eugene's Nuclear Power Controversy, 1968-1970

In November 1968, voters in Eugene, Oregon, overwhelmingly approved a measure allowing their municipal electric utility to sell bonds to fund construction of a nuclear power plant. Eighteen months later, on May 26, 1970, citizens again went to the polls; this time, however, they voted to impose a four-year moratorium on their utility's nuclear construction plans. Why this rapid shift? What had changed in the intervening months to convert general approval to rejection of nuclear power plans? The answer lies in an examination of national, regional, and local developments. Eugene's aborted affair with nuclear energy came near the end of a long period of American energy abundance. Domestic crude petroleum at about $3.00 a barrel, imports at about $1.25 a barrel, seemingly inexhaustible supplies of coal, and convenient natural gas resources had fueled the nation's post-World War II boom. The spread of electricity to rural America had been followed by the rapid intensification of household energy use. Between 1961 and 1970, while the nation's average residential electricity rates declined by about fifteen percent, the average home's monthly usage grew about eighty-three percent.'

Modelling alternative residential peak-load electricity rate structures

We specify a model of consumer behavior that permits the simultaneous estimation of effects of time-of-use rates having a demand charge, differential energy charges, and any combination of such charges. The model employs a flexible functional form and thus does not impose restrictions on substitution possibilities among types of usage. We estimate the model using data from the Wisconsin Residential Electricity Pricing Experiment for eight system peak days. The most surprising finding of our empirical application is that the two types of time-of-use rates employed in the Wisconsin experiment have similar effects on patterns of household electricity usage.

Energy savings and cost-effectiveness of heat exchanger use as an indoor air quality mitigation measure in the BPA weatherization program

The Bonneville Power Administration (BPA) has proposed a ten year program to encourage the weatherization of electrically heated homes in the Pacific Northwest. The purpose of this program is to reduce residential electrical energy demand for space heating. If air infiltration rates are reduced by employing house tightening measures, indoor air quality mitigation measures may be required in residences with significant sources of indoor air contaminants. The use of residential air-to-air heat exchangers has been proposed as a possible strategy to assure that indoor air quality is not substantially degraded by house tightening. We examine the energy impact and cost effectiveness of heat exchanger utilization in tightened homes in the BPA region. Significant energy savings are predicted if homes are tightened and heat exchangers are utilized. From the homeowner's perspective, the results of our economic analysis indicate that, at the relatively low residential electric rates in the BPA region, the use of heat exchangers in existing homes that are tightened is not economically viable. On the other hand, from the utility perspective, it may be cost effective to use heat exchangers in the weatherization program if the marginal cost to the utility is compared with the cost of conserved energy.