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.     

Estimating the option value of a non-firm electricity tariff

We estimate the option value of a non-firm electricity tariff commonly used by a local distribution company (LDC) in its electricity demand response program. This option value captures the benefit that a LDC enjoys from not serving an end-use load during high-price hours in a wholesale electricity market. It is conservative in that it does not include the cost savings in meeting the LDC's resource adequacy requirement or deferring transmission and distribution (T&D) investments necessary for delivering reliable service. Illustrated by a Northern California example, our two-pronged approach entails (a) a set of summer monthly market price regressions to forecast daily spot price distributions that incorporate uncertainty in natural gas price and weather; and (b) a simulation exercise to quantify the tariff's value under a specific design. The results indicate that a non-firm service tariff can have varying option value estimates that are highly sensitive to the tariff's design, and that an incentive payment based on the option value alone is likely insufficient to attract customer participation in a non-firm service program.     

Estimating the value of wind energy using electricity locational marginal price

There is an increasing interest in adding renewables such as wind to electricity generation portfolios in larger amounts as one response to concern about atmospheric carbon emissions from our energy system and the resulting climate change. Most policies with the aim of promoting renewables (e.g., RPS, FIT) do not explicitly address siting issues, which for wind energy are currently approached as the intersection of wind resource, land control, and transmission factors. This work proposes the use of locational marginal price (LMP), the location and time specific cost of electricity on the wholesale market, to signal locations where generation can address electricity system insufficiency. After an examination of the spatial and temporal behavior of LMP in Michigan over the first two years of wholesale market operation, this work combines LMP with wind speed data to generate a value metric. High value sites in Michigan tend to be sites with higher wind speeds, with the bulk of value accruing in the fall and winter seasons.     

A comparative analysis of the value of pure and hybrid electricity storage

Significant natural gas and electricity price variation and volatility, especially during the past few years, raise questions about understanding the value drivers behind electricity storage. The impact of these drivers for pure storage (such as pumped hydroelectric storage) and compressed air energy storage (CAES) are different and in this paper we explore these differences in operation and net revenue over a variety of timescales. We also consider the arbitrage value that is attainable in practice and explain why simple forecasting techniques based on historical data will generally be less successful for CAES. The breakeven cost of storage and how this can depend on regulatory treatment of storage and market structure is also considered.     

Comparing welfare effects of different regulation schemes: An application to the electricity distribution industry

We compare the welfare effects of different regulation schemes of electricity distribution utilities. The compared regulation schemes are Fixed Price regulation, Cost of Service regulation, Menu of Cost-Contingent Contracts and Simple Menu of Contracts. In our calculations we utilize the information of a firm’s potential to improve cost efficiency. The firm-specific cost information of Finnish electricity distribution utilities is obtained by using various Stochastic Frontier models. Our basic result is that welfare can be improved by changing the Cost of Service regulation scheme to the Menu of Contracts regulation. Welfare also increases in the case of Fixed Price regulation and Simple Menu of Contract regulation. There is however, a significant difference among regulation regimes on how this improved welfare is distributed to consumers and producers.     

Estimating the potential for electricity savings in households

Improving efficiency in the use of energy is an important goal for many nations since end-use energy efficiency can help to reduce CO₂ emissions. Furthermore, since the residential sector in industrialised countries requires around one third of the end-use electricity, it is important for policy makers to estimate the scope for electricity saving in households to reduce electricity consumption by using appropriate steering mechanisms. We estimate the level of technical efficiency in the use of electricity using data from a Swiss household survey. We find an average inefficiency in electricity use by Swiss households of around 20 to 25%. Bottom-up economic-engineering models estimate the potential in Switzerland to be around 15%. In this paper we use a sub-vector input distance frontier function based on economic foundations. Our estimates lie at the upper end of the electricity saving potential estimated by the afore-mentioned economic-engineering approach.     

Estimating the price elasticity of US electricity demand

The use of a single electricity price has been seen as a major shortcoming of econometric models of residential electricity demand. It has been suggested that demand estimation should be based on the full rate schedule. This suggestion is evaluated here by examining demand estimates for 27 investor-owned US utilities over the period 1957–1972. The specification errors resulting from using an average revenue price are measured. It is found that statistically valid demand estimated do not necessarily require information on tariff schedules, but that state-wide aggregates of elasticity may often be inapplicable to individual utilities.     

Performance of the SAC-C satellite electricity storage system

The analysis of telemetry data of the Argentine electricity storage system SAC-C satellite is presented. Diagnostic indicators were established in order to evaluate the in-flight performance of the satellite nickel-hydrogen batteries. The state of charge of the batteries was related to the hydrogen pressure. A predictive analysis allowed us to detect early failure of the electricity storage system.     

Grid-connected renewables,storage and the UK electricity market

This article is mainly a counterpoint to an article by Swift-Hook in the journal of Renewable Energy titled “Grid-connected intermittent renewables are the last to be stored”. It also describes the four main distinct UK markets where electrical energy and services are traded, in order to provide a context for the discussion of renewable energy and energy storage in the UK electricity system. In Swift-Hook’s article it was argued that “grid-connected intermittent renewables like wind energy will never be stored unless nothing else is available” and that “storage is counter-productive for fuel saving”. We, however, find evidence that “grid-connected intermittent renewables” have been, and will continue to be stored when it suits the “UK market” to do so. Furthermore, Swift-Hook’s article neglects the potential wider benefits that storage offers to UK energy policy’s goals, in terms of reduced emissions (when used in conjunction with renewables) and enhanced security of supply.     

Estimating the agricultural demand for electricity in the presence of measurement error in the data

This paper begins by discussing some of the problems frequently encountered in obtaining demand elasticity estimates. To these problems is added that associated with inaccuracy in the measurement of the dependent variable and one or more of the independent variables that impact upon the quantity demanded. Two diagnostics — the regression coefficient bounds and the bias correction factor — are introduced to assess the effect that such a measurement error has on the estimated coefficients of demand relationships. Use of these diagnostics aids in assessing the integrity of the estimates obtained. In considering the demand for electricity for irrigation and the demand for electricity for other (non-irrigation) uses by farmers in the USA, both the quantity demanded and the unit price data available for demand model estimation purposes contain measurement errors. The regression coefficient bounds diagnostic is used to indicate a range over which the true price responsiveness of farmers to changes in energy prices lies. The results suggest that each 1% increase (decrease) in the price of energy will result in between a 0·51 and 0·35% decrease (increase) in the quantity of electricity demanded for irrigation and between a 0·43 and 0·17% decrease (increase) in the quantity of electricity demanded for other uses. The bias correction factor is computed to evaluate the magnitude of the under-estimation of the responsiveness of the quantity of electricity demanded for irrigation and electricity for other uses to a change in the number of acres irrigated and the number of acres planted. For electricity for irrigation, the under-estimation was 14·1% while, for electricity for other uses, it was 13·9%.     

The value of information in electricity investment games

In this paper we look at the assumptions behind a Cournot model of investment in electricity markets. We analyze how information influences investment, looking at the way common knowledge of marginal costs, expectations on the competitors’ marginal costs, expectations on the level and duration of demand, and conjectures on the others’ behavior, influence the value of a project. We expose how the results are highly dependent on the assumptions used, and how the investment Nash–Cournot game with perfect and complete information implies such a degree of coordination between players that the outcome of the game would be classified by any regulation law as collusive behavior. Furthermore, we introduce the concept of Nash Value of Complete Information. As an example we use a stylized model of investment in liberalized electricity markets.     

Estimating short and long-term residential demand for electricity: New evidence from Sri Lanka

This study investigates the short-run dynamics and long-run equilibrium relationship between residential electricity demand and factors influencing demand – per capita income, price of electricity, price of kerosene oil and price of liquefied petroleum gas – using annual data for Sri Lanka for the period, 1960–2007. The study uses unit root, cointegration and error-correction models. The long-run demand elasticities of income, own price and price of kerosene oil (substitute) were estimated to be 0.78, ? 0.62, and 0.14 respectively. The short-run elasticities for the same variables were estimated to be 0.32, ? 0.16 and 0.10 respectively. Liquefied petroleum (LP) gas is a substitute for electricity only in the short-run with an elasticity of 0.09. The main findings of the paper support the following (1) increasing the price of electricity is not the most effective tool to reduce electricity consumption (2) existing subsidies on electricity consumption can be removed without reducing government revenue (3) the long-run income elasticity of demand shows that any future increase in household incomes is likely to significantly increase the demand for electricity and (4) any power generation plans which consider only current per capita consumption and population growth should be revised taking into account the potential future income increases in order to avoid power shortages in the country.     

Estimating the net electricity energy generation and demand using the ant colony optimization approach: Case of Turkey

This paper presents Turkey's net electricity energy generation and demand based on economic indicators. Forecasting model for electricity energy generation and demand is first proposed by the ant colony optimization (ACO) approach. It is multi-agent system in which the behavior of each ant is inspired by the foraging behavior of real ants to solve optimization problem. Ant colony optimization electricity energy estimation (ACOEEE) model is developed using population, gross domestic product (GDP), import and export. All equations proposed here are linear electricity energy generation and demand (linear_ACOEEGE and linear ACOEEDE) and quadratic energy generation and demand (quadratic_ACOEEGE and quadratic ACOEEDE). Quadratic models for both generation and demand provided better fit solution due to the fluctuations of the economic indicators. The ACOEEGE and ACOEEDE models indicate Turkey's net electricity energy generation and demand until 2025 according to three scenarios.     

Multiobjective assessment of distributed energy storage location in electricity networks

This paper presents a methodology to provide information to a decision maker on the associated impacts, both of economic and technical nature, of possible management schemes of storage units for choosing the best location of distributed storage devices, with a multiobjective optimisation approach based on genetic algorithms. The methodology was applied to a case study, a known distribution network model in which the installation of distributed storage units was tested, using lithium-ion batteries. The obtained results show a significant influence of the charging/discharging profile of batteries on the choice of their best location, as well as the relevance that these choices may have for the different network management objectives, for example, for reducing network energy losses or minimising voltage deviations. Results also show a difficult cost-effectiveness of an energy-only service, with the tested systems, both due to capital cost and due to the efficiency of conversion.     

Power system economics : The value of natural gas in electricity generation

The study reported in this paper is concerned with assessing the value of natural gas in power generation. It had previously been assumed that this value is equal to price(s) of displaced fuel(s). A methodology is derived to assess this value in integrated supply systems and results are derived for a hypothetical system. It is shown that the value is system specific and may be equal to, greater than or less than the value of displaced fuel. The methodology and results reported are relevant to the debate on gas parity pricing.     

A novel business model for aggregating the values of electricity storage

Electricity storage is considered as a valuable source of flexibility with applications covering the whole electricity value chain. Most of the existing evaluation methods for electricity storage are conceived for one specific use of the storage, which often leads to the conclusion that the investment on storage does not pay off. However, the value of storage cannot be properly estimated without taking into account the possibility of aggregating the services that storage can offer to different actors. This paper proposes a new business model that allows aggregating multiple revenue streams of electricity storage in a systematic way. The model consists in coordinating a series of auctions in which the right to utilize the storage unit is auctioned upon different time horizons. In the mean time, non-conflicting usage of storage by the actors in these different auctions is ensured. The functioning of the model is demonstrated by a case study. The results show that a storage unit can achieve higher return on investment in the manner proposed in the business model.     

Economic analysis of the seasonal storage of electricity with liquid organic hydrides

A future alternative for generating winter electricity is the seasonal storage of surplus summer electricity in the form of chemically bound hydrogen in liquid organic hydrocarbons using the MTH-system (Methylcyclohexane–Toluene–Hydrogen). This paper compares the economics of the MTH-system with the conventional production of electricity from fossil fuel sources.

Based on numerical modelling of the individual plants, simulations of several design alternatives of the MTH-system were performed for 1000 GWh of stored summer electricity and 80 MW output. The overall efficiencies η_tot and the economic results of these simulations are η_tot=0.40 and 0.26 $/kWh for the MTH-SOFC system alternative, η_tot=0.33 and 0.30 $/kWh for the MTH-MCFC and η_tot=0.25 and 0.36 $/kWh for the MTH-system with gas and steam turbines.

Compared with the cost of electricity production using fossil fuels (0.05–0.1 $/kWh), the electricity produced by the MTH-system is expensive. Therefore an economic comparison including an assumed carbon tax was made to account for a possible scarcity of energy or the environmental impact due to the use of fossil energy resources. It concludes that the MTH-system is not competitive for the levels of carbon tax under discussion, but compares with options for providing electricity from new renewables.

Due to the disparities in economics and carbon taxes, a best case study of the MTH-system was made to reduce its economic disadvantages. This results in a maximum efficiency of the MTH-system of 0.48 with corresponding winter electricity costs of 0.17 $/kWh.     

Estimating the health damage costs of syrian electricity generation system using impact pathway approach

Based on the simplified impact pathway approach the environmental impacts from airborne pollutant emissions of Syrian electricity generation system have been assessed and the associated external damage costs to human health have been evaluated. The obtained results indicate that the environmental impacts can add considerable external cost to the typical generation cost. The estimated externalities vary between 2.5 and 0.07 US-cents per generated kWh for heavy fuel oil and NG fired power plants respectively. For the fuel oil fired power plants the resulting external cost, arise mainly from Sulphates impact, amounts to about 25% of the present generation costs. These results indicate the advantage of NG fired power plants as clean generation technology and the necessity of supplying oil fired power plants with SO₂ emission reduction technologies.