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A fundamental policy question for distributed energy resources (DER) is whether they create system benefits shared by all utility customers in addition to being profitable for the installing customer. This question has received considerable attention in “value of DER” and net metering reform proceedings for behind-the-meter solar photovoltaics in recent years. Commercial customer-sited lithium-ion batteries with a primary use case of demand charge management are forecast to greatly increase in the coming decade due to falling storage costs, making comparison of their customer and system benefits a timely topic in DER valuation. We conduct an overview of the system benefits of standalone commercial customer-sited storage on United States’ electric tariffs and find system benefits will not be realized for many standalone commercial customer-sited storage installations in the absence of incentives for storage dispatch during the top 50–100 annual hours that drive grid infrastructure investment. Regulatory implementation of default peak pricing during a small subset of annual hours for customer-sited storage can realize additional system benefits and offer Pareto improvement. Additional transparency in regulatory estimates of these system benefits helps catalyze longer-term visions for increased competition at the retail level using DERs.

Competitive electricity markets can procure reserve generation through a market in which the demand for reserves is administratively established. A downward sloping or stepped administrative demand curve is commonly termed an operating reserve demand curve (ORDC). We propose a dynamic formulation of an ORDC with generator forced outage probabilities conditional on ambient temperature to implement scarcity pricing in a wholesale electricity market. This formulation improves on common existing methods used by wholesale market operators to articulate ORDCs by explicitly accounting for a large source of observed variability in generator forced outages, whereby for a fixed load, more reserves are required during times of extreme heat and cold to maintain a constant risk of reserve shortage. Such a dynamic ORDC increases social welfare by $17.1 million compared to current practice in the PJM Interconnection during a high load week in a welfare-maximizing electricity market with co-optimized procurement of energy and reserves. A dynamic ORDC increases reserve prices under scarcity conditions, but has minimal effects on total market payments. The results are directly relevant to the modeled two-settlement electricity market in PJM, which is currently undergoing enhancements to its ORDC.

Using 2012–2018 power plant failure data from the North American Electric Reliability Corporation, we examine how many fuel shortage failures at gas power plants were caused by physical interruptions of gas flow as opposed to operational procedures on the pipeline network, such as gas curtailment priority. We find that physical disruptions of the pipeline network account for no more than 5% of the MWh lost to fuel shortages over the six years we examined. Gas shortages at generators have caused correlated failures of power plants with both firm and non-firm fuel arrangements. Unsurprisingly, plants using the spot market or interruptible pipeline contracts for their fuel were somewhat more likely to experience fuel shortages than those with firm contracts. We identify regions of the Midwest and Mid-Atlantic where power plants with non-firm fuel arrangements may have avoided fuel shortage outages if they had obtained firm pipeline contracts. The volume of gas needed by power plants to fuel the lost MWh in those regions was only a small fraction of the total volume delivered to potentially non-essential commercial and industrial pipeline customers in those regions and modest prices there at the times when power plants failed indicate gas was available.

We investigate the resource adequacy requirements of the PJM Interconnection, and the sensitivity of capacity procurement decisions to the choice of reliability metric used to measure resource adequacy. Assuming that plants fail independently, we find that PJM's 2010 reserve margin of 20.5% was sufficient to achieve the stated reliability standard of one loss of load event per ten years, with 0.012 expected loss of load events per year. PJM could reduce reserve margins to 13% and still achieve adequate levels of reliability as measured by the 2.4 Loss of Load Hours metric and the 0.001% Unserved Energy metric, which are used by other U.S. and international systems. A reserve margin of 13–15% would minimize long-run system costs. Reducing reserve margins from 20.5% to 13% in 2010 would have reduced PJM's capacity procurement by 11 GW, the same amount of coal capacity that PJM has identified as at high risk of retirement. We also investigate the risk posed by correlated failures among generators, a risk traditionally not modeled by system planners. We illustrate that three types of correlated failures may increase outage risks: natural gas supply disruptions, reduced reliability among generators during winter months, and the simultaneous shutdown of multiple nuclear generators for regulatory reasons.

We assess the ability of distributed solar to defer distribution capacity projects in a typical low load growth utility in the Northeast USA, PECO. We find that targeted placement can increase the deferral value of solar up to fourfold, but that deferrable projects are rare. In our baseline scenario, we find a 5% solar energy penetration with Net Energy Metering rolled out from 2020 to 2030 would increase rates by 0.8% over a 20-year horizon and generate just $1 MM in net present deferral value. This estimate assumes untargeted placement of solar, a low effective capacity (i.e. the reduction in peak load relative to solar's nominal capacity), a 1% growth rate, and 1% of PECO's distribution yearly capex budget that is deferrable. A higher effective capacity (e.g. from coupling energy storage with solar) and targeted placement could generate a net $8 MM of value over the same horizon, but the rate increase is mostly unaffected. We recommend the use of targeted solar placement in utility planning processes. Compared to untargeted placement, targeted placement can increase the total deferral value fourfold, but the effect on rates is small for PECO because few capacity deferral opportunities exist.

We develop a metric to quantify the sub-hourly variability cost of individual wind plants and show its use in valuing reductions in wind power variability. Our method partitions wind energy into hourly and sub-hourly components and uses corresponding market prices to determine variability costs. We use publically available 15-min ERCOT data, although the method developed can be applied to higher time resolution data if available. We do not estimate uncertainty costs though our metric can separate integration costs into variability and uncertainty components. The mean variability costs arising from 15-min to 1-h variations (termed load following) for 20 ERCOT wind plants was $8.73±$1.26 per MWh in 2008 and $3.90±$0.52 per MWh in 2009. Load following variability costs decrease as capacity factors increase, indicating wind plants sited in locations with good wind resources cost a system less to integrate. Twenty interconnected wind plants had a variability cost of $4.35 per MWh in 2008. The marginal benefit of interconnecting another wind plant diminishes rapidly: it is less than $3.43 per MWh for systems with 2 wind plants already interconnected, less than $0.7 per MWh for 4–7 wind plants, and less than $0.2 per MWh for 8 or more wind plants.

A reconfigurable network can change its topology by opening and closing switches on power lines. We use real wind, solar, load, and cost data and a model of a reconfigurable distribution grid to show that reconfiguration allows a grid operator to reduce operational losses as well as to accept more intermittent renewable generation than a static configuration can. Net present value analysis of automated switch technology shows that the return on investment is negative for this test network when considering only loss reduction, but that the investment is attractive under certain conditions when reconfiguration is used to minimize curtailment.

We investigate the economic viability of coupling a wind farm with compressed air energy storage (CAES) to participate in the day-ahead electricity market at a time when renewable portfolio standards are not binding and wind competes freely in the marketplace. In our model, the CAES is used to reduce the risk of committing uncertain quantities of wind energy and to shift dispatch of wind generation to high price periods. Other sources of revenue (capacity markets, ancillary services, price arbitrage) are not included in the analysis. We present a model to calculate profit maximizing day-ahead dispatch schedules based on wind forecasts. Annual profits are determined with dispatch schedules and actual wind generation values. We find that annual income for the modeled wind–CAES system would not cover annualized capital costs using market prices from the years 2006 to 2009. We also estimate market prices with a carbon price of $20 and $50 per tonne CO2 and find that revenue would still not cover the capital costs. The implied cost per tonne of avoided CO2 to make a wind–CAES profitable from trading on the day-ahead market is roughly $100, with large variability due to electric power prices.

Compressed air energy storage (CAES) could be paired with a wind farm to provide firm, dispatchable baseload power, or serve as a peaking plant and capture upswings in electricity prices. We present a firm-level engineering-economic analysis of a wind/CAES system with a wind farm in central Texas, load in either Dallas or Houston, and a CAES plant whose location is profit-optimized. With 2008 hourly prices and load in Houston, the economically optimal CAES expander capacity is unrealistically large – 24 GW – and dispatches for only a few hours per week when prices are highest; a price cap and capacity payment likewise results in a large (17 GW) profit-maximizing CAES expander. Under all other scenarios considered the CAES plant is unprofitable. Using 2008 data, a baseload wind/CAES system is less profitable than a natural gas combined cycle (NGCC) plant at carbon prices less than $56/tCO 2 ($15/MMBTU gas) to $230/tCO 2 ($5/MMBTU gas). Entering regulation markets raises profit only slightly. Social benefits of CAES paired with wind include avoided construction of new generation capacity, improved air quality during peak times, and increased economic surplus, but may not outweigh the private cost of the CAES system nor justify a subsidy.

We present the first frequency-dependent analyses of the geographic smoothing of wind power’s variability, analyzing the interconnected measured output of 20 wind plants in Texas. Reductions in variability occur at frequencies corresponding to times shorter than � 24 h and are quantified by measuring the departure from a Kolmogorov spectrum. At a frequency of 2.8 � 10 � 4 Hz (corresponding to 1 h), an 87% reduction of the variability of a single wind plant is obtained by interconnecting 4 wind plants. Interconnecting the remaining 16 wind plants produces only an additional 8% reduction. We use step change analyses and correlation coefficients to compare our results with previous studies, finding that wind power ramps up faster than it ramps down for each of the step change intervals analyzed and that correlation between the power output of wind plants 200 km away is half that of co-located wind plants. To examine variability at very low frequencies, we estimate yearly wind energy production in the Great Plains region of the United States from automated wind observations at airports covering 36 years. The estimated wind power has significant inter-annual variability and the severity of wind drought years is estimated to be about half that observed nationally for hydroelectric power.

Using data from the North American Electric Reliability Council (NERC) for 1984–2006, we find several trends. We find that the frequency of large blackouts in the United States has not decreased over time, that there is a statistically significant increase in blackout frequency during peak hours of the day and during late summer and mid-winter months (although non-storm-related risk is nearly constant through the year) and that there is strong statistical support for the previously observed power-law statistical relationship between blackout size and frequency. We do not find that blackout sizes and blackout durations are significantly correlated. These trends hold even after controlling for increasing demand and population and after eliminating small events, for which the data may be skewed by spotty reporting. Trends in blackout occurrences, such as those observed in the North American data, have important implications for those who make investment and policy decisions in the electricity industry. We provide a number of examples that illustrate how these trends can inform benefit-cost analysis calculations. Also, following procedures used in natural disaster planning we use the observed statistical trends to calculate the size of the 100-year blackout, which for North America is 186,000 MW.

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.

The location of a new electric power generation system with carbon capture and sequestration (CCS) affects the profitability of the facility and determines the amount of infrastructure required to connect the plant to the larger world. Using a probabilistic analysis, we examine where a profit-maximizing power producer would locate a new generator with carbon capture in relation to a fuel source, electric load, and CO 2 sequestration site. Based on models of costs for transmission lines, CO 2 pipelines, and fuel transportation, we find that it is always preferable to locate a CCS power facility nearest the electric load, reducing the losses and costs of bulk electricity transmission. This result suggests that a power system with significant amounts of CCS requires a very large CO 2 pipeline infrastructure.

Unlike markets for storable commodities, electricity markets depend on the real-time balance of supply and demand. Although much of the present-day grid operates effectively without storage, cost-effective ways of storing electrical energy can help make the grid more efficient and reliable. We investigate the economics of two emerging electric energy storage (EES) technologies: sodium sulfur batteries and flywheel energy storage systems in New York state's electricity market. The analysis indicates that there is a strong economic case for EES installations in the New York City region for applications such as energy arbitrage, and that significant opportunities exist throughout New York state for regulation services. Benefits from deferral of system upgrades may be important in the decision to deploy EES. Market barriers currently make it difficult for energy-limited EES such as flywheels to receive revenue for voltage regulation. Charging efficiency is more important to the economics of EES in a competitive electricity market than has generally been recognized.