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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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11 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2010

Fairness and dynamic pricing: comments

In ''The Ethics of Dynamic Pricing,'' Ahmad Faruqui lays out a case for improved efficiency in using dynamic prices for retail electricity tariffs and addresses various issues about the distributional effects of alternative pricing mechanisms. The principal contrast is between flat or nearly constant energy prices and time-varying prices that reflect more closely the marginal costs of energy and capacity. The related issues of fairness criteria, contracts, risk allocation, cost allocation, means testing, real-time pricing, and ethical policies of electricity market design also must be considered. (author)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2010

FERC sees huge potential for demand response

The FERC study concludes that U.S. peak demand can be reduced by as much as 188 GW -- roughly 20 percent -- under the most aggressive scenario. More moderate -- and realistic -- scenarios produce smaller but still significant reductions in peak demand. The FERC report is quick to point out that these are estimates of the potential, not projections of what could actually be achieved. The main varieties of demand response programs include interruptible tariffs, direct load control (DLC), and a number of pricing schemes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2010

Is flat fair?

Dynamic pricing holds out the promise of shifting peak demand as well as reducing overall demand. But it also raises thorny issues of fairness. All practical pricing systems involve tradeoffs between equity and efficiency. I examine the circumstances under which equity ought to be allowed to trump efficiency and whether or not this constitutes a defense of flat pricing. (author)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2010

The ethics of dynamic pricing

Dynamic pricing has garnered much interest among regulators and utilities, since it has the potential for lowering energy costs for society. But the deployment of dynamic pricing has been remarkably tepid. The underlying premise is that dynamic pricing is unfair. But the presumption of unfairness in dynamic pricing rests on an assumption of fairness in today's tariffs. (author)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2010

The practical equity implications of advanced metering infrastructure

Reductions in advanced metering costs and the efficiency benefits of dynamic pricing make a compelling case to adopt both, particularly for industrial and commercial facilities. Regulators should seriously consider such policies for residential households as well. Regulators can take meaningful steps to mitigate, if not entirely offset, the possibility that some low-income ratepayers may have higher electricity bills with AM and DP. (author)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2010

Decentralised optimisation of cogeneration in virtual power plants

Within several projects we investigated grid structures and management strategies for active grids with high penetration of renewable energy resources and distributed generation (RES and DG). Those ''smart grids'' should be designed and managed by model based methods, which are elaborated within these projects. Cogeneration plants (CHP) can reduce the greenhouse gas emissions by locally producing heat and electricity. The integration of thermal storage devices is suitable to get more flexibility for the cogeneration operation. If several power plants are bound to centrally managed clusters, it is called ''virtual power plant''. To operate smart grids optimally, new optimisation and model reduction techniques are necessary to get rid with the complexity. There is a great potential for the optimised management of CHPs, which is not yet used. Due to the fact that electrical and thermal demands do not occur simultaneously, a thermally driven CHP cannot supply electrical peak loads when needed. With the usage of thermal storage systems it is possible to decouple electric and thermal production. We developed an optimisation method based on mixed integer linear programming (MILP) for the management of local heat supply systems with CHPs, heating boilers and thermal storages. The algorithm allows the production of thermal and electric energy with a maximal benefit. In addition to fuel and maintenance costs it is assumed that the produced electricity of the CHP is sold at dynamic prices. This developed optimisation algorithm was used for an existing local heat system with 5 CHP units of the same type. An analysis of the potential showed that about 10% increase in benefit is possible compared to a typical thermally driven CHP system under current German boundary conditions. The quality of the optimisation result depends on an accurate prognosis of the thermal load which is realised with an empiric formula fitted with measured data by a multiple regression method. The key functionality of a virtual power plant is to increase the value of the produced power by clustering different plants. The first step of the optimisation concerns the local operation of the individual power generator, the second step is to calculate the contribution to the virtual power plant. With small extensions the suggested MILP algorithm can be used for an overall EEX (European Energy Exchange) optimised management of clustered CHP systems in form of the virtual power plant. This algorithm has been used to control cogeneration plants within a distribution grid. (author)

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2010

Springboard Engineering's Smart Grid Controller for Non-Smart Household Electricity-Consuming Appliances (Final Technical Report)

The Smart Grid opens the door to the development of many companion technologies which will in turn enable the development of a variety of devices for household electricity-consuming appliances that can communicate with it; especially, many major appliance manufacturers (such as Whirlpool and General Electric) have made public commitments to design their appliances to be Smart Grid-compatible over the next several years. Yet during that same time period, customers will purchase many millions of long-lasting appliances which are not compatible with the Smart Grid. This research project's purpose is to bring significant Smart Grid compatibility to previously-installed appliances that were not specifically designed for any Smart Grid communications, in a way that is both economical and attractive for users who want to share in the energy cost savings and reduction of peak power demand opportunities provided by the evolving Smart Grid infrastructure. The focus of this effort is to identify and research smart control solutions which take advantage of the effective strategies of demand-response (DR) communications from utilities [including time-of-day (TOD) and peak-demand pricing options] and function apart from any need for operational changes to be designed into the non-smart appliances. Our Phase I concepts promote technological advancements for enabling devices that shift the available-use time of millions of different appliances which otherwise have no Smart Grid capability. We researched low-cost microcontroller-based ways of creating devices with the ability to: (1) maintain an accurate time and day (with no need for battery backup throughout a power outage); (2) perform two-way wired and wireless communications directly with the utility company's demand management signals, to identify both low-cost time periods as well as critical-reduction periods when the cost of energy use would otherwise be much higher; (3) measure the power usage of the connected non-smart appliance; and (4) remove power for a period of time from the appliance (such as a dehumidifier, portable heater, or pool pump) in response to both time-pricing schedule and critical peak-load information from the utility, or inform the user of a batch-type appliance (such as a clothes dryer or dishwasher) regarding the current cost associated with using the appliance. The new products that could be developed as a result of this research into new consumer-centric features and characteristics includes smart wall outlets, smart outlet power-monitoring adapters, smart load switches and smart remote electric rate indicators associated with the non-smart appliances. Our Phase I goal of determining the feasibility of the above technologies was successful. The objectives were also met of developing concepts for a family of microprocessor-based control/indicator devices that can provide the above capabilities while connected in series between an appliance and its electrical power source and/or while indicating cost-of-use status to the appliance user.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Increasing Revenue of Nuclear Power Plants With Thermal Storage

Introducing large amounts of electricity produced from variable renewable energy sources such as wind and solar decreases wholesale electricity price while increasing the volatility of the market. These conditions drive the need for peak-load power generation, while regulation requirements fuel the push for flexible power generation. The increase of variable renewable energy in the market share, along with falling natural gas prices, makes nuclear power plants less competitive. Thermal storage is being considered to increase the nuclear power plant revenue. Thermal storage increases the flexibility of the nuclear plant system without sacrificing its efficiency. There are multiple opportunities to increase the nuclear power plant revenue, including increased capacity payments, arbitrage, and ancillary services. An economic analysis was performed to investigate the revenue increase of the system with thermal storage. The investment cost was assessed, and net present value was evaluated for the considered scenarios. Two system designs were considered in the analysis: a thermal storage system using the existing power conversion infrastructure and an integrated design with thermal storage fully incorporated into the reactor system design. The preliminary analysis showed that introducing a thermal storage system is profitable for some scenarios considered. Profitability depends significantly on the storage size, output flexibility, share of variable renewable energy, and market characteristics.

25 ENERGY STORAGE↗
DOE OSTI2019

Impacts of variable renewable energy on wholesale markets and generating assets in the United States: A review of expectations and evidence

Here, we synthesize available literature, data, and analysis on the degree to which growth in variable renewable energy (VRE) has impacted or might in the future impact bulk power system assets, pricing, and costs in the United States. Most studies of future scenarios indicate that VRE reduces wholesale energy prices and capacity factors of thermal generators. Traditional baseload generators are more exposed to these changing market conditions than low-capital cost and more flexible intermediate and peak-load generators. From analysis of historical data we find that VRE is already influencing the bulk power market through changes in temporal and geographic patterns areas with higher levels of VRE. The most significant observed impacts have concentrated in areas with significant VRE and/or nuclear generation along with limited transmission, with negative pricing also often occurring during periods with lower system-wide load. So far, however, VRE, has had a relatively modest impact on historical average annual wholesale prices across entire market regions, at least in comparison to other drivers. The reduction of natural gas prices is the primary contributor to the decline in wholesale prices since 2008. Similarly, VRE impacts on thermal plant retirements have been limited and there is little relationship between the location of recent retirements and VRE penetration levels. Finally, although impacts on wholesale prices have been modest so far, impacts of VRE on the electricity market will be more significant under higher VRE penetrations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2014

Combined Municipal Solid Waste and biomass system optimization for district energy applications

Highlights: • Combined energy conversion of MSW and agricultural residue biomass is examined. • The model optimizes the financial yield of the investment. • Several system specifications are optimally defined by the optimization model. • The application to a case study in Greece shows positive financial yield. • The investment is mostly sensitive on the interest rate, the investment cost and the heating oil price. - Abstract: Municipal Solid Waste (MSW) disposal has been a controversial issue in many countries over the past years, due to disagreement among the various stakeholders on the waste management policies and technologies to be adopted. One of the ways of treating/disposing MSW is energy recovery, as waste is considered to contain a considerable amount of bio-waste and therefore can lead to renewable energy production. The overall efficiency can be very high in the cases of co-generation or tri-generation. In this paper a model is presented, aiming to support decision makers in issues relating to Municipal Solid Waste energy recovery. The idea of using more fuel sources, including MSW and agricultural residue biomass that may exist in a rural area, is explored. The model aims at optimizing the system specifications, such as the capacity of the base-load Waste-to-Energy facility, the capacity of the peak-load biomass boiler and the location of the facility. Furthermore, it defines the quantity of each potential fuel source that should be used annually, in order to maximize the financial yield of the investment. The results of an energy tri-generation case study application at a rural area of Greece, using mixed MSW and biomass, indicate positive financial yield of investment. In addition, a sensitivity analysis is performed on the effect of the most important parameters of the model on the optimum solution, pinpointing the parameters of interest rate, investment cost and heating oil price, as those requiring the attention of the decision makers. Finally, the sensitivity analysis is enhanced by a stochastic analysis to determine the effect of the volatility of parameters on the robustness of the model and the solution obtained.

09 BIOMASS FUELS↗
DOE OSTI2010

Use of Residential Smart Appliances for Peak-Load Shifting and Spinning Reserves Cost/Benefit Analysis

In this report, we present the results of an analytical cost/benefit study of residential smart appliances from a utility/grid perspective in support of a joint stakeholder petition to the ENERGY STAR program within the Environmental Protection Agency (EPA) and Department of Energy (DOE). The goal of the petition is in part to provide appliance manufacturers incentives to hasten the production of smart appliances. The underlying hypothesis is that smart appliances can play a critical role in addressing some of the societal challenges, such as anthropogenic global warming, associated with increased electricity demand, and facilitate increased penetration of renewable sources of power. The appliances we consider include refrigerator/freezers, clothes washers, clothes dryers, room air-conditioners, and dishwashers. The petition requests the recognition that providing an appliance with smart grid capability, i.e., products that meet the definition of a smart appliance, is at least equivalent to a corresponding five percent in operational machine efficiencies. It is then expected that given sufficient incentives and value propositions, and suitable automation capabilities built into smart appliances, residential consumers will be adopting these smart appliances and will be willing participants in addressing the aforementioned societal challenges by more effectively managing their home electricity consumption. The analytical model we utilize in our cost/benefit analysis consists of a set of user-definable assumptions such as the definition of on-peak (hours of day, days of week, months of year), the expected percentage of normal consumer electricity consumption (also referred to as appliance loads) that can shifted from peak hours to off-peak hours, the average power rating of each appliance, etc. Based on these assumptions, we then formulate what the wholesale grid operating-cost savings, or benefits, would be if the smart capabilities of appliances were invoked, and some percentage of appliance loads were shifted away from peak hours to run during off-peak hours, and appliance loads served power-system balancing needs such as spinning reserves that would otherwise have to be provided by generators. The rationale is that appliance loads can be curtailed for about ten minutes or less in response to a grid contingency without any diminution in the quality of service to the consumer. We then estimate the wholesale grid operating-cost savings based on historical wholesale-market clearing prices (location marginal and spinning reserve) from major wholesale power markets in the United States. The savings derived from the smart grid capabilities of an appliance are then compared to the savings derived from a five percent increase in traditional operational machine efficiencies, referred to as cost in this report, to determine whether the savings in grid operating costs (benefits) are at least as high as or higher than the operational machine efficiency credit (cost).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗