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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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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Droop Control-Based Dispatch of an Islanded Microgrid With Multiple Grid-Forming Sources

Before rotating, fossil fuel-based, synchronous generators (SGs) are phased out, in line with renewable generation goals, grid-forming (GFM) inverters are expected to parallel SGs. Primary droop control allows GFM inverters to share power without communication; however, it is necessary to dispatch GFM inverters and/or SGs with the desired output power for better energy management (e.g., one GFM inverter needs to charge the battery due to a low state of charge). Therefore, this paper develops an analytic approach to dispatching GFM inverters and SGs with the desired output power by shifting the droop intercept up/down while maintaining the same frequency operating point for improved transient stability. This concept is demonstrated through a pure hardware setup with two off-the-shelf inverters and one diesel generator under an islanded microgrid, and we provide insight on the real-world implementation of the proposed concept.

droop control↗
DOE OSTI2024

Decomposing a renewable energy design and dispatch model

We address a mixed-integer linear programming model which selects a cost-minimizing set of available technologies with which to design a renewable energy system and prescribe their associated dispatch decisions. Realistically sized instances of such models pose computational challenges. To this end, we develop a Lagrangian heuristic based on a decomposition methodology which partitions the model into blocks and optimizes these more manageable, smaller subproblems. It also provides a lower bound to assess solution quality. In conclusion, we apply this methodology to the National Renewable Energy Laboratory's Renewable Energy Integration and Optimization (REopt TM ) model to generate near-optimal solutions to realistic instances containing, on average, approximately 300,000 variables and at least as many constraints, with a mean 30% optimality gap improvement using a five-minute solution time limit, compared to directly solving the original monolith.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Adjustable and distributionally robust chance-constrained economic dispatch considering wind power uncertainty

This paper proposes an adjustable and distributionally robust chance-constrained (ADRCC) optimal power flow (OPF) model for economic dispatch considering wind power forecasting uncertainty. The proposed ADRCC-OPF model is distributionally robust because the uncertainties of the wind power forecasting are represented only by their first- and second-order moments instead of a specific distribution assumption. The proposed model is adjustable because it is formulated as a second-order cone programming (SOCP) model with an adjustable coefficient. This coefficient can control the robustness of the chance constraints, which may be set up for the Gaussian distribution, symmetrically distributional robustness, or distributionally robust cases considering wind forecasting uncertainty. The conservativeness of the ADRCC-OPF model is analyzed and compared with the actual distribution data of wind forecasting error. The system operators can choose an appropriate adjustable coefficient to tradeoff between the economics and system security.

17 WIND ENERGY↗
DOE OSTI2019

Optimal dispatch for participation of electric vehicles in frequency regulation based on area control error and area regulation requirement

In this study, optimal strategies are proposed for electric vehicles in charging stations to participate in the secondary frequency regulation, while considering their charging demands. In order to fairly allocate the dispatch from the control center among electric vehicles according to their charging demands, two optimal real-time strategies are proposed, respectively based on area control error and area regulation requirement. With the proposed strategies, the expected charging of electric vehicles is optimally tracked in real time by using the regulation task from the control center. Simulations on a two-area interconnected power grid show that the proposed two strategies can respectively lead to a 12.66% and 16.78% frequency deviation reduction and a 13.76% and 9.86% generator regulation reduction. At the same time, the charging demands of EVs can also be ensured.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

A Model for Evaluating the Configuration and Dispatch of PV Plus Battery Power Plants

An open-source model was developed to optimize energy storage operation for photovoltaic- (PV-) plus-battery systems with AC-coupled and DC-coupled configurations. It includes the ability to use forecast energy prices to optimize battery charge and discharge on a rolling time horizon. The model allows for exploration of different configurations, including capital costs, inverter performance, dispatch flexibility, and capturing otherwise clipped energy for the DC-coupled system. The model can run 20 full years of hourly data in approximately two seconds, allowing comparison of a large number of configurations. We applied the model in a test case demonstrating reduced inverter clipping for DC-coupled systems and yielded slightly higher overall value than AC-coupled systems, with an approximately 2 percent increase in internal rate of return or benefit/cost ratio. Our results show that at current estimated prices for lithium-ion battery systems, large-scale PV-plus-battery plants are economically viable under the right conditions, with the configuration playing a role in system flexibility and performance. This model provides the ability for project developers, industry professionals, and researchers to use readily available software to quickly evaluate and design these systems.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

Optimizing design and dispatch of a renewable energy system

Renewable energy technologies are becoming increasingly important due to their cost-competitiveness, and because of enhanced climate concerns. We demonstrate the capabilities of an integer-programming optimization model that minimizes capital (investment) and operational costs, and utility charges, while adhering to system sizing constraints, demand requirements, and interoperability characteristics of the systems chosen. Furthermore, the model recommends an optimally sized mix of renewable energy, conventional generation, and energy storage technologies, while simultaneously optimizing the corresponding dispatch strategy. Our case studies explore several venues, i.e., a small campus and a local hospital, with complex utility rate tariffs, multi-technology integration opportunities, and incentives for renewable power production. Using an optimization model, versus applying rules of thumb, can produce millions of dollars in savings over a 25-year time horizon and result in thousands of kilowatts of installed renewable energy.

25 ENERGY STORAGE↗
DOE OSTI2021

Implication of production tax credit on economic dispatch for electricity merchants with storage and wind farms

The production tax credit (PTC) promotes wind energy development, reduces power generation costs, and can affect merchants’ joint economic dispatch, particularly for electricity merchants with both energy storage and wind farms. Two common PTC policies are studied – in the first policy, a wind farm receives PTC by selling wind generation to the market and its storage can be used to store energy from the wind generation and energy purchased from the grid but the energy released from the storage cannot receive PTC; in the second policy, the energy released from the storage can also qualify for PTC but purchasing energy from the grid is not allowed. We then employ dynamic programming to study merchants' optimal decision-making while considering PTC and the physical characteristics of storage systems. We analytically show that the state of charge (SOC) range can be segmented into different regions by SOC reference points under two PTC policies. The merchant's optimal action can be conveniently and uniquely determined based on the region within which the current SOC falls. Moreover, this study illustrates that PTC could substantially alter the optimal scheduling policy structures by affecting reference points and their relationships. The results showed that the frequencies for charging and discharging storage decisions decreased with an increase in PTC subsidy. Last, we confirm that, although the first policy allows merchants to buy electricity from the market, the second policy can bring more profits when the PTC is large at the current PTC rates. Furthermore, the findings can provide multistage decision-making guidance to electricity merchants in the wholesale power market.

17 WIND ENERGY↗
DOE OSTI2024

Evaluating the Impact of Off-Design CHP Performance on the Optimal Sizing and Dispatch on Hybrid Renewable-CHP Distributed Energy Resources

The maturation of distributed energy resources (DER) has prompted the exploration of their deployment in commercial building applications due to their potential to supply energy at lower costs and emissions rates compared to centralized generation. While several software tools exist for evaluating the techno-economic potential of integrated renewable energy and combined heat and power (CHP) systems for distributed generation applications, many suffer from poor accuracy in capturing off-design (part load and changes in ambient air temperature and pressure) performance characteristics of microturbines, combustion turbines, or internal combustion engines. Thus, this paper presents a methodology for integrating these off-design characteristics in the mixed-integer linear program within REopt, a hybrid DER screening tool. The economic impact of the CHP off-design performance is observed through several application studies of various hybrid system configurations in different climates. Each study indicates how CHP off-design performance influences optimal sizing and dispatch decisions and therefore overall system economic value. We observe through case studies that modeling without the off-design effects, depending on the CHP prime mover and site, can result in Net Present Value predictions of hybrid systems that can be overoptimistic in frequently hot climates (up to 52%), too conservative in frequently cold climates (up to 11%), or unaffected (+/-1%) in temperate climates. Cases also highlight several advantages of hybrid systems relative to non-hybrid systems such as total economic value and the systems' ability to mitigate potentially negative consequences attributed to off-design performance.

ambient de-rate↗
DOE OSTI2022

A nuclear-hydrogen hybrid energy system with large-scale storage: A study in optimal dispatch and economic performance in a real-world market

Here a study in optimal dispatch and economic analysis of a novel nuclear hybrid energy system (NHES) with large-scale hydrogen storage and a novel control scheme is conducted. The control scheme makes charge and discharge decisions by using the real-time electricity price relative to the historical price distribution. The pricing data is taken from the ERCOT Houston and West load zones with different price oscillations. Six case control studies with different levels of aggressiveness were chosen for each load zone for a total of 12 case studies. It is found that in a high price volatility load zone, a more aggressive control strategy maximizes revenue, while in a less oscillatory load zone, a moderate control strategy performs better. The NHES can store energy when the price is low and sell additional electricity when the price is high, as well as participate in the ancillary services market. Due to these advantages, the NHES can generate 10–40 million USD more revenue annually than a stand-alone nuclear plant. Due to higher costs, the NHES has a higher LCOE (81.36 USD/MWh) than a stand-alone plant (68.66 USD/MWh); however, the LCOE of the NHES is still comparable to other new forms of electricity generation. It is found that both the NHES and the stand-alone plant are not economical in the existing electricity market. Due to the extra revenue generated, the hybrid system has a positive annual cashflow whereas the stand-alone plant does not. It is found that the hybrid plant needs less cost subsidy than a stand-alone plant to become economical.

08 HYDROGEN↗
DOE OSTI2017

A multi-criteria decision analysis-based approach for dispatch of electric microgrids

This paper presents a decision support system (DSS) for multi-objective dispatch of an electric microgrid con-sidering cost of operation, peak load reduction, and emissions. Discrete compromise programming (DCP) is used as the multi-criteria decision analysis (MCDA) technique for providing the decision support to the distribution system operator (DSO) by ranking various alternatives based on preference of the objec-tives. Simulations are performed on a notional electric microgrid based on the IEEE 13-node test feeder and the results are pre-sented with appropriate visualization.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Optimizing dispatch for a concentrated solar power tower

Concentrating solar power (CSP) systems employ a sophisticated thermal receiver, power cycle, and a heliostat field, comprised of thousands of mirrors spread over hundreds of acres of land, and are most cost-effective with relatively large quantities of energy storage which can be scheduled for dispatch. We exercise an existing optimization model that maximizes revenue over a year-long time horizon, solved using a standard 48-h look-ahead policy at hourly fidelity on a CSP system under development in California. The system employs molten salt power tower technology with a 150 MWe (net) turbine, eight hours of thermal storage at full load, and a solar field that provides 1.75 times the rated turbine thermal power. The model considers system configuration and interoperability aspects, such as storage tank size, production capacities, and ramp rates, and determines decisions that expedite financing, permitting, and plant design. Relative to results achieved via industry practice, the existing optimization model reduces the number of power cycle (i.e., turbine) start-up events by 86.4%, thereby improving net revenue by more than 8.5% annually; this corresponds to an approximately $140 M increase in net revenue over the lifetime of the plant, taking a step towards advancing the long-term economic viability of large-scale renewable energy systems. Sensitivity analysis on uncertain parameter values provides insight regarding those values that influence profit most significantly.

14 SOLAR ENERGY↗
DOE OSTI2024

H ∞ Control for Energy Dispatch in Autonomous Nanogrid With Communication Delays

This paper proposes an optimal controller and estimator for energy dispatch to balance the power supply and demand considering communication delays. The proposed algorithm involves modeling an autonomous nanogrid (ANG) consisting of distributed energy resources, energy storage systems, loads, an $H$ ∞ controller with a reference power modulation technique, and a state estimator. The ANG was developed to express the dynamic supply-demand energy balance of a nanogird system. Reference power modulation was designed to generate the desired ESS power based on the imbalanced energy. Random communication delays were modeled using a stochastic variable satisfying the Bernoulli random binary distribution. The optimal $H$ ∞ controller and estimator were developed using a linear matrix inequality approach to exponentially stabilize the closed-loop system. Simulations were performed using real daily demand forecasts obtained from the Korea Meteorological Administration to demonstrate the effectiveness of the proposed real-time optimization algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

A Distributionally Robust Optimization Framework for Stochastic Assessment of Power System Flexibility in Economic Dispatch

Given the complexity of power systems, particularly the high-dimensional variability of net loads, accurately depicting the entire operational range of net loads poses a challenge. To address this, recent methodologies have sought to gauge the maximum range of net load uncertainty across all buses. In this paper, we consider the stochastic nature of the net load and introduce a distributionally robust optimization framework that assesses system flexibility stochastically, accommodating a minimal extent of system violations. We verify the proposed method by solving the flexibility of the economic dispatch problem on four distinct IEEE standard test systems. Compared to traditional deterministic flexibility evaluations, our approach consistently yields less conservative flexibility outcomes.

distributionally robust optimization↗
DOE OSTI2022

Dynamic Economic Dispatch Considering Transmission–Distribution Coordination and Automatic Regulation Effect

With the rapid increase of renewable energy sources, the variability and uncertainty in power systems are significantly increased, and the power system operation is facing more and more challenges. In the traditional dynamic economic dispatch (DED) of transmission systems, the frequency and voltage regulation effects are not actively utilized. In addition, the transmission systems and distribution systems are optimized separately; the transmission–distribution coordination effect is not considered. In this article, a new DED is proposed. The optimal scheduling results are obtained by making a balance between operating cost and reliability cost. Both the automatic regulation effect and transmission–distribution coordination effect are explored and exploited in terms of the equivalent reserve, which can reduce the reserve provided by generating units, and can further enhance the security and economics of power system operation. The validity and effectiveness of the proposed model are illustrated by case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

A New LMP-Sensitivity-Based Heterogeneous Decomposition for Transmission and Distribution Coordinated Economic Dispatch

Transmission and distribution coordinated economic dispatch (TDCED) will be necessary to settle the problems caused by high penetrations of distributed generators in future grids. An efficient heterogeneous decomposition algorithm (HGD) was proposed to solve the TDCED, but it may diverge occasionally. To overcome this shortcoming, a new HGD (N-HGD) with enhanced convergency is proposed and studied in this paper. Compared with the previous HGD, the N-HGD similarly decomposes the TDCED into transmission ED and distribution ED subproblems, but it considers the sensitivity of the boundary locational marginal price to load injections to enhance convergency and avoid divergence. Two kinds of sensitivity computing methods, M-c and M-p, are studied. M-c is based on a centralized sensitivity equation, executed on the transmission side. M-p is based on a probing mechanism and can be executed distributedly on the distribution side. The reason for the N-HGD's improved convergency is theoretically analyzed, and the optimality is proven. Numerical tests show that N-HGD performs better than the original HGD, as well as a penalty-based modified HGD that needs a careful parametertuning process. Furthermore, compared with M-c, an M-p-based N-HGD is preferable because it has a much lower computational cost and no additional communicational cost.

distribution↗
DOE OSTI2017

Security and Cloud Outsourcing Framework for Economic Dispatch

The computational complexity and problem sizes of power grid applications have increased significantly with the advent of renewable resources and smart grid technologies. The current paradigm of solving these issues consist of inhouse high performance computing infrastructures, which have drawbacks of high capital expenditures, maintenance, and limited scalability. Cloud computing is an ideal alternative due to its powerful computational capacity, rapid scalability, and high cost-effectiveness. A major challenge, however, remains in that the highly confidential grid data is susceptible for potential cyberattacks when outsourced to the cloud. In this work, a security and cloud outsourcing framework is developed for the Economic Dispatch (ED) linear programming application. As a result, the security framework transforms the ED linear program into a confidentiality-preserving linear program, that masks both the data and problem structure, thus enabling secure outsourcing to the cloud. Results show that for large grid test cases the performance gain and costs outperforms the in-house infrastructure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Minimizing Uncertainties Impact in Decision Making with an Applicability Study for Economic Power Dispatch

This report summaries the work performed under the LDRD project on the preliminary study on knowledge automation, where specific focus has been made on the investigation of the impact of uncertainties of human decision making onto the optimization of the process operation. At first the statistics on signals from the Brain-Computing Interface (BCI) is analyzed so as to obtain the uncertainties characterization of human operators during the decision making phase using the electroencephalogram (EEG) signals. This is then followed by the discussions of an architecture that reveals the equivalence between optimization and closed loop feedback control design, where it has been shown that all the optimization problems can be transferred into the control design problem for closed loop systems. This has led to a “closed loop” framework, where the structure of the decision making is shown to be subjected to both process disturbances and controller’s uncertainties. The latter can well represent the uncertainties or randomness occurred during human decision making phase. As a result, a stochastic optimization problem has been formulated and a novel solution has been proposed using probability density function (PDF) shaping for both the cost function and the constraints using stochastic distribution control concept. A sufficient condition has been derived that guarantees the convergence of the optimal solution and discussions have been made for both the total probabilistic solution and chanced constrained optimization which have been well-studied in optimal power flows (OPF) area. A simple case study has been carried out for the economic dispatch of powers for a grid system when there are distributed energy resources (DERs) in the system, and encouraging results have been obtained showing that a significant savings on the generation cost can be expected.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2018

Dispatchable Solar Power Plant Project

As penetration of intermittent renewable power increases, grid operators must manage greater variability in the supply and demand on the grid. One result is that utilities are planning to build many new natural gas peaking power plants that provide added flexibility needed for grid management. This report discusses the development of a dispatchable solar power (DSP) plant that can be used in place of natural gas peakers. Specifically, a new molten-salt tower (MST) plant has been developed that is designed to allow much more flexible operation than typically considered in concentrating solar power plants. As a result, this plant can provide most of the capacity and ancillary benefits of a conventional natural gas peaker plant but without the carbon emissions. The DSP system presented was designed to meet the specific needs of the Arizona Public Service (APS) utility 2017 peaking capacity request for proposals (RFP). The goal of the effort was to design a MST peaker plant that had the operational capabilities required to meet the peaking requirements of the utility and be cost competitive with the natural gas alternative. The effort also addresses many perceived barriers facing the commercial deployment of MST technology in the US today. These include MST project development issues such as permitting, avian impacts, visual impacts of tower CSP projects, project schedule, and water consumption. The DSP plant design is based on considerable analyses using sophisticated solar system design tools and in-depth preliminary engineering design. The resulting DSP plant design uses a 250 MW steam power cycle, with solar field designed to fit on a square mile plot of land that has a design point thermal rating of 400 MWt. The DSP plant has an annual capacity factor of about 16% tailored to deliver greater than 90% capacity during the critical Arizona summer afternoon peak. The table below compares the All-In energy cost and capacity payment of conventional combustion turbines to DSP plants. These results estimate that the cost of the DSP plant is about 10% higher than a similarly-sized and operated frame combustion turbine and slightly cheaper than an aero derivative combustion turbine when APS reference fuel and emissions costs are included. The DSP plant cost is based on a single, first-of-a-kind plant, and it is likely that subsequent plants would be less expensive.

14 SOLAR ENERGY↗