Search NASA⌕ Search

SEARCH · Search NASA

Results for “Dispatchable Solar Power”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Model Formulations: Integrating Distributed Energy Resources (DER) using Advanced Unit Commitment Models and DER Aggregation Methodologies

A distribution energy resource aggregator (DERA) constitutes a group of distribution energy resources with small generation capacities which meet the threshold to participate in the electricity wholesale market. This document provides the proposed DERA model formulation that will be implemented in the SCUC simulation’s architecture for the SCUC-DER project. Different economical assessment methodologies have been developed to incorporated bids for individual distributed resources, which include solar cost dispatch and cost model, BESS opportunity cost offer algorithm, and price sensitive demand response model. Detailed methods are proposed to aggregate individual cost offers to a DERA cost curve to bid in SCUC market while three methods are proposed to simulate DER actual dispatch. Based on the DERA models in this document, the SCUC-DER project will be able to assess the impacts of DERA on the distribution system’s operation and reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Enhanced Simulation Tools for Scheduling Solar Plus Storage Power Plants

This is the final technical report for the Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) under the Solar Energy Technology's Office Balance of Systems program, Award Number 38429. This report summarizes the key outputs and findings of the project, which was focused on long-duration energy storage (LDES) and solar. In particular, one of the most significant challenges of maximizing the value of variable solar energy is the timing of charging and discharging stored energy from LDES devices. Power systems often fail to capture the benefits of LDES and can undervalue the role of storage in providing energy arbitrage, reliability support, and resiliency. This project examined those challenges and proposed alternative methodologies that better capture the value that LDES can provide.

14 SOLAR ENERGY↗
DOE OSTI2017

Greening the Grid: Advances in Production Cost Modeling for India Renewable Energy Grid Integration Study

The Greening the Grid: Pathways to Integrate 175 Gigawatts of Renewable Energy into India's Electric Grid study uses advanced weather and power system modeling to explore the operational impacts of meeting India's 2022 renewable energy targets and identify actions that may be favorable for integrating high levels of renewable energy into the Indian grid. The study relies primarily on a production cost model that simulates optimal scheduling and dispatch of available generation in a future year (2022) by minimizing total production costs subject to physical, operational, and market constraints. This fact sheet provides a detailed look at each of these models, including their common assumptions and the insights provided by each.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective

Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision makers. With the recent surge in variable renewable energy (VRE) generators - primarily wind and solar photovoltaics - the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. To assess current best practices, share methods and data, and identify future research needs for VRE representation in capacity expansion models, four capacity expansion modeling teams from the Electric Power Research Institute, the U.S. Energy Information Administration, the U.S. Environmental Protection Agency, and the National Renewable Energy Laboratory conducted two workshops of VRE modeling for national-scale capacity expansion models. The workshops covered a wide range of VRE topics, including transmission and VRE resource data, VRE capacity value, dispatch and operational modeling, distributed generation, and temporal and spatial resolution. The objectives of the workshops were both to better understand these topics and to improve the representation of VRE across the suite of models. Given these goals, each team incorporated model updates and performed additional analyses between the first and second workshops. This report summarizes the analyses and model 'experiments' that were conducted as part of these workshops as well as the various methods for treating VRE among the four modeling teams. The report also reviews the findings and learnings from the two workshops. We emphasize the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Hydrogen Based Energy Storage System for Integration with Dispatchable Power Generator (Phase I Feasibility Study)

This project examined the feasibility of integrating hydrogen generation, storage, and use as a means to decarbonize campus activities while retaining the ability to utilize the existing natural gas fired combined heat and power system installed at the campus of the University of California @ Irvine. Analysis of specific potential sites for the integrated system identified a location adjacent to the existing central plant which resulted in minimization of interconnections. A strategy based on use of commercial electrolyzers and gas storage was identified. Primary technology advancements are required for the gas turbine to accommodate higher levels of hydrogen and the integrated controls. The project indicated challenges for adopting the proposed strategy with the present rates and constraints. The availability of a relatively low-cost biogas resource by the campus already decarbonizes the gas turbine to some extent. In the absence of this resource, procurement of electricity directly from large scale renewable operations could facilitate lower electricity costs. Additional solar resources on campus could also help in this regard. The gas turbine cannot be operated below 50% capacity due to air permit constraints. Using the otherwise curtailed gas turbine operation to generate hydrogen via electrolysis by consuming natural gas is not highly efficient and therefore leads to relatively high costs of electricity returned. Several scenarios demonstrate potential for effective decarbonization, yet most involve lower and lower capacity factor for the legacy gas turbine which is not a good use of the asset. A small gas turbine output with higher efficiency operation would help. As would ability to export electricity to the grid. Certainly current rate structures and operational scenarios are less attractive than other possible future structures which should be pushed for in the future.

03 NATURAL GAS↗
DOE OSTI2021

Development of Energy Storage: Cost models

Energy storage technologies offer a promising solution to electric grid stability issues associated with the integration of variable renewable generators. The capability to match the electrical power output to instantaneous fluctuations in grid demand is crucial to ensure continuity of service. Including energy storage capability in an integrated energy system (IES) can provide the flexibility needed to meet variable electric demand and reduce the load following demands place on the reactor. In this report, economic data collected for energy storage (ES) technologies are described to support the objective of assessing the profitability of ES integration within the IES framework. In particular, there is a growing interest in thermal energy storage (TES) given its unique capability for long-duration storage for improving electricity reliability at a low levelized cost. It is common practice to evaluate the total lifetime cost and profitability before commercializing new technologies. In this report we identify and examine the models needed to better understand the economics of thermal energy storage. We extend the TES cost model in RAVEN in the context of a balance of plant (BOP) that incorporates thermal storage. To focus the discussion, following a general overview of the most promising TES technologies, we consider a use case that involves a sensible heat, two-tank, molten-salt system. Structural and operational details are reported to identify the source of construction capital expenditure and operation and maintenance cost. A detailed description of the different cost items is provided as well as the cost scaling with different storage capacity and power ratings for capacity optimization purpose. In addition, the capital expenditure and the recurring cost of representative two-tank, molten salt coupled with concentrated solar plants are provided for readers’ reference. The ES use case is noteworthy as it is in the pilot stage of commercialization. We identify those areas that would benefit from an increased economic focus to obtain a more complete compilation of cost data. We also describe the thermal coupling issues that arise from integration of the two-tank molten salt thermal energy storage system with a BOP, which is the subject of our current research. Some components of costs will need to be evaluated through dedicated technoeconomic analysis in future modeling activities using modeling procedures proposed in this report. With the data presented and the procedures described in this report, sufficiently accurate models can be implemented for the solution of both the power dispatch and the capacity expansion problems within the RAVEN-based HYBRID framework.

25 ENERGY STORAGE↗
DOE OSTI2022

Thermophotovoltaic efficiency of 40%

Thermophotovoltaics (TPVs) convert predominantly infrared wavelength light to electricity via the photovoltaic effect, and can enable approaches to energy storage and conversion that use higher temperature heat sources than the turbines that are ubiquitous in electricity production today. Since the first demonstration of 29% efficient TPVs (Fig. 1a) using an integrated back surface reflector and a tungsten emitter at 2,000°C (ref. 10), TPV fabrication and performance have improved. However, despite predictions that TPV efficiencies can exceed 50%, the demonstrated efficiencies are still only as high as 32%, albeit at much lower temperatures below 1,300 C (refs. 13,14,15). Here we report the fabrication and measurement of TPV cells with efficiencies of more than 40% and experimentally demonstrate the efficiency of high-bandgap tandem TPV cells. The TPV cells are two-junction devices comprising III–V materials with bandgaps between 1.0 and 1.4 eV that are optimized for emitter temperatures of 1,900–2,400°C. The cells exploit the concept of band-edge spectral filtering to obtain high efficiency, using highly reflective back surface reflectors to reject unusable sub-bandgap radiation back to the emitter. A 1.4/1.2 eV device reached a maximum efficiency of (41.1 ± 1)% operating at a power density of 2.39 W cm –2 and an emitter temperature of 2,400°C. A 1.2/1.0 eV device reached a maximum efficiency of (39.3 ± 1)% operating at a power density of 1.8 W cm–2 and an emitter temperature of 2,127°C. These cells can be integrated into a TPV system for thermal energy grid storage to enable dispatchable renewable energy. This creates a pathway for thermal energy grid storage to reach sufficiently high efficiency and sufficiently low cost to enable decarbonization of the electricity grid.

14 SOLAR ENERGY↗
DOE OSTI2023

Multiscale Electricity Modeling for Evaluating Carbon Capture and Sequestration Technologies (Final Report)

Carbon capture and sequestration (CCS) technologies that can operate with a high degree of operating flexibility could provide necessary electric grid flexibility in a system with high shares of variable renewables. This project examines the deployment and dispatch potential of twelve unique flexible CCS (FLECCS) technologies that encompass post-combustion carbon dioxide (CO 2 ) capture designs, concepts using a storage media to enable energy arbitrage, and hybrid processes that integrate CCS with direct air capture (DAC) for flexibility with net zero or negative CO 2 emissions. FLECCS technology potential is explored with a multi-model, multi-scale framework including the Regional Energy Deployment System (ReEDS) electric sector capacity expansion model (CEM) and the PLEXOS production cost model (PCM). Innovative methods were developed to represent FLECCS technology operating modes, performance, and cost in the two models. ReEDS was then used to simulate nine scenarios for each FLECCS technology, three CO 2 emissions price futures reaching $\$$150, $\$$225, and $\$$300/tCO 2 in 2050; and three scenarios for FLECCS technology deployment favorability relative to competing technologies. For each CO 2 price and reference FLECCS favorability, the 2050 infrastructures from ReEDS model are downscaled and implemented in PLEXOS to examine hourly dispatch under detailed operational constraints that are not included in ReEDS. FLECCS technologies exhibited a wide range of deployment potential ranging from none to several hundred gigawatts of capacity, with outcomes highly sensitive to input cost and performance parameters that are inherently highly uncertain. When deployed, FLECCS tended to displace a combination of wind, solar, and natural gas-based technologies rather than supporting increased renewable deployment. As a result, CO 2 emissions reductions facilitated by FLECCS deployment tended to come with higher overall system costs and electricity prices. When economically competitive, FLECCS technologies can contribute significant flexible generation and firm capacity to the grid, but continued technology development and an expanded analytical scope are necessary to fully understand FLECCS deployment potential its impact on the electric power sector. Follow-on analysis incorporating captured CO 2 tax credit value from the Inflation Reduction Act (IRA) and other potential policy scenarios could be particularly valuable, as this policy can substantially change the relative competitiveness of FLECCS technologies.

03 NATURAL GAS↗
DOE OSTI2017

Novel Control Strategy for Multiple Run-of-the-River Hydro Power Plants to Provide Grid Ancillary Services

Electricity generated by Hydropower Plants (HPPs) contributes a considerable portion of bulk electricity generation and delivers it with a low carbon footprint. In fact, HPP electricity generation provides the largest share from renewable energy resources, which includes solar and wind energy. The increasing penetration of wind and solar penetration leads to a lowered inertia in the grid and hence poses stability challenges. In recent years, breakthrough in energy storage technologies have demonstrated the economic and technical feasibility of extensive deployments in power grids. Multiple ROR HPPs if integrated with scalable, multi time-step energy storage so that the total output can be controlled. Although, the size of a single energy storage is far smaller than that of a typical reservoir, cohesively managing multiple sets of energy storage distributed in different locations is proposed. The ratings of storages and multiple ROR HPPs approximately equals the rating of a large, conventional HPP. The challenges associated with the system architecture and operation are described. Energy storage technologies such as supercapacitors, flywheels, batteries etc. can function as a dispatchable synthetic reservoir with a scalable size of energy storage will be integrated. Supercapacitors, flywheels, and battery are chosen to provide fast, medium, and slow responses to support grid requirements. Various dynamic and transient power grid conditions are simulated and performances of integrated ROR HPPs with energy storage is provided. The end goal of this research is to investigate the inertial equivalence of a large, conventional HPP with a unique set of multiple ROR HPPs and optimally rated energy storage systems.

13 HYDRO ENERGY↗
DOE OSTI2019

Incentive-Based Control and Coordination of Distributed Energy Resources. Final Report

The rapid growth of low-inertia renewable energy resources represents an immense opportunity for the U.S. to minimize its carbon footprint, while presenting a challenge for system operators as traditional “spinning” generation resources are displaced. This transformation requires solutions to robustly and cost-effectively manage dynamic changes on the grid while ensuring quality of service. There is growing recognition that distributed energy resources (DERs – loads, distributed generation, storage, electric vehicles, etc.) represent a great potential to perform this function. This report details a scalable hierarchical control strategy for coordinating thousands of heterogeneous DERs in order to provide three ancillary gird services: 1) frequency response, a rapid (within 2 seconds) service used to maintain the grid at 60 Hz; 2) regulation response, a larger response used to balance on-going differences in supply and demand on the grid; and, 3) ramping reserve, used to bring on capacity to replace lost generation. The developed control architecture consists of 1) a Distribution Reliability Coordinator (DRC), 2) aggregator controllers, and finally, 3) DER controllers. The DRC coordinates all the flexible loads and distributed energy resources on the distribution system and bids the aggregate flexibility into the wholesale market. The DRC also performs resource allocation (deciding how the flexible devices on the distribution system will be dispatched) to meet the requirements for each of the three ancillary services. The aggregators control a collection of devices that are geographically co-located and provide a platform to aggregate their flexibility and mitigate uncertainty associated with a single flexible load by managing a large aggregation of similar loads (so that any stochastic effects average out). Finally, DER controllers (for example, thermostats for air conditioners, chargers for electric vehicles) adjust the power consumption of individual devices to ensure accurate and reliable delivery of the requested grid services. Evaluation and validation of this approach was conducted with a mixture of simulation and hardware testing for a range of DERs in residential (air conditioners and water heaters), commercial HVAC (ventilation fans and central chiller plants), and micro-grids (battery energy storage, solar PV etc.). This culminated in DER hardware and simulation models operating in conjunction with grid simulations as part of a large scale federated test-bed demonstration. Simulations of over 10,000 controllable residential devices (a combination of air conditioners, water heaters, batteries, and electric vehicles) demonstrated that this advanced control approach could simultaneously meet all three grid services. Furthermore, hardware-in-the-loop testing was performed with operational micro-grid and commercial building HVAC equipment. The micro-grid equipment (representing PV, battery storage, and back-up generators) demonstrated the ability to meet all frequency response requirements (except ramping time). The commercial building HVAC ventilation equipment successfully provided the regulating response service. An Industry Advisory Board (IAB) was formed and engaged throughout the project to get feed-back on project risks and potential commercialization barriers. Their input was invaluable in identify key risks stemming from regulatory and market access challenges, financial risks from under-performance, and competitive threats from utility-scale solutions such as integrated storage. A phased commercialization plan was developed that addresses continued risk reduction (value proposition refinement and performance uncertainty assessments), piloting through field demonstrations with key stakeholders, and finally, deployment as an emerging standard for DER control.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Bidding Curve Design for Hybrid Power Plants with Uncertain Solar Forecast: Preprint

This paper presents a novel bidding curve design algorithm tailored for hybrid power plants (HPPs) to participate in the wholesale electricity market. Utilizing forecasts for photovoltaic (PV) generation and available battery power, our algorithm strategically computes the bidding curve to maximize HPP profit while adeptly managing the inherent uncertainty associated with PV power generation. In addition, the introduction of the penalty cost in HPP bidding curves provides the system operator a tool to effectively manage the system-level uncertainty that caused by HPPs. Numerical analysis through Monte Carlo simulations confirms that our bidding curve methodology outperforms the benchmark across various scenarios.

bidding curve↗
DOE OSTI2018

An Evaluation of Electricity Net Load Profiles and the Baseload Generation Concept

This paper investigates the amount of baseload generation that would be displaced due to renewable resources being implemented to meet state renewable portfolio standards (RPS) in the following regions: the Midwest Independent System Operator (MISO), the PJM regional transmission organization (RTO), the Electric Reliability Council of Texas (ERCOT), and the California ISO (CAISO). Modeling of these regions was done in Promod, a security constrained economic dispatch (SCED) model, for the years 2016-2030, to compare scenarios with and without the two primary intermittent renewable resources (solar and wind) attributable to the RPS regulations implemented in each state. In addition, a new statistical approach was developed for evaluating the variability in net load shapes caused by these two intermittent resources. The load variability index (LVI) was developed to apply to the hourly net load profiles for each day as a means of comparing variability in net loads.

14 SOLAR ENERGY↗
DOE OSTI2024

Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services

The project's primary objective is to develop a digital-twin based Photovoltaic (PV) Analysis and Response Support (PARS) platform, which aims to provide real-time situational awareness and optimal response plans. This platform is designed to enhance the performance of hybrid PV systems, making them competitive with or even superior to conventional generation resources. The PARS platform enabled the project team to develop and evaluate an extensive suite of grid support functionalities for the hybrid PV systems to enhance grid performance, across key areas including visibility, dispatchability, security, resilience, and reliability. Given the global push toward achieving 100% clean energy by 2035, there is a significant increase in the integration of inverter-based resources (IBRs) throughout the energy grid. Effectively managing the inherent variability and uncertainty associated with IBRs is crucial for ensuring cost-effectiveness, reliability, and security in both the main grid and islanded microgrids. Constrained to a limited array of IEEE test systems or standard feeder models, traditional IBR modeling struggles to assimilate new field data, accurately reflect system dynamics, and adapt to the evolving energy landscape. In our project, we embraced a Digital Twin (DT) strategy for crafting the PARS platform. A digital twin acts as a precise virtual counterpart of a physical system, built on historical data and continuously honed with real-time insights. This enables the high-fidelity DT to accurately mirror current system operations and forecast future scenarios. Consequently, the PARS platform becomes an ideal environment for testing and refining monitoring, control, power, and energy management algorithms designed to boost hybrid PV system performance. The defining feature of the PARS platform, distinguishing it from other advanced simulation tools, is its exceptional adaptability. This is achieved by employing actual network topologies and utilizing real-time field data for fine-tuning and calibration, ensuring a close emulation of real-world conditions. The project deliverables include: 1) High-fidelity IBR models and tools for real-time parameterization, utilizing real-time field measurements to refine IBR models for enhanced accuracy and performance; 2) Grid-forming and Grid-following capabilities to deliver resilience services, including blackstart, voltage and frequency support, cold-load pick-up, power reserves, and three-phase load balancing across grid-connected and microgrid settings; 3) Machine learning-based forecasting tools and methods for generating synthetic data and topologies, creating diverse and realistic simulation environments for evaluating varied operational scenarios; 4) Advanced microgrid power and energy management algorithms for optimizing the integration and operation of PV, storage, and demand response resources within both feeder and community scales. The power grid data sets are provided by four utility companies in North Carolina and the New York Power Administration. Acting as industry advisors, our industry partners communicated stakeholder needs and regulatory standards to the research teams, aiding technology transfer by incorporating the developed methodologies into their daily operations. This collaboration ensures that the PARS platform, functioning as a power system digital twin, enhances our understanding of IBR dynamic behaviors and enables the development and evaluation of IBR control functions that match or exceed the capabilities of conventional synchronous generators.

14 SOLAR ENERGY↗
DOE OSTI2024

Transitioning to Hybrid Power Plants

Hybrid power plants are power generation systems that combine two or more types of electricity generation or storage, creating systems where the optimal dispatch provides more benefits that the sum of the individual components can. These plants exemplify the interconnected challenges of grid modernization. On one hand, rapid increase in deployment and enhanced controllability of renewable energy assets is needed to meet clean energy targets, but on the other, increasing electrification makes it more difficult to manage load and growth in the number of endpoints and stakeholders involved with hybrid plants complicates asset management and cybersecurity. This talk will cover trends in hybrid power plant technologies and deployments, identify future prospects for hybrid systems, and discuss the challenges and research opportunities that exist to transition from the traditional power grids of today to smart, distributed, hybrid power grids we may see in the next few decades.

14 SOLAR ENERGY↗
DOE OSTI2024

Dispatching Grid-Forming Inverters in Grid-Connected and Islanded Mode: Preprint

This paper explores the dispatch-ability of grid-forming (GFM) inverters in grid-connected and islanded mode. Grid-forming (GFM) inverters usually use droop control to automatically share power with other GFM sources (inverters and synchronous generator (SG)) and follow the change of the load demand. However, they can be dispatched like their grid-following (GFL) counterparts to output the target active and reactive power. This will help the grid operator better manage their inverter-based resources (IBRs) for improved operation efficiency and reliability. Therefore, this paper proposes an innovative concept of dispatching GFM sources (inverters and SG) to output the target power for both grid-connected and islanded mode by adjusting their droop intercepts. The fundamental principle of doing so is that the GFM inverter's active and reactive power is dictated by its frequency and voltage, thus, dispatching active and reactve power of a GFM inverter can be achieved through dispatching its frequency and voltage. Moreover, the concept distinguishes the dispatch rules for grid-connected and islanded mode. Finally, the concept is validated with an example microgrid system with two GFM inverters, one diesel generator, one grid-following inverter and loads in both grid-connected and islanded mode. This pioneering work results in a practical guidance for power system energy management system (EMS) development to control a future grid with GFM and GFL inverters.

droop control↗
DOE OSTI2023

Conservation Voltage Reduction with Distributed Energy Resource Management System, Grid-Edge, and Legacy Devices: Preprint

Distribution utilities use conservation voltage reduction (CVR) to obtain energy savings and lower peak demand by reducing bus voltages. Traditionally, the CVR is accomplished by controlling the legacy assets such as load tap changers, voltage regulators, and capacitor banks. The deployment of the advanced distribution management system (ADMS) and distributed energy resource management system (DERMS) enables the integration of distributed energy resources into the distribution networks and provide the grid services including CVR. This paper studies the coordinated operation of an ADMS and a DERMS in achieving CVR and voltage regulation. A commercial ADMS uses legacy devices and Edge-of-Network Grid Optimization (ENGO) devices to obtain energy savings through CVR. A prototype DERMS dispatches the photovoltaic smart inverters based on real-time optimal power low to ensure voltage regulation across the feeder. The results show that the coordinated operation of ADMS and DERMS is effective in achieving CVR and voltage regulation. Specifically, energy savings of up to 4.7% are observed in the real utility distribution system used in this study.

advanced distribution management system↗
DOE OSTI2019

Analysis of Differential Financial Impacts of LWR Load-Following Operations. Revision 1

This document reports the application of HERON (Holistic Energy Resource Optimization Network), a newly-developed RAVEN (Risk Analysis Virtual ENvironment) plugin for grid and capacity optimization, to a case study conducted in collaboration with Arizona Public Service (APS). The study is a work in progress; this report presents a description of current models and corresponding results for a particular consideration. APS is anticipating several operational challenges. The first is rapid growth of Variable Renewable Energy (VRE) sources such as wind and solar power providing energy to the grid in the APS service region. This creates challenges for baseload operation of the Palo Verde Generating Station (PVGS), a nuclear power plant co-owned and operated by APS. The second challenge for APS is a change in the cooling water acquisition contract with the Sub Regional Operating Group (SROG). The existing contract is expiring soon, and a renewal is only available for a significantly higher price of water. These two challenges represent a difficulty in maintaining profitability for PVGS as local area demand is highly fluctuant and water prices may increase. Furthermore, excess production at PVGS is currently traded on the Palo Verde energy Hub (PVH), which occasionally offers very low or negative locational marginal prices (LMP) for electricity. This analysis considers the potential benefits of occasional curtailment of PVGS as a method to mitigate unprofitable production hours. Similar to load following, optional daily curtailment would allow APS to elect curtailment of PVGS as low as 70% of its nominal operating level between the hours of 08:00 and 16:00 provided local area demand is met and it is profitable to do so. This document reports a stochastic differential analysis of the Net Present Value (NPV) of PVGS as operated by NPS as a result of optional curtailment operation. To model this differential case, HERON has been designed from previous efforts in this study as a generic tool to accelerate the design and execution of RAVEN workflows for technoeconomic analysis of grid energy systems. HERON leverages both RAVEN and the CashFlow plugin for RAVEN to stochastically explore or optimize a response surface with energy grid system production capacities as inputs and mean NPV as a goal function. HERON performs these evaluations by stochastically sampling market, weather, and demand events using RAVEN’s ARMA reduced-order model capability to generate boundary conditions for dispatch optimization. The algorithm performs the dispatch optimization for each of the synthetic scenarios. For this case, HERON designs workflows to simulate behavior of the PVH, wind, solar, and APS local area demand, and use these synthetic scenarios to stochastically evaluate the differential benefit of optional curtailment for each scenario. While this study finds optional curtailment to be a potential source of revenue, the magnitude of the differential NPV is sufficiently small that it is unlikely a priority for increasing the profitability of PVGS. Further, the differential NPV shrinks throughout the simulated years, suggesting the long-term benefit of such operation given current assumptions is negligible.

14 SOLAR ENERGY↗