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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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DOE OSTI2022

North Carolina Water Utility Builds Resilience with Distributed Energy Resources

As the frequency and duration of grid outages increase, backup power systems are becoming more important for ensuring that critical infrastructure continues to provide essential services. Most facilities rely on diesel generators, which may be ineffective during long outages owing to limited fuel supplies and high generator failure rates. Distributed energy resources such as solar, storage, and combined-heat-and-power systems, coupled with on-site biofuel production, offer an alternative source of on-site generation that can provide both cost savings and resilience (i.e., the ability to respond to catastrophic events with longer-term consequences). A mixed-integer linear program minimizes costs and maximizes resilience at a wastewater treatment plant in Wilmington, North Carolina. We find that the plant can reduce life-cycle energy costs by 3.1% through the installation of a hybrid combined-heat-and-power, photovoltaic, and storage system. When paired with existing diesel generators, this system can sustain full load for seven days while saving $664,000 over 25 years and reducing diesel fuel use by 48% compared with the diesel-only solution. This analysis informed a decision by the Cape Fear Public Utility Authority to allocate funds for the implementation of a combined-heat-and-power system at the wastewater treatment plant in fiscal year 2023. Finally, the benefits of deploying hybrid combined-heat-and-power technologies and the utilization of on-site biofuel production extend, on a national scale, to thousands of wastewater treatment facilities and other types of critical infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Hybrid Power Plants: Status of Operating and Proposed Plants, 2023 Edition [Slides]

Improving battery technology and the growth of variable renewable generation are driving a surge of interest in “hybrid” power plants that combine, for example, wind or solar generating capacity with co-located batteries. While most of the current interest involves pairing photovoltaic (PV) plants with batteries, other types of hybrid or co-located plants with wide-ranging configurations have been part of the U.S. electricity mix for decades. This annually updated briefing tracks and maps existing hybrid or co-located plants across the United States while also synthesizing data from power purchase agreements (PPAs) and generation interconnection queues to shed light on near- and long-term development pipelines. The scope includes “co-located hybrids” that pair two or more resources (e.g., multiple types of generation and/or generation with storage) that are operated largely independently behind a single point of interconnection, and “full hybrids” that also feature coordinated operations of the co-located resources. The focus is on plants with one megawatt (MW) or more of capacity; smaller (often behind-the-meter) projects are also increasingly common, but are not included in this data synthesis. Key findings from the latest briefing include: -At the end of 2022, there were 374 hybrid plants (>1 MW) operating across the United States (+25% compared to the end of 2021), totaling nearly 41 GW of generating capacity (+15%) and 5.4 GW/15.2 GWh of energy storage (+69%/+88%). PV+storage plants are by far the most common, dominating in terms of plant number (213), storage capacity (4.0 GW/12.5 GWh), storage:generator capacity ratio (49%), and storage duration (3.1 hours). But there are nearly twenty other hybrid plant configurations as well, including several different fossil hybrid categories (each dominated by the fossil component) as well as wind+storage, wind+PV, wind+PV+storage, geothermal+PV, and others. -Last year was another strong year for PV+storage hybrids in particular: 59 of the 62 hybrids added in 2022 were PV+storage. As of the end of 2022, there was roughly as much storage capacity operating within PV+storage hybrid plants as in standalone storage plants (~4 GW each). In storage energy terms, however, PV+storage edged out standalone storage by ~2 GWh (12.5 GWh vs. 10.4 GWh, respectively). -Interconnection queue data show continued strong developer interest in hybridization. At the close of 2022, there were 51% more hybrid plants—representing 59% more generating capacity—in interconnection queues across the United States than there were at the end of 2021. Solar dominates these proposed plants as well: at the close of 2022, there were 457 GW of solar capacity proposed as a hybrid (representing ~48% of all solar capacity in the queues), most typically pairing PV with battery storage. At the same time, there were 24 GW of wind capacity proposed as a hybrid (representing ~8% of all wind capacity in the queues), again most-often pairing wind with storage. Meanwhile, more than half of all storage in the queues is estimated to be part of a hybrid plant. While many of the plants proposed in the queues will not ultimately reach commercial operations, the depth of interest in hybrid plants—especially PV+storage—is notable, particularly in certain regions. For example, in CAISO, 97% of all solar capacity and 45% of all wind capacity in the queues is proposed as a hybrid. -The report also surveys power purchase agreement (PPA) price data from a sample of operating and proposed PV+storage plants. Though PV+storage PPA prices have fallen over time, “levelized storage adders” have recently increased somewhat to ~$\$ $7000/MW-month, ~$\$ $60/MWh-stored (assuming one full cycle per day), or ~$\$ $15/MWh-PV. Some of the recent price increase could simply reflect a trend towards higher battery:PV capacity ratios over time, which increases costs, all else being equal. The well-publicized impact of inflationary and supply chain pressures on battery prices is no doubt a contributor as well.

25 ENERGY STORAGE↗
DOE OSTI2024

Hybrid Power Plants: Status of Operating and Proposed Plants, 2024 Edition [Slides]

Improving battery technology and the growth of variable renewable generation are driving a surge of interest in “hybrid” power plants that combine, for example, wind or solar generating capacity with co-located batteries. While most of the current interest involves pairing photovoltaic (PV) plants with batteries, other types of hybrid or co-located plants with wide-ranging configurations have been part of the U.S. electricity mix for decades. This annually updated briefing tracks and maps existing hybrid or co-located plants across the United States while also synthesizing data from power purchase agreements (PPAs) and generation interconnection queues to shed light on near- and long-term development pipelines. The scope includes “co-located hybrids” that pair two or more resources (e.g., multiple types of generation and/or generation with storage) that are operated largely independently behind a single point of interconnection, and “full hybrids” that also feature coordinated operations of the co-located resources. The focus is on plants with one megawatt (MW) or more of capacity; smaller (often behind-the-meter) projects are also increasingly common, but are not included in this data synthesis.

14 SOLAR ENERGY↗
DOE OSTI2022

Hybrid Power Plants: Status of Operating and Proposed Plants, 2022 Edition [Slides]

Falling battery prices and the growth of variable renewable generation are driving a surge of interest in “hybrid” power plants that combine, for example, wind or solar generating capacity with co-located batteries. While most of the current interest involves pairing photovoltaic (PV) plants with batteries, other types of hybrid or co-located plants with wide-ranging configurations have been part of the U.S. electricity mix for decades. This annually updated briefing tracks and maps existing hybrid or co-located plants across the United States while also synthesizing data mined from power purchase agreements (PPAs) and generation interconnection queues to shed light on near- and long-term development pipelines. The scope includes co-located hybrid plants that pair two or more generators and/or that pair generation with storage at a single point of interconnection, and full hybrids that feature co-location and co-control. The focus is on plants with one megawatt (MW) or more of capacity; smaller (often behind-the-meter) projects are also increasingly common, but are not included in this data synthesis. Key findings from the latest briefing include: -At the end of 2021, there were nearly 300 hybrid plants (>1 MW) operating across the United States, totaling nearly 36 gigawatts (GW) of generating capacity and 3.2 GW/8.1 GWh of energy storage. PV+storage plants are by far the most common, dominating in terms of plant number (140), storage capacity (2.2 GW/7.0 GWh), storage:generator ratio (53%), and storage duration (3.2 hours). But there are nearly twenty other hybrid plant configurations as well, including several different fossil hybrid categories (each dominated by the fossil component) as well as wind+storage, wind+PV, wind+PV+storage, geothermal+PV, and others. -Last year was a breakout year for PV+storage hybrids in particular: 67 of the 74 hybrids added in 2021 were PV+storage. By the end of 2021, there were more GW of battery capacity installed in PV+storage hybrids (2.2 GW) than as standalone storage plants (1.8 GW). The difference is even starker in energy terms, with PV+storage plants hosting twice as much battery capacity as standalone storage plants (7 GWh vs. 3.5 GWh, respectively). Much of the battery capacity added in hybrid form in 2021 was a battery retrofit to a pre-existing PV plant. -Data on plants under development from the interconnection queues of all seven ISOs/RTOs plus 35 individual utilities suggest that these hybridization trends are likely to continue. At the close of 2021, there were more than 670 GW of solar plants in the nation’s queues; 285 GW (~42%) of this capacity was proposed as a hybrid, most typically pairing PV with battery storage (PV+storage represented nearly 90% of all hybrid capacity in the queues). For wind, 247 GW of capacity sat in the queues, with 19 GW (~8%) proposed as a hybrid, again most-often pairing wind with storage (wind+storage represented ~4% of all hybrid capacity in the queues). Meanwhile, nearly half of all storage in the queues is estimated to be part of a hybrid plant. While many of these proposed plants will not ultimately reach commercial operations, the depth of interest in hybrid plants—especially PV+storage—is notable.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Environmental Co‐Benefits of Maintaining Native Vegetation With Solar Photovoltaic Infrastructure

Abstract Co‐locating solar photovoltaics with vegetation could provide a sustainable solution to meeting growing food and energy demands. However, studies quantifying multiple co‐benefits resulting from maintaining vegetation at utility‐scale solar power plants are limited. We monitored the microclimate, soil moisture, panel temperature, electricity generation and soil properties at a utility‐scale solar facility in a continental climate with different site management practices. The compounding effect of photovoltaic arrays and vegetation may homogenize soil moisture distribution and provide greater soil temperature buffer against extreme temperatures. The vegetated solar areas had significantly higher soil moisture, carbon, and other nutrients compared to bare solar areas. Agrivoltaics in agricultural areas with carbon debt can be an effective climate mitigation strategy along with revitalizing agricultural soils, generating income streams from fallow land, and providing pollinator habitats. However, the benefits of vegetation cooling effects on electricity generation are rather site‐specific and depend on the background climate and soil properties. Overall, our findings provide foundational data for site preservation along with targeting site‐specific co‐benefits, and for developing climate resilient and resource conserving agrivoltaic systems.

14 SOLAR ENERGY↗
DOE OSTI2025

A review of Geological Thermal Energy Storage for seasonal, grid-scale dispatching

Energy storage is essential for the decarbonization of the U.S. energy grid, especially with the increasing deployment of variable renewable energy sources like solar and wind. Geological thermal energy storage (GeoTES) has emerged as a promising long duration, grid scale solution, providing stability and security through flexible operations and valuable grid services. GeoTES utilizes subsurface reservoirs to store thermal energy for power generation and direct-use heating and cooling. This approach significantly enhances the use of low-temperature reservoirs, which would otherwise be unsuitable for geothermal power plants. It also aligns well with depleted oil and gas reservoirs, concentrating solar power, non-flexible renewables (photovoltaic and wind), and geothermal-related power cycles. Given the favorable marginal costs of GeoTES as storage duration increases, it becomes particularly competitive for seasonal, grid-scale dispatch, where few technologies are viable. This paper provides a comprehensive review of GeoTES systems and the research underpinning itsr development. This analysis begins by defining and categorizing the unique characteristics of thermal energy storage techniques, setting GeoTES apart from other technologies. The various components, configurations, subsurface characteristics, and modeling efforts that guide GeoTES development are then explored. Finally, challenges in GeoTES research, development, and deployment are discussed, along with mitigation strategies and lessons from related technologies. Beyond their economic benefits, GeoTES systems support grid resilience and decarbonize industrial processes. Their scalability, broad distribution, seasonal storage potential, and flexible dispatch capacity make GeoTES a valuable tool for expanding renewable energy deployment and addressing climate change.

15 - GEOTHERMAL ENERGY↗
DOE OSTI2022

FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data

The growth of the photovoltaic market has pushed the demand for power forecasting and performance evaluation for a huge population of PV power plants. Many of these power plants have spatiotemporal coherence that can be utilized for improving model accuracy. We have demonstrated in this paper the FAIRification of spatiotemporal PV time series data. Through the creation of a solar power plant ontology, we propose standards for the naming and structure of metadata used to describe the data from these power plants. Using the structure from this ontology, we have developed both R and Python packages for the automation of the FAIRification process. Going further, we have also developed an R package that automates the analysis of the quality of a data set through the designation of letter grades. To solve the issue of data missingness, we propose the use of St-GNN autoencoders to detect and impute missing values from a data set by utilizing data from power plants nearby.

14 SOLAR ENERGY↗
DOE OSTI2022

FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data

The ongoing growth of the photovoltaic market has pushed the demand for power forecasting and performance evaluation for a huge population of PV power plants. Through access to a large number of time series data sets from different power plants, we have found common issues that impede the modeling process. Namely, the time series data are hard to transfer between groups due to differences in variable nomenclature, and the quality of the data sets can vary. We address the issue of variable nomenclature by FAIRifying spatiotemporal PV time series data. Through the creation of a solar power plant ontology, we propose standards for the naming and structure of metadata used to describe the data from these power plants. Using the structure from this ontology, we have developed both R and Python packages for the automation of the FAIRification process. We have also developed an R package that automates the analysis of the quality of a data set through the designation of letter grades. With access to large time series data sets across many power plants, we can utilize spatiotemporal coherence between the sites in order to improve the quality of our data. To solve the issue of data missingness, we propose the use of Spatiotemporal-GNN autoencoders to detect and impute missing values from a data set by utilizing data from power plants nearby.

14 SOLAR ENERGY↗
DOE OSTI2023

Optimal Sizing and Dispatch of Solar Power with Storage

Designers of utility-scale solar plants with storage, seeking to maximize some aspect of plant performance, face multiple challenges. In many geographic locations, there is significant penetration of photovoltaic generation, which depresses energy prices during the hours of solar availability. An energy storage system affords the opportunity to dispatch during higher-priced time periods, but complicates plant design and dispatch decisions. Solar resource variability compounds these challenges, because determining optimal system sizes requires simultaneously considering how the plant will be operated under the imposed market and weather conditions. We develop an approach to analyze the economic performance of hybrid and single-technology solar power plants, which incorporates optimal dispatch, and considers the expected electricity market and weather conditions. We utilize the System Advisor Model software package to simulate the operation of multiple renewable generation and energy storage technologies, in conjunction with hourly-fidelity generation decisions determined by a revenue-maximizing, mixed-integer linear program. We show that, under our assumed market and weather conditions, the lifetime benefit-to-cost ratio can be improved by 6 to 19 percent, relative to a baseline design without optimizing, and that a concentrating solar power with thermal energy storage design produces significantly more energy per year, but is less profitable under our cost assumptions.

black-box optimization↗
DOE OSTI2020

Detection and Localization of Damaged Photovoltaic Cells and Modules Using Spread Spectrum Time Domain Reflectometry

The operating efficiency of photovoltaic (PV) plants can be improved if damaged or degraded modules can be detected and identified. Currently, string-level power electronics can detect problems with modules or cabling but not locate them, which would facilitate addressing these issues. Here, we investigate the ability of spread spectrum time domain reflectometry (SSTDR) to both detect and locate/identify damaged cells and modules within a series-connected PV string. We tested the ability of SSTDR to detect and locate single-cell mini-modules and full-sized PV modules, which were intentionally damaged by impacts with a hammer (breaking the glass and damaging the silicon below) or by cutting through some or all busbars. Damage to the glass and silicon of cells was detected and located within a small string of minimodules. Busbar damage was detectable only if an open was created by cutting through all intercell busbars. Furthermore, physical impact damage to the glass and silicon of a full-sized PV module could be detected, but further development of signal processing is needed to achieve localization of such damaged modules within a string.

14 SOLAR ENERGY↗
DOE OSTI2021

A Technical and Economic Assessment of LWR Flexible Operation for Generation and Demand Balancing to Optimize Plant Revenue

With increased penetration of subsidized variable renewable energy (VRE) resources and competition from low natural gas prices, existing light water reactor (LWR) nuclear power plants (NPPs) are struggling to remain economically competitive. This work examines the potential economic competitiveness of various thermal energy storage (TES) technologies when coupled directly or indirectly with a NPP. To highlight their relative economic competitiveness, we contrast several energy storage solutions in stochastic dispatch optimization. We leverage data from recent work analyzing a range of TES technologies with varying capital costs, performance, and technology readiness level (TRL) to establish our case. We explore inserting these technologies into an electricity market with existing nuclear generation and large projected variable renewable energy (VRE) penetration. Although these technologies' projected capital costs may make them unlikely candidates in their current state, this analysis demonstrates a high-fidelity techno-economic analysis of energy storage. Furthermore, as the projected cost of energy storage technologies evolves, this analysis sets a precedent for similar future investigations. One region with projected trends that may be unfavorable for existing nuclear capacity is the New York Independent System Operator (NYISO) market. New York state’s baseload generation has been historically provided by fossil-fired and nuclear assets. However, amid economic pressures from subsidized VREs and low natural gas prices, the state has recently deactivated Indian Point nuclear power plant units 2 and 3. Furthermore, the state plans to meet its zero-emission generation target by 2040 by replacing fossil-fired capacity with significant investments in VRE resources like wind and solar photovoltaic (PV) and battery storage. Increased intermittent resource penetration lowers the baseload power requirement, adding further economic pressure to the state’s three remaining NPPs still in operation. With three NPPs still in operation in New York, this work analyzes potential economic benefits to NPPs on the New York grid when directly or indirectly coupled with various TES technologies. This work requires two modeling steps to analyze the potential economic benefits of various system configurations of the TES directly or indirectly coupled with nuclear. First, this analysis leverages capacity expansion modeling by experts at the Electric Power Research Institute (EPRI). Using their deterministic capacity expansion model, U.S. Regional Economy, Greenhouse Gas, and Energy (US-REGEN), EPRI analysts evaluated the capacity and generation evolution of the New York state energy market under four projection scenarios. These four projection scenarios were developed to represent the potential evolution of the capacity and generation in NYISO from 2015 to 2050 under various economic, technology, and policy constraints. The results from these capacity expansion models are then used as boundary conditions in the second modeling step. The second modeling step uses the Holistic Energy Resource Optimization Network (HERON) for a set of stochastic techno-economic analyses (STEAs) to investigate the potential increase in the economic viability of various configurations of the TES. With no current capacity expansion capabilities, HERON takes the data generated from US-REGEN for 2050 to generate synthetic load, solar, and wind data. Then HERON economically optimizes the capacity and dispatch of the various TES configurations. The potential economic benefit is the differential net present value (NPV) of the TES configurations from the no-TES baseline. As a stochastic techno-economic analysis package, HERON introduces uncertainty into the economic metrics, while US-REGEN trades resolution for reduced computational complexity. Using HERON also allows the modeling of direct thermal coupling, a feature not common in capacity and dispatch models. As expected, with high capital costs, the costs of introducing energy storage for all the technologies considered outweighed the potential economic benefit of this strategy for flexible plant operation. The benefit of this analysis is primarily in demonstrating a workflow that examines innovative solutions to increase NPP revenue via TES coupling. HERON’s stochastic capacity and dispatch optimization process used in this work has proven an effective tool in observing and evaluating the impact of introducing storage technologies in a grid energy system.

25 ENERGY STORAGE↗
DOE OSTI2021

Field Accelerated Stress Testing (FAST): Forecasting Plant-specific Failure Modes and Degradation Rates

Photovoltaic plant owners and insurance companies would like to be prepared for the forthcoming material warranty claims (material defects) and power warranty claims (degradation rate). To address the needs of these stakeholders, this presentation aims to introduce a new conceptual approach to perform accelerated testing right at the field of interest and it is called field accelerated stress testing (FAST). The primary goal of this presentation is to present a conceptual approach to forecast the field specific failure modes and degradation rates in advance by a factor of 2 to 5, right at the plant site using a few spare modules available at the plant location itself.

14 SOLAR ENERGY↗
DOE OSTI2022

Arbitrage and Capacity Firming in Coordination with Day-Ahead Bidding of a Hybrid PV Plant: Preprint

A hybrid PV plant (HPP) combines a photovoltaic (PV) plant with a battery energy storage system (BESS), which is considered a promising step towards the future of renewable power plants by the U.S. Department of Energy. When the renewable penetration reaches a significant level, a hybrid PV plant can bid in as a controllable thermal plant in the future electricity market. In this study, a bidding and BESS scheduling model is proposed for the HPP. The robust optimization (RO) technique has been utilized to identify the worst-case scenario of uncertainties during the bidding process. To address the overly conservative issue of the single-stage RO, we have decoupled the BESS schedule for arbitrage and PV capacity firming by a two-stage RO formulation. By comparing the output of single-stage RO and two-stage RO, the two-stage RO bids and schedules in a more aggressive manner, which increases the income of HPP. Also, the penalty of under-generation is considered in our model so that the day-ahead bidding decision and arbitrage schedules can be adjusted based on the potential UNDER-GENERATION penalty. Because the proposed model is non-convex and contains multi-stages, the Column-and-Constraint Generation (C&CG) algorithm is applied to the model as the solution. The proposed model has shown better economic performance compared to a state-of-art single-stage bidding method in case studies.

BESS scheduling↗
DOE OSTI2020

Luminescent Enhancement for Combined Solar and Commercial Agriculture. Final Report

This proposal will develop a new racking / mounting system combined with a new agriculture-tuned luminescent solar panel for low cost high tunnel implementation to produce both crops and electricity for small local farms. Crop trials performed under this specialized panel/racking system can be extended to open field agriculture with standard utility scale racking system in phase II. The US agricultural industry uses about 300 billion KW-hr of energy / year. Of this energy consumption, roughly 20% goes towards food production and 20% goes towards food processing. This proposal will allow farm land to simultaneously generate electricity, food AND provide jobs. Employment is one of the largest hurdles for the introduction of solar into rural areas. The ability to provide agricultural jobs in addition to solar energy from a plot of land will pave the way for greater adoption of photovoltaics in rural areas. A cost effective and highly durable hybrid power generating high tunnel greenhouse will be developed that generates electricity at less than $2.50/watt INSTALLED cost and can be used for crop production of high values crops. The high tunnel will use a new design of Soliculture greenhouse integrated luminescent solar panels to selectively absorb the green portion of the solar spectrum that is not used by plants and convert the light to red light with higher photosynthetic efficiency and to enhance power output of solar cells. Green light is selectively downshifted to red light using luminescent materials that match the photosythetically active region for plants and the efficiency maximum of Si photovoltaic cells. The color tuning associated with converting green light to red light has been shown to facilitate fruit production in commercial greenhouses growing cucumbers, lettuce and herbs.

14 SOLAR ENERGY↗
DOE OSTI2021

Impact of High Penetration Distributed Energy Resources on the Bulk Electric System

The growth of distributed energy resources (DERs), mostly generation using intermittent renewable energy sources, along with the retirement of central generation (mostly conventional power plants using fossil-fuel-based resources) has implications for the steady-state and dynamic performance of the bulk electric system (BES). Among the DERs connected to the distribution system, photovoltaic (PV) systems are the most prevalent and have been installed at an increasing rate. Until recently, the penetration levels of DERs have not been high enough to create significant impacts on the reliability and security of power system operation. However, in recent years, the penetration levels of DERs have risen to a level that their impacts on the bulk electric system should be considered in a detailed fashion in planning and operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Electromagnetic Transient Simulation of Large-Scale Inverter-Based Resources With High-Granularity

The power grid is undergoing a significant transformation with the rapid increase in inverter-based resources (IBRs), including large-scale photovoltaic (PV) plants. Ensuring reliable and resilient grid operation in this new paradigm necessitates high-granularity electromagnetic transient (EMT) modeling that accurately captures the behavior of individual inverters and their interactions within IBR plants. Central to this approach is the detailed representation of both the IBR plant’s collector system and the dynamics of individual inverters. To achieve this, a high-granularity EMT model of a large-scale PV plant has been developed using advanced simulation algorithms, including matrix splitting and the Schur complement. These proposed techniques significantly enhance simulation speed, numerical stability, and accuracy while improving the modularity and efficiency of the collector system’s representation. The effectiveness of the proposed methods is validated through simulations of a representative large-scale PV plant consisting of 125 individual PV inverters, 25 IBR unit transformers, and a 52-bus collector system.

Choi, Jongchan [Oak Ridge National Laboratory (ORN↗
DOE OSTI2020

Distributed Minimization of the Power Generation Cost in Prosumer-Based Distribution Networks: Preprint

Traditionally, electrical power was generated in big power plants. The cost of producing energy was related to the cost of fuel, e.g., carbon or gas, and by the cost of maintaining the power plants. With the advent of distributed energy resources, power can be produced directly at the edge of the electrical network by a new type of agents: the prosumers. Prosumers are entities that both consume and generate power, e.g., by means of photovoltaic panels. The cost of the power produced by prosumers is no longer related to fuel consumption since energy coming from distributed generators is essentially free. Rather, the cost is related to the remuneration that is due to the prosumers for the services they provide. The proposed control strategy minimizes the active power generation cost in the aforementioned scenario. The control scheme requires that the prosumers measure their voltage and then adjust the amount of injected power, according to a continuous time feedback control law that is indeed a projected gradient descent strategy. Simulations are provided in order to illustrate the algorithm behavior.

distributed control↗