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DOE OSTI2023

Voltage Support With PV Inverters in Low-Voltage Distribution Networks: An Overview

Large solar photovoltaic (PV) penetration using inverters in low voltage (LV) distribution networks may pose several challenges, such as reverse power flow and voltage rise situations. These challenges will eventually force grid operators to carry out grid reinforcement to ensure continued safe and reliable operations. However, smart inverters with reactive power control capability enable PV systems to support voltage quality in the distribution network better. Here, this paper gives an overview of the current state-of-the-art control strategies for handling voltage problems through PV inverters and other devices. In addition, the (control) technical issues of PV systems integrated into the LV distribution network are considered from a control point of view. By comparing the control issues of PV integration into the grid, the paper aims to help distribution system operators to expand the volume of PV generation in the distribution system in an efficient and safe manner. Additionally, it will help control engineers and researchers select proper control strategies for PV systems as well as other distributed renewable sources.

42 ENGINEERING↗

DOE OSTI2024

Integrate Latimer Controls' Solution into RTAC (CRADA Final Report, CRD-23-24672)

Latimer Controls, Inc. was awarded two vouchers under the Department of Energy's American-Made Solar Prize Round 6 to conduct collaborative research at a national laboratory. The National Renewable Energy Laboratory (NREL) was selected as a partner to assist Latimer Controls in the performance evaluation of its photovoltaic (PV) control software. This collaboration focuses on developing a hardware-in-the-loop (HIL) testbed at NREL, which will be used to test and validate the Latimer PV control technology in a realistic yet de-risked environment. Both Latimer and NREL teams will work together to analyze the collected test data, derive insights, and disseminate the scientific findings. Recent studies underscore the potential of solar energy as a zero-marginal-cost and zero-emission flexibility resource within the bulk power system, particularly when integrated with advanced control systems. To enhance the performance of such systems, Latimer Controls has developed leading-edge technologies, including machine learning (ML) algorithms and hierarchical inverter set-point allocation methods. These innovations are designed to estimate the operational headroom of large PV plants for grid integration and control. However, comprehensive validation under real-world conditions remains necessary. To address this gap, the concurrent CRADA project proposes the real-world application and validation of the Latimer Control solution within a HIL environment. Initially, the Latimer algorithm was developed and tested within MATLAB Simulink, a platform suitable for research-level simulations and iterative development. However, transitioning this technology to a real solar site as an industry-ready solution necessitates implementation in a format compatible with widely used solar power plant controllers. In this additional CRADA work, the MATLAB Simulink-based logic will be translated into Structured Text, a programming language compliant with IEC 61131 standards, which is commonly used for custom logic implementations in industry-leading programmable logic controllers (PLCs), such as the Schweitzer SEL real-time automation controller (RTAC). This transition will facilitate the deployment of the Latimer Control solution in real-world solar power plants, thereby advancing the technology towards commercialization.

14 SOLAR ENERGY↗

DOE OSTI2025

Cost-optimized energy storage operation for a grid-connected solar PV system at community and individual scales

This study provides a comparative analysis of grid-connected PV-integrated battery storage at individual and community scales. The paper addresses the challenge of managing energy demand-generation mismatch by using a battery energy storage optimization algorithm, which minimizes operational costs while accounting for battery degradation. Also, this work introduces a broader evaluation basis that includes seasonal variability, grid exchange smoothness, and scalability across different battery capacities. Results show that community-scale storage more effectively dampens grid exchange power fluctuations and reduces system costs, particularly with moderate price differences between electricity buying and selling prices and low battery capacities. The paper also analyzes the impacts of static control versus cost-optimized battery system management. Here, it is shown that the gap in system costs between the cost-optimized and static control scenarios widens as the price difference increases.

25 ENERGY STORAGE↗

DOE OSTI2024

A Comprehensive Strategy for Grid Forming Control in DC Coupled Photovoltaic and Battery Energy Storage Inverters

This paper presents an integrated DC-DC and DCAC grid-forming control strategy for DC-coupled photovoltaic (PV) plus battery energy storage systems, considering the effect of DC link voltage variations caused by direct PV connections. A power reference algorithm determines power distribution between the PV and battery to the grid while observing device power ratings to prevent the over-rating of components and keep the battery's state of charge within an acceptable range. The simulated utility-scale model in MATLAB/Simulink illustrates its ability against extreme phase angle variation contingencies in the grid while controlled through grid-forming control with a fast dynamic on DC link voltage. The simulation results confirm the effectiveness of the proposed control in integrating PV plus battery configurations with grid forming control and maintaining reliable grid operation under severe grid disturbances.

battery, boost, control, energy storage, grid form↗

DOE OSTI2022

Generating Sequential PV Deployment Scenarios for High Renewable Distribution Grid Planning

This paper introduces a novel approach for generating solar photovoltaic (PV) plant deployment scenarios for grid integration planning. The approach guarantees consistency among scenarios of the same deployment by ensuring that higher penetration scenarios contain PV units deployed in lower penetration scenarios. It also constrains the size and spatial distribution of the PV plants and considers three placement types. A case study on a real-world distribution system proves that the precepts of scenario consistency, deployment diversity, and placement are met. The study further investigates the impact of the resulting scenarios via a stochastic hosting capacity analysis. Results indicate that the ratio between PV and load sizes, referred to as the nodal PV penetration factor (NPPF), is a key driver of the grid integration impact. By reducing the NPPF from 5 to 2, the maximum hosting capacity increased by at least 112%. The study also reveals that scenarios under random placement can lead to higher hosting capacity values.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

DOE OSTI2022

Generating Sequential PV Deployment Scenarios for High Renewable Distribution Grid Planning: Preprint

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

DOE OSTI2021

High-Fidelity Models and Fast EMT Simulation Algorithms for Isolated Multi-port Autonomous Reconfigurable Solar power plant (MARS)

The integration of hybrid photovoltaic (PV) and energy storage system (ESS) based plants has become a promising way of solving the intermittency of PV plants and providing frequency support to the power grid. The multi-port autonomous reconfigurable solar power plant (MARS) can integrate the PV systems and ESSs to an ac grid and dc lines. The proposed isolated MARS incorporates an isolated converter that connects to the PV arrays and is based on the dual active bridge (DAB) converter. The high frequency switching in the DAB and the means to control the DAB converter using delays between switching signals lead to the need for a small timestep in simulations. Moreover, several hundreds of modules that include a DAB converter are present in the MARS. The small timestep and the presence of several hundreds of modules lead to a significant rise in the overall simulation time. To address this issue, simulation algorithms like numerical stiffness-based hybrid discretization and the hysteresis relaxation technique are applied to the switched system model of isolated MARS. Additionally, an event-driven interpolating method is introduced to help increase the minimum timestep to simulate the conventional DAB converter model while maintaining high accuracy in the simulation results. The developed model is validated by comparison with its reference model built in the PSCAD/EMTDC and MATLAB software environments using library components.

Xia, Qian↗

DOE OSTI2020

Duty-Cycle Predictive Control of Quasi-Z-Source Modular Cascaded Converter Based Photovoltaic Power System

A duty-cycle predictive control is proposed for dc grid integration of front-end isolated quasi-Z-source modular cascaded converter (qZS-MCC) photovoltaic (PV) power system. The post-stage qZS half-bridge dc-dc converter deals with PV maximum power point tracking, dc grid integration, and dc-link voltage balance; whereas, the front-end isolation converters operate at a constant duty cycle of 50%. Thus, it saves control hardware resources while overcoming challenges from PV-panel voltage variations and dc-bus voltage limit. The proposed control uses the derived circuit model to predict the global active-state duty cycle for grid-connected current control and predict the shoot-through duty cycles for dc-link voltage balance, achieving a fast and accurate tracking target. The proposed control method has advantages of: i) eliminating weighting factors that exist in conventional model predictive control (MPC), ii) no sophisticated loop parameters design that exists in proportional-integral (PI) control, iii) operating at constant switching frequency that is different from the conventional MPC with variable switching frequency. Simulation and experimental tests are carried out to verify the effectiveness of the proposed control method and compare with the PI-based control system.

42 ENGINEERING↗

DOE OSTI2024

Overview and Commentary on Applying the Coordinated Vulnerability Disclosure Process to Photovoltaic System Devices

The rapid expansion of photovoltaic (PV) systems, particularly inverters, has introduced new cybersecurity challenges that threaten both local operations as well as the broader electrical grid’s stability. PV inverters, integrated into critical energy infrastructure are potential targets for cyber attacks due to vulnerabilities in firmware, remote access systems, and communication protocols. The Coordinated Vulnerability Disclosure (CVD) process, as defined by the Cybersecurity and Infrastructure Security Agency (CISA), provides a framework for identifying, reporting, and addressing these vulnerabilities in a transparent and collaborative manner. This report outlines the CVD process as it applies to PV systems, detailing the roles of key stakeholders, such as manufacturers, grid operators, and security researchers. The report also highlights specific challenges in managing vulnerabilities for new and legacy PV systems, which includes those introduced by insecure communications and third-party supply chain components. By adhering to the CVD process, the PV industry can mitigate cybersecurity risks, ensure regulatory compliance, and maintain consumer trust, while safeguarding the operational resilience of the energy grid. Ultimately, the effective coordination of vulnerability management is crucial for securing the future of PV systems within the critical electric grid infrastructure landscape.

14 SOLAR ENERGY↗

DOE OSTI2021

Resampling and data augmentation for short-term PV output prediction based on an imbalanced sky images dataset using convolutional neural networks

Integrating photovoltaics (PV) into electricity grids is challenged by potentially large fluctuations in power generation. In recent years, sky image-based PV output prediction using convolutional neural networks (CNNs) has emerged as a promising approach to forecasting fluctuations. A key challenge is imbalanced sky image datasets: because of the geography of solar PV system installations, sky image datasets are often rich in sunny condition data but deficient in cloudy condition data. This imbalance contrasts with the fact that model errors are dominated by cloudy condition performance. In this study, we attempt to remedy this by exploring the enrichment and augmentation of an imbalanced sky images dataset for two PV output prediction tasks: nowcasting (predicting concurrent PV output) and forecasting (predicting 15-minute-ahead future PV output). We empirically examine the efficacy of using different resampling and data augmentation approaches to create a rebalanced dataset for model development. A three-stage greedy search is used to determine the optimal resampling approach, data augmentation techniques and over-sampling rate. The results show that for the nowcast problem, resampling and data augmentation can effectively enhance the model performance, reducing overall root mean squared error (RMSE) by an average of 4%, or a 15 std. (standard deviation) of improvement compared to the variability of the baseline model. In contrast, the treatment RMSE for the forecast problem nearly always overlaps the baseline performance at the ± 2 std. level. The optimal resampling approach expands on the original dataset by over-sampling the minority cloudy data, with the best results from large over-sampling rate (e.g., 4 ~ 6 times over-sampling of cloudy images).

14 SOLAR ENERGY↗

DOE OSTI2021

Photovoltaic (PV) System Levelized Cost of Energy (LCOE) Evaluation with Grid Support Function Valuation and Service Lifetime Estimation

Photovoltaic (PV) systems play a critical role in renewable energy resource grid integration, and levelized cost of energy (LCOE) is commonly used to evaluate PV system feasibility in modern power grids. In this work, a revised PV system LCOE calculation model is derived to quantify the potential of LCOE reduction. Particularly, the grid support functions are valuated to offset the investment and operation costs of PV systems, which thereby reduces the LCOE. Meanwhile, PV system service lifetime is also estimated with the derived PV inverter reliability model, considering the critical components (i.e., semiconductor devices and capacitors). The case studies with field datasets are conducted to validate the effectiveness of the developed LCOE calculation model.

Zhao, Shijia↗

DOE OSTI2020

Detection and Diagnosis of Data Integrity Attacks in Solar Farms Based on Multilayer Long Short-Term Memory Network

Photovoltaic (PV) systems are becoming more vulnerable to cyber threats. In response to this emerging concern, developing cyber-secure power electronics converters has received increased attention from the IEEE Power Electronics Society that recently launched a cyber-physical-security initiative. Here this letter proposes a deep sequence learning based diagnosis solution for data integrity attacks on PV systems in smart grids, including dc–dc and dc–ac converters. The multilayer long short-term memory networks are used to leverage time-series electric waveform data from current and voltage sensors in PV systems. The proposed method has been evaluated in a PV smart grid benchmark model with extensive quantitative analysis. As a comparison, we have evaluated classic data-driven methods, including K-nearest neighbor, decision tree, support vector machine, artificial neural network, and convolutional neural network. Comparison results verify performances of the proposed method for detection and diagnosis of various data integrity attacks on PV systems.

42 ENGINEERING↗

DOE OSTI2021

Optimal Sizing of an Electric Vehicle Charging Station with Integration of PV and Energy Storage

This paper proposes an optimization model for the optimal configuration of an grid-connected electric vehicle (EV) extreme fast charging station considering integration of photovoltaic (PV) and energy storage. The proposed model minimizes the annualized net cost (i.e., maximizes the annualized net profit) of the extreme fast charging station, including investment and maintenance cost of charging ports, PV and energy storage, net cost of purchasing energy from utility and selling energy to EV customers, degradation cost of energy storage and demand charge. The decision variables are number of charging ports, capacity of invested PV and the power and energy ratings of invested energy storage. The Erlang-loss system is adopted to model the EV mobility. Results of numerical simulations indicate that investment of PV and energy storage could increase the annualized profit of the extreme fast charging station. In addition, the impacts of various parameters on the optimal solution are investigated by sensitivity analysis.

Liu, Guodong↗

DOE OSTI2022

Discrete and Integrated Solutions for Hybrid PV Plants Without Momentary Cessation in Low SCR and High Penetration PE Grids

With the increased penetration of power electronic (PE) based loads and sources, advanced solutions may be required for the enhancement of grid stability in regions with low short circuit ratio (SCR) and high penetration PE grids. The requirement of advanced solutions arises from the gradual paradigm shift of the electric grid from the traditional electric machine dominant system to a high penetration of PE-based system. One of the major challenges with such systems in recent times is the momentary cessation during alternating current (ac) grid transmission faults. During momentary cessation, PE-based resources cease to operate, thus creating probable reliability challenges for the grid. In this paper, potential feasible options to provide continuity of operation during such scenarios are presented. The options are considered through identifying upgrades in existing and upcoming discrete development of photovoltaic (PV) and energy storage systems (ESS) termed as discrete hybrid PV plants. Additionally, an advanced concept of integrated development of PV and ESS connecting to ac transmission grid links called multi-port autonomous reconfigurable solar power plant (MARS) is evaluated. The developed new solutions are evaluated for different grid use cases and scenarios in PSCAD.

Marthi, Phani Ratna Vanamali↗

DOE OSTI2023

Performance Evaluation of Next-Generation Grid Automation and Controls with High PV Penetration

This paper presents a hardware-in-the-loop (BIL) simulation to evaluate the performance of an advanced grid automation architecture, referred to as data-enhanced hierarchical control (DEHC), in achieving voltage regulation and conservation voltage reduction (CVR) in distribution networks with very high photovoltaic (PV) generation. This architecture comprises an advanced distribution management system (ADMS), a distributed energy resource management system (DERMS), and grid-edge devices working synergistically to provide the grid benefits. The HIL setup used for the evaluation includes ADMS, DERMS, and grid-edge devices. The DEHC performance is evaluated in two representative scenarios considering loose and tight constraints of the power factor at the substation. The results show that the DEHC architecture is effective in achieving voltage regulation and CVR and thus enables the grid integration of high levels of PV generation.

ADMS↗

DOE OSTI2021

Quantifying the Solar Energy Resource for Puerto Rico

After Hurricane Maria, multiple U.S. Department of Energy laboratories studied the state of the electric grid in Puerto Rico and analyzed grid resilience and grid integration of renewable energy. As part of the work done at the National Renewable Energy Laboratory, researchers created new solar resource data, conducted a technical potential and supply curve analysis, and studied the interannual variability of the solar resource. A new methodology was developed to downscale solar resource data from the National Solar Radiation Data Base (NSRDB) from a 4-km x 4-km spatial and 30-minute temporal resolution to a 2 km x 2 km and 5-minute resolution. This methodology primarily used simple physical principles to develop high-resolution cloud properties which were then used to compute solar radiation. The high-resolution datasets were validated against ground measurements and the error metrics were found to be similar to the original lower resolution dataset. Using 20 years of downscaled data from the NSRDB multi-year capacity factors for photovoltaics (PV) were developed for both single-axis tracking and fixed latitude-tilt configurations. Use of the multi-year data provides the ability to understand variability in capacity factors due to variability in weather over a long period of time. For Puerto Rico the coastal regions were found to have significant higher capacity factors than inland. Using land-use and terrain information a technical potential analysis was conducted for Puerto Rico. This analysis restricted single PV plant development to a maximum of 100 MW nameplate capacity. The nameplate capacity for each municipality were then determined. Based on our assumptions, 56 of the 78 total municipalities of Puerto Rico contain some level of solar capacity. Most of the interior municipalities did not have any capacity because of the geographic exclusions used in this study. The lowest capacity for a PV plant observed in a municipality was 10 MW. The maximum capacity within a county was 2,000 MW. Further a supply curve analysis was conducted by taking the results of the technical potential and quantifying system and transmission costs. The levelized cost of energy (LCOE) was calculated for each theoretical PV plant site, and the levelized cost of transmission was added to the LCOE to produce a total cost estimate for each site. The results of the supply curve analysis allow for a relative comparison of the cost for integrating new PV capacity into the grid. This analysis indicates that cheaper total LCOE sites tend to be larger in capacity. The total capacity in this study was found to be far beyond the maximum peak load for the island. However, this study does not consider the economic and market potential for development. The cumulative capacity presented in this study assumes that the best locations are developed first and ignores the complex decision paths for new power plant development. Therefore, this analysis can only be treated as illustrative. Finally this study investigates the impact of inter-annual variability of resource using a variety of metrices including probability of exceedance and variation in capacity factor and LCOE. This study demonstrates that the capacity factor or LCOE could vary by over 10% year to year. This clearly indicates the risks involved in using any particular year of data and clearly points to the use of multi-year data to reduce some of the risks related to variability in weather.

14 SOLAR ENERGY↗

DOE OSTI2022

Providencia Island White Papers: Hawaii, USA: A Grid Planning Case Study for Providencia Island, Colombia

Special considerations exist for island grids seeking to smoothly integrate distributed energy resources (DERs), such as rooftop photovoltaics (PV), with an existing fossil fuel-based grid without compromising system stability and reliability. Hawaii, having successfully integrated nonconventional renewable energy sources for a hybrid electricity grid, may serve as a guide for technical specifications and interconnection policy. Island grid planners may seek to follow Hawaii's example by standardizing technical specifications of generators, particularly for advanced inverter components.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Providing Ancillary Services with Photovoltaic Generation in Multi-Timescale Grid Operation: Preprint

With photovoltaic (PV) generation substantially increases, electric power systems need more flexible resources that can provide ancillary services to mitigate the variability and uncertainty of the PV generation. On the one hand, the increase of PV generation necessitates the needs of more flexible resources. On the other hand, PV generation, because of its low operation cost, has been replacing the conventional generation in the system which is the main flexible resources in the current system. Consequently, there is a trend to require the renewable generation including PV to provide flexible ancillary services to further accommodate more PV integration. This paper proposes a multi-timescale grid operation model considering the various control strategies of PV providing different ancillary services. Numerical case studies demonstrate that with PV providing both regulation reserve and primary frequency reserve, the system operating costs and PV curtailment will be reduced significantly. It shows that not only the system reliability but also PV's profitability can be improved with PV providing more ancillary services.

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