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WECC Variable Generation Planning Reference Book

This planning reference book is a document reflecting a Western Electricity Coordination Council (WECC) effort to put together multiple sources of information and provide a clear, systemic, comprehensive outline of the problems, both existing and anticipated; their impacts on the system; currently used and proposed solutions by the industry and research community; planning practices; new technologies, equipment, and standards; and expected future trends. This living (periodically updated) document could help WECC and other practicing engineers, especially the younger generation of engineers joining the workforce, to get familiar with a large variety of information related to the integration of variable resources into the WECC system, bypassing in part the need for time-consuming information gathering and learning processes from more experienced engineers or from the literature.

Electricity↗

Marine Hydrokinetic Energy Site Identification and Ranking Methodology Part I: Wave Energy

Marine hydrokinetic energy is a promising and growing piece of the renewable energy sector that offers high predictability and additional energy sources for a diversified energy economy. This report investigates the market opportunities for wave energy along the U.S. coastlines. It is part one of a two-part investigation into the United State's two largest marine hydrokinetic resources (wave and tidal). Wave energy technology is still an emerging form of renewable energy for which large-scale, grid-connected project costs are currently poorly defined. Ideally, device designers would like to know the resource conditions at economical project sites so they can optimize device designs. On the other hand, project developers need detailed device cost data to identify sites where projects are economical. That is, device design and siting are, to some extent, a coupled problem. This work describes a methodology for identifying likely deployment locations based on a set of criteria that wave energy experts in industry, academia, and national laboratories agree are likely to be important factors for all technology types. This work groups the data for the six criteria into 'locales' that are defined as the smaller of either the local transmission grid or a state boundary. The former applies to U.S. islands (e.g., Hawaii, American Samoa) and rural villages (e.g., in Alaska); the latter applies to states in the contiguous United States. These data are then scored from 0 to 10 according to scoring functions that were developed with input from wave energy industry and academic experts. The scores are aggregated using a simple product method that includes a weighting factor for each criterion. This work presents two weighting scenarios: a long-term scenario that does not include energy price (weighted zero) and a near term scenario that includes energy price. The aggregated scores are then used to produce ranked lists of likely deployment locales. In both scenarios, Hawaii and the Pacific Northwest (northern California, Oregon, and Washington) rank at the top of the lists. Hawaii ranks highest in the near-term scenario because it has high energy costs. In the long-term scenario, Oregon ranks highest because it has a large market and an energetic resource. Several East Coast states and Puerto Rico are also identified as potential wave energy deployment sites if technological innovations make it possible to efficiently generate electricity from the modest resource there. There are also several small-market sites in Alaska and U.S. Pacific Islands that rank particularly well in the near-term analysis due to their high energy prices. These locations may represent opportunities to demonstrate economical wave energy conversion as a stepping-stone to larger markets. Several factors that will affect wave project costs and siting have not been considered here -- including permitting constraints, conflicting use, seasonal resource variability, extreme event likelihood, and distance to ports -- because consistent data are unavailable or technology-independent scoring could not be identified. As the industry continues to mature and converge around a subset of device archetypes with well-defined costs, more precise investigations of project siting that include these factors will be possible. For now, these results provide a high-level guide pointing to the regions where markets and resource will one day support commercial wave energy projects.

16 TIDAL AND WAVE POWER↗

Marine Hydrokinetic Energy Site Identification and Ranking Methodology Part II: Tidal Energy

Marine hydrokinetic energy is a promising and growing piece of the renewable energy sector that offers high predictability and additional energy sources for a diversified energy economy. This report investigates the market opportunities for tidal energy along the U.S. coastlines. It is part one of a two-part investigation into the United States' two largest marine hydrokinetic resources (wave and tidal). Tidal energy technology is still an emerging form of renewable energy for which large-scale grid-connected project costs are currently poorly defined. Ideally, device designers would like to know the resource conditions at economical project sites so they can optimize device designs. On the other hand, project developers need detailed device cost data to identify sites where projects are economical. That is, device design and siting are, to some extent, a coupled problem. This work describes a methodology for identifying likely deployment locations based on a set of criteria that tidal energy experts in industry, academia, and national laboratories agree are likely to be important factors for all technology types. Several factors that will affect tidal project costs and siting have not been considered here -- including permitting constraints, conflicting use, seasonal resource variability, extreme event likelihood, and distance to ports -- because consistent data are unavailable or technology-independent scoring could not be identified. As the industry continues to mature and converge around a subset of device archetypes with well-defined costs, more precise investigations of project siting that include these factors will be possible. For now, these results provide a high-level guide pointing to the regions where markets and resource will one day support commercial tidal energy projects.

16 TIDAL AND WAVE POWER↗

Validation of Reanalysis-Based Offshore Wind Resource Characterization Using Lidar Buoy Observations

The offshore wind industry in the U.S. is gaining strong momentum to achieve sustainable energy goals, and the need for observations to provide resource characterization and model validation is greater than ever. Pacific Northwest National Laboratory (PNNL) operates two lidar buoys for the U.S. Department of Energy (DOE) in order to collect hub height wind data and associated meteorological and oceanographic information near the surface in areas of interest for offshore wind development. This work evaluates the performance of commonly used reanalysis products and spatial approximation techniques using lidar buoy observations off the coast of New Jersey and Virginia, USA. Reanalysis products are essential tools in order to set performance expectations and quantify the wind resource variability at a given site. Long-term accurate observations at typical wind turbine hub-heights have been lacking at offshore locations. Using wind speed observations from both lidar buoy deployments, biases and degrees of correspondence for the Modern Era Retrospective Analysis for Research and Applications-2 (MERRA-2), the North American Regional Reanalysis (NARR), and the analysis system of the Rapid Refresh (RAP) are examined both at hub height and near surface. Results provide insights on the performance and uncertainty of using reanalysis products for long-term wind resource characterization.

lidar buoy, model validation, offshore wind energy↗

Demonstration of a Variable Phase Turbine Power System for Low Temperature Geothermal Resources

A variable phase turbine assembly will be designed and manufactured having a turbine, operable with transcritical, two-phase or vapor flow, and a generator – on the same shaft supported by process lubricated bearings. The assembly will be hermetically sealed and the generator cooled by the refrigerant. A compact plate-fin heat exchanger or tube and shell heat exchanger will be used to transfer heat from the geothermal fluid to the refrigerant. The demonstration turbine will be operated separately with two-phase flow and with vapor flow to demonstrate performance and applicability to the entire range of low temperature geothermal resources. The vapor leaving the turbine is condensed in a plate-fin refrigerant condenser. The heat exchanger, variable phase turbine assembly and condenser are all mounted on single skids to enable factory assembly and checkout and minimize installation costs. The system will be demonstrated using low temperature (237F) well flow from an existing large geothermal field. The net power generated, 1 megawatt, will be fed into the existing power system at the demonstration site. The system will demonstrate reliable generation of inexpensive power from low temperature resources. The system will be designed for mass manufacturing and factory assembly and should cost less than $\$$1,200/kWe installed, when manufactured in large quantities. The estimated cost of power for 300F resources is predicted to be less than 5 cents/kWh. This should enable a substantial increase in power generated from low temperature geothermal resources.

15 GEOTHERMAL ENERGY↗

Investigation of onshore wind farm wake recovery with in situ aircraft measurements during AWAKEN

The share of wind power for electricity supply is increasing worldwide. This highly variable resource requires the improved prediction of power output for network stability. The interaction between wind farm wakes and the atmospheric boundary layer (ABL) introduces uncertainties in power production that warrant detailed investigation. The flow downwind of wind farms is characterized by a reduction in wind speed and an increase in turbulence, which both vary with atmospheric conditions. During the American WAKE experimeNt (AWAKEN), the Technische Universität Braunschweig conducted measurement flights with a research aircraft upwind and downwind of onshore wind farms in the southern Great Plains in Oklahoma in the USA. This study utilizes data from 20 flights conducted at approximately hub height in September 2023 to investigate the wind field variability downwind of the wind farms and vertical profiles to observe atmospheric stratification. The flights were aligned perpendicular to the main wind direction downwind of the King Plains and Armadillo Flats wind farms. Additionally, lidar data from both upwind and downwind ground-based measurement sites and sonic anemometer data were used for comprehensive analysis. Results indicate that under stable ABL conditions, the wake persists at greater downwind distances with a higher velocity deficit in the wake relative to the undisturbed flow compared to unstable stratification. In homogeneous terrain under stable conditions, wake recovery to 95 % occurs between a distance of 4.5 and 9 km downwind of the wind farm. In the semi-complex terrain characterized by shallow hills, slopes, and valleys, the wake exhibits a higher velocity deficit compared to homogeneous terrain, while in some cases the wake was amplified by the terrain resulting in higher velocity deficit 10 km downwind of the wind farm compared to the measurements closer to the wind farm. The turbulent kinetic energy (TKE) and “TKE difference” was found to be a valuable measure in understanding wakes in a semi-complex terrain, showing a clear wake recovery and formation depending on the stratification of the ABL.

17 WIND ENERGY↗

Storage Effectiveness in Enabling Variable Generation and Avoiding Fossil Emissions

In this paper, we investigate the relationship between storage and variable generation (VG) and how they can be used to replace fossil-fired technologies and their associated emissions. Unlike fossil generation, VG relies on variable resources (wind, solar, etc.), and the timing of these resources does not always match system needs, creating challenges both in terms of when energy is delivered and the reliability of that delivery. These challenges are typically addressed in one of two ways: paring VG with storage to provide firmed, time-shiftable energy or by building additional VG throughout an interconnection so that adequate amounts of VG are always available. The choice of how much to build of each (storage and VG) is typically an economic one. In this work, we focus on the former case - investigating the role of storage in bringing renewables onto the grid.

13 HYDRO ENERGY↗

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↗

Setting cost targets for zero-emission electricity generation technologies

Clean energy deployment scenarios typically assume a diverse mix of low-emission generation. However, because of historically low natural gas prices and cost reductions for onshore wind and photovoltaic technologies, recent new capacity deployment, especially in the United States, has come largely from these three generation sources. Here, we quantify competitive cost targets for three less-common zero-emission generation technologies -- nuclear, concentrating solar, and offshore wind -- under a range of future conditions. We determine the cost targets based on the technologies' system value, such that technology value equals or exceeds its cost. Using a capacity expansion model that develops system-wide, economically optimal generation scenarios of the United States power sector, we find that nuclear, concentrating solar, and offshore wind would need to attain levelized cost ranges of $53-84/MWh, $65-91/MWh, and $39-77/MWh, respectively, to achieve 1% additional grid penetration. We refer to this metric as the 'required cost,' which is a technology's levelized cost of energy needed to achieve a specific penetration level. Higher penetrations lead to lower required costs as lower-cost generation is displaced. We estimate that to reach 10% penetration, the required cost for nuclear declines to $45-76/MWh. Because of resource variability and increased transmission needs for concentrating solar power and offshore wind, even lower costs are needed to reach higher penetrations: required cost ranges to achieve 10% penetration are estimated to be $30-56/MWh and $18-40/MWh for these two technologies respectively. Our analysis informs research and development priorities and the design of policies supporting clean technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Distributed Wind-Hybrid Microgrids with Autonomous Controls and Forecasting

Distributed wind-hybrid microgrids have the potential to provide key resilience and economic benefits to both the customers they serve and the utility grids they are connected to. Such microgrids will likely be a key part of the grid of the future, whether connected to large utility grids or linked together in multi-microgrid systems. Through the hybridization of distributed wind and solar photovoltaics, autonomous device-level and system-level controls, battery energy storage systems with smart inverters, and forecasting, these microgrids could maintain local stability and provide grid services - all with renewable power. In the literature, these elements have been considered individually. However, they have not been combined and demonstrated at a high fidelity, which is essential to prove the concept's operation before moving to hardware-in-the-loop and physical demonstrations. In this work, we develop a high-fidelity MATLAB-Simulink model of a real distributed wind-hybrid microgrid that includes all these elements. We demonstrate the microgrid maintaining stability and production in a variety of islanded, grid-connected, and transition scenarios. This includes riding through faults and grid transitions, handling resource variability, and providing grid services. The results demonstrate, at a high fidelity, how distributed wind-hybrid microgrids can operate in an economic and resilient fashion. Finally, we provide recommendations for future research to move advanced distributed wind-hybrid microgrids toward deployment.

ancillary services↗

Identifying recharge sources and their impacts on a North Central New Mexico shallow aquifer using unsupervised machine learning

In this article, shallow aquifers are important but highly variable resources in arid to semi-arid regions. Limited shallow aquifer volume results in high sensitivity to recharge fluctuations, which can impact the local fauna and flora, and transport of contaminants in the aquifer or vadose zone. Aquifer response to external forcing (e.g., precipitation) is usually solved by estimating aquifer parameters and running physics-based models to match known fluctuations of hydraulic head. However, this technique is time and computationally expensive. Furthermore, high aquifer complexity decreases precision in physics-based models. Alternatively supervised machine learning is used to predict aquifer dynamics. However, these techniques rely on input data and struggle to interpret aquifer response for missing sources (i.e., snowpack data). To counter these problems, we propose an unsupervised machine learning technique (NMFk) to estimate the impact of different sources on aquifer recharge. NMFk is used to understand the influence of external forcing on shallow aquifer recharge in the Pajarito Plateau (Los Alamos, NM, USA). The results show how NMFk can be used to reduce the data dimension in a complex field dataset to three recharge signals that cause fluctuations within the field data. Here, the source signals are interpreted as rainfall, snowmelt, and a delayed aquifer response to the previous two signals. These results evidence how heterogeneous aquifers delimited by canyons incised into the Pajarito Plateau respond in similar ways to the source signals identified by NMFk. Furthermore, results show the importance of the local geology where faults act as sinks, and anthropogenic disturbances can facilitate infiltration amplifying the interpreted signal.

54 ENVIRONMENTAL SCIENCES↗

Understanding Biases in Pre-Construction Estimates

The pre-construction energy generation of a wind farm (P50) is difficult to estimate and evaluate. This paper presents a methodology to measure the accuracy of the p50 prediction, which we call the Historical Validation Survey (HVS), for several wind farms in the continental United States. Our results indicate that there is a bias between predicted and measured energy, even when controlling for factors like grid curtailment and resource variability. We also find that our results depend on the assumptions we make during analysis, which we quantify with a sensitivity analysis. This method allows the estimation of uncertainty we have in our findings. When we account for reasonable ranges of model assumptions, we find that, in the most optimistic case, there is still a bulk -5.5% bias when estimating pre-construction energy generation. When controlling for grid curtailment this number reduces to a range of -3.5 to -4.5%.

17 WIND ENERGY↗

Distribution Model Creation using Circuit Maps for Applied PV Impact Studies

Photovoltaic (PV) generation is becoming increasingly common on power distribution systems. The output fluctuations of this variable resource necessitate the creation of an accurate model to ensure that any adverse impacts to the distribution system are properly addressed. To reduce model creation time, a method of extracting data from AutoCAD drawings using scripted methods was developed. This paper will present a distribution model creation and validation process, document case studies of evaluating the impact of PV interconnections on utility distribution feeders, and discuss future applications. PV integration was found to be easier on 23 kV circuits compared to 4.16 kV circuits.

integrated circuit modeling↗

A Novel Secondary Frequency Regulation with Optimal Priority Selection of AGC Contributions

Automatic generation control (AGC) is used to maintain acceptable frequencies during operation owing to fluctuations in load and variable resources. In conventional industry applications, the AGC signal is allocated to each generator according to the predispatched frequency regulation capacity or the order of economic efficiency. However, with the increasing integration of inverter-based resources (IBRs), the retirement of conventional synchronous generators (SGs) has posed new challenges to frequency control schemes because fewer of them are optional for AGC regulation. In this paper, we propose a novel model predictive control (MPC)-based frequency regulation model to reduce control cost and ensure stability, by considering different critical dynamic factors when optimally selecting the AGC units. The proposed control model – developed in a general form – comprehensively embeds characteristics such as generator ramping rates, reserve capacity, and operation cost. The model predictive control–based two-timescale AGC scheme enhances the capability of immunizing the power disturbance from types of resources by coordinating the control signals between faster IBRs and slower SGs. The case study’s proposed model is verified to be effective in synergistically enforcing different dynamic properties of AGC units into the frequency regulation scheme.

Jiang, Sufan [The University of North Carolina at ↗

Distributed MPC for Efficient Coordination of Storage and Renewable Energy Sources Across Control Areas

In electric power systems, multiple entities are responsible for ensuring an economic and reliable way of delivering power from producers to consumers. With the increase of variable renewable generation it is becoming increasingly important to take advantage of the individual entities' (and their areas') capabilities for balancing variability. Hence, in this paper, we employ and extend the approximate Newton directions method to optimally coordinate control areas leveraging storage available in one area to balance variable resources in another area with only minimal information exchange among the areas. The problem to be decomposed is a model predictive control problem including generation constraints, energy storage constraints, and AC power flow constraints. Singularity issues encountered when formulating the respective Newton-Raphson steps due to intertemporal constraints are addressed and extensions to the original decomposition method are proposed to improve the convergence rate and required communication of the method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Hawaii Utility Integration Initiatives to Enable Wind (Wind HUI) (Final Technical Report)

To advance the state and nation toward clean energy, Hawaii is pursuing an aggressive Renewable Portfolio Standard (RPS), 40% renewable generation and 30% energy efficiency and transportation initiatives by 2030. Additionally, with support from federal, state and industry leadership, the Hawaii Clean Energy Initiative (HCEI) is focused on reducing Hawaii's carbon footprint and global warming impacts. To keep pace with the policy momentum and changing industry technologies, the Hawaiian Electric Companies are proactively pursuing a number of potential system upgrade initiatives to better manage variable resources like wind, solar and demand-side and distributed generation alternatives (i.e. DSM, DG).

17 WIND ENERGY↗

Large Customers Group: Report-out Presentation [Slides]

Targets for demand response load participation provide market certainty for sellers, CSPs, and investment in supporting technology. Bigger RPS and resulting variable resources lead to market demand.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimization of a Virtual Power Plant to Provide Frequency Support.

Increasing the penetration of distributed renewable sources, including photovoltaic (PV) sources, poses technical challenges for grid management. The grid has been optimized over decades to rely upon large centralized power plants with well-established feedback controls, but now non-dispatchable, renewable sources are displacing these controllable generators. This one-year study was funded by the Department of Energy (DOE) SunShot program and is intended to better utilize those variable resources by providing electric utilities with the tools to implement frequency regulation and primary frequency reserves using aggregated renewable resources, known as a virtual power plant. The goal is to eventually enable the integration of 100s of Gigawatts into US power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗