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At least 1,063 records · Page 59

Optimal Economic Dispatch and Load-Following Strategies for Nuclear Integrated Energy Systems

The need for distributed and adaptable energy resources that can handle the growing unpredictability in both supply and demand is rising as the power system continues to modernize. In order to satisfy those needs and maintain grid resilience, nuclear power plants can dynamically control their output, despite typically being used as baseload generators. By incorporating energy storage and renewable energy sources, nuclear integrated energy systems are designed to satisfy the electrical and thermal demands of different end-user applications while ensuring flexible power operation. These systems generate revenue by participating in both wholesale and ancillary services electricity markets, as well as commodity markets for various byproducts generated from coupled industrial processes. This study addresses the economic dispatch efficiency of a tightly coupled nuclear integrated energy system comprising a gigawatt-scale light water reactor, commercialized in the U.S., a high-temperature steam electrolysis unit, a district heating network, and specified electrical loads. To demonstrate the nuclear power plant’s flexibility within the day-ahead unit commitment and economic dispatch framework, while maintaining equilibrium even during periods of refueling outages, this paper develops a mixed-integer linear programming framework that models the subsystems and components of its nuclear steam supply system. A systematic comparative analysis of flexible versus baseload nuclear power plant operation under varying levels of renewable energy integration indicates that flexible operation enhances system profitability by more than 18% while also increasing energy storage utilization, improving reactor responsiveness to load fluctuations, and allowing for greater participation across numerous electricity markets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A Combined Day-ahead and Real-time approach for Scheduling Real and Reactive power dispatch of Battery Energy Storage System

A combined day-ahead (look-ahead) and real-time optimization approach is proposed to schedule BESS real and reactive power dispatch. The look ahead scheduling agent maximizes profit and essentially performs the function of energy arbitrage by looking at forecasted prices, network constraints and BESS operating conditions to generate real power dispatch schedule. While this schedule is followed, the real time optimization agent computes an optimum reactive power set-point (for a particular objective function) using optimal power flow framework. The concepts are implemented by co-simulating legacy tools and demonstrated on a large real world distribution system. In addition to the profits from energy arbitrage, optimum reactive power set point computation results in achieving desirable network attributes like flat voltage profiles and minimizing voltage deviations from desired value.

Bhatti, Bilal A.↗

PNNL DSSE Docker Image

This is the docker image for Pacific Northwest National Laboratory's DSSE (distribution system state estimator) used for the demo of OEDI-SI platform. To support the operation of modern distribution systems, operators require real-time visibility into system states. Due to a lack of measurements and unbalanced operation, the state estimation in distribution systems is challenging. This submission is related to an OEDI-SI use case which demonstrates the application of an extended Kalman filter-based state estimator on an IEEE-123 bus system. The state estimator uses the measurements to generate voltage estimates for the system.

Array↗

Simulation of the Multi-Wake Evolution of Two Sandia National Labs/National Rotor Testbed Turbines Operating in a Tandem Layout

The future of wind power systems deployment is in the form of wind farms comprised of scores of such large turbines, most likely at offshore locations. Individual turbines have grown in span from a few tens of meters to today’s large turbines with rotor diameters that dwarf even the largest commercial aircraft. These massive dynamical systems present unique challenges at scales unparalleled in prior applications of wind science research. Fundamental to this effort is the understanding of the wind turbine wake and its evolution. Furthermore, the optimization of the entire wind farm depends on the evolution of the wakes of different turbines and their interactions within the wind farm. In this article, we use the capabilities of the Common ODE Framework (CODEF) model for the analysis of the effects of wake–rotor and wake-to-wake interactions between two turbines situated in a tandem layout fully and partially aligned with the incoming wind. These experiments were conducted in the context of a research project supported by the National Rotor Testbed (NRT) program of Sandia National Labs (SNL). Results are presented for a layout which emulates the turbine interspace and relative turbine emplacement found at SNL’s Scaled Wind Technologies Facility (SWiFT), located in Lubbock, Texas. The evolution of the twin-wake interaction generates a very rich series of secondary transitions in the vortex structure of the combined wake. These ultimately affect the wake’s axial velocity patterns, altering the position, number, intensity, and shape of localized velocity-deficit zones in the wake’s cross-section. This complex distribution of axial velocity patterns has the capacity to substantially affect the power output, peak loads, fatigue damage, and aeroelastic stability of turbines located in subsequent rows downstream on the farm.

Baruah, Apurva (ORCID:0000000252354068)↗

Estimated Hourly Electricity Demand Profiles for Each County in the Contiguous United States

In this data descriptor, we present hourly electricity demand estimates for each county in the contiguous United States from 2016 to 2023. The demand profiles represent the sum of two components for each county. The first is the weighted average of reported hourly demand profiles for North American Electric Reliability Corporation balancing authority (BA) regions and subregions, scaled to match annual estimates of county-level retail sales and direct use of electricity and weighted by the estimated percentage of county load served by each BA region or subregion. The second is the weighted average of modeled hourly, county- and sector-level distributed photovoltaic (DPV) capacity factor profiles, scaled to match annual estimates of on-site consumption of DPV-generated electricity for each county and weighted by the percentage of consumption attributable to each sector.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Restoration Strategy for Active Distribution Systems Considering Endogenous Uncertainty in Cold Load Pickup

Cold load pickup (CLPU) phenomenon is identified as the persistent power inrush upon a sudden load pickup after an outage. Under the active distribution system (ADS) paradigm, where distributed energy resources (DERs) are extensively installed, the decreased outage duration can induce a strong interdependence between CLPU pattern and load pickup decisions. In this paper, we propose a novel modelling technique to tractably capture the decision-dependent uncertainty (DDU) inherent in the CLPU process. Subsequently, a two-stage stochastic decision-dependent service restoration (SDDSR) model is constructed, where first stage searches for the optimal switching sequences to decide step-wise network topology, and the second stage optimizes the detailed generation schedule of DERs as well as the energization of switchable loads. Further, to tackle the computational burdens introduced by mixed-integer recourse, the progressive hedging algorithm (PHA) is utilized to decompose the original model into scenario-wise subproblems that can be solved in parallel. The numerical test on modified IEEE 123-node test feeders has verified the efficiency of our proposed SDDSR model and provided fresh insights into the monetary and secure values of DDU quantification.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Advanced Distributed Wind Turbine Controls Series: Part 1-Flatirons Campus Model Overview – Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL)

Wind turbines are typically deployed to provide energy, reduce diesel-fuel consumption, reduce carbon emissions, and reduce costs for energy and fuel transportation. However, in addition to solely providing energy to the power system, wind turbines contain rotating masses and inverter-based controls that can enable various reliability and resilience services through advance controls. As part of the Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL), it is demonstrated that advanced wind turbine controls can be employed to support higher contributions of wind, and to demonstrate ways that wind can play a role in supporting grid stability in islanded or grid-connected configurations. This paper documents models of various subsystem comprising a portion of NREL's Flatirons campus that will be used in three subsequent reports to demonstrate capabilities of advanced wind turbine controls. The series of reports will detail advanced capabilities of distributed wind turbines to provide support to isolated grids, distribution grids, and microgrids. We developed models to simulate a wind turbine (600 kW), solar PV (430 kW), battery energy storage system (1 MW/1MWh), a diesel generator (2 MW) and various types of loads (critical, dynamic). The model of the subsystems in MATLAB/Simulink are validated with available data from real-world components on NREL's Flatirons Campus. These validated models can be configured for various studies including four MIRACL use cases: 1) isolated grids, 2) microgrids, and 3) behind-the-meter, and 4) front-of-the-meter wind turbine deployments.

17 WIND ENERGY↗

A baseline for ensemble-based, time-resolved inflow reconstruction for a single turbine using large-eddy simulations and latent diffusion models

We are interested in reconstructing winds flowing through a turbine on a second-by-second basis over a 10 min window. Previously, we developed a machine learning algorithm that takes in a snapshot of wind speed measurements and generates ensembles of three-dimensional wind field estimates. Here, we use these estimates as initial conditions in large-eddy simulations and reconstruct atmospheric and turbine response dynamic quantities in a synthetic field campaign. In doing so, we establish a baseline for model validation that future time-aware data assimilation techniques will be compared to. In turbine-free case studies, ground truth wind speeds consistently fall within our estimated wind speed distribution for the first 100 s after the simulation start. In simulations with turbines, the wind estimates show a small bias of 0.10 m s 1 and good correlation of 0.80 during the first 100 s. During this window, our estimates of the Blade 1 bending moment and generator power typically span the ground truth, with the estimate of the former performing better overall. In summary, this approach shows promise as a stand-alone technique for reconstructing real-world inflow and turbine dynamics in 1-2 min windows and as a foundation for future time-aware data assimilation techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SPATIOTEMPORAL TRACKING OF WIDE AREA POWER OUTAGE FROM NIGHT-TIME LIGHT IMAGERY

Monitoring progress of power restoration following extreme events is essential for situational awareness about spatio-temporal distribution of populations without power and to help with response efforts. Because of the proprietary nature of restoration data, and the difficulty in obtaining power outage data from utility companies in near real-time (e.g., during hurricane Maria (2017)), this project used satellite derived nighttime lights data from Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) to (i) monitor wide area power outage and (ii) estimate impacted customers over time to assist with restoration. A discussion of the methodology and its implementation during hurricanes Maria (2017) and Eta (2020) is presented in this paper. Future work will focus on calibrating estimated customers based on light intensity and density distribution, and generation of restoration profiles for emergency response.

Kar, Bandana↗

The Challenges of Modeling Distributed Energy Resources (DERs) as Blackstart Resources and for Volt-VAR Optimality

Modeling, testing and instituting Distributed Energy Resources (DERs) as Blackstart Resoucrces presents several challenges due to the fundamental differences between traditional black start resources (e.g., large generators) versus DERs like solar PV systems with battery storage. This paper addresses some of these key challenges. These include intermittency of coordinating DERs to provide continuous power during a black start event, especially during extended periods of cloud cover or when battery energy storage is depleted. This paper additionally addresses the collapsing voltage and stability control challenges specific to maintaining bulk power system stability during black start synchronization These physical and engineering limitations require careful engineering design, modeling and engineering to ensure that DERs can support critical loads and substations during black start events. A variety of additional challenges also exist. Additionally, there are challenges associated with feeder location and low voltage secondary system impacts on DER functions and settings. We compare typical functions and settings for DERs for power factor control and correction. We also demonstrate how voltag control via Volta-VAR power factor correction can be done

Mukherjee, Srijib↗

A Data-Driven Algorithm for Enabling Delay Tolerance in Resilient Microgrid Controls Using Dynamic Mode Decomposition

The increased implementation of smart grid technologies in the power distribution grid presents unique opportunities that enable resiliency, but also brings challenges motivating needs for novel solutions and mitigation techniques. The bi-directional power and data flow allow for the grid to operate with increased resiliency, which is the ability to avoid discontinuity of service to end-use loads during extreme events. However, in applications where control of the distribution grid or microgrid relies on communication networks, the degradation of communication systems in the form of loss or high latency can cause maloperation and result in loss of end-use loads. Here this paper presents a novel framework to enable delay tolerance of centralized microgrid control schemes to mitigate communication system latency impacts and guarantee successful control action. We demonstrate the delay tolerance on a control scheme that operates a battery energy storage system (BESS) to offset the sudden loss of generation and maintain system frequency. During periods of severely degraded communication system performance, the proposed delay-tolerant algorithm compensates for the latency by utilizing a data-driven model generated at the device level using dynamic mode decomposition (DMD) to determine the performance of the communications. The DMD technique predicts the system’s frequency using device-level terminal measurements and provides updated control signals. The HELICS cosimulation platform evaluates the cyber-physical interaction of the power system model in GridLAB-D, the centralized control agent in Python, and the discrete network model in NS-3. The framework is tested and validated on the IEEE-123 node system modified to represent a networked remote microgrid model, and the results show an improvement in the dynamic performance

24 POWER TRANSMISSION AND DISTRIBUTION↗

Converter-Interfaced CHP Plant for Improved Grid-Integration, Flexibility and Resiliency

GE Research and its partner GE Renewables have proposed the use of an interface converter solution to increase the penetration of small to medium-sized CHP (1MWe to 20MWe) into distribution grids and improve their flexibility and grid support capability. Indeed, the proposed interface converter solution thanks to presence of the grid-ready inverter, allows to streamline the compliance to grid codes requirements, reduce the interconnection delays and costs and ultimately one of the main barriers for CHP adoption by commercial and industrial facilities. An additional benefit provided by the interface converter is the use of the grid-ready inverter for reactive power which eliminates the need of sizing the generator for that capability. These two benefits highly favor the economic feasibility of converter-interfaced CHP. Five user cases, each in one of the leading U.S states for CHP potential reported by the DOE in its estimation of the U.S Technical Potential of CHP, were selected to compare the economic performances of converter-interfaced CHP as compared with directly-coupled. They include a college campus in California, a hospital in New York, a water reclamation plant in Texas, a hotel in Minnesota, and a large office building in Pennsylvania. Results showed that, the presence of the interface converter allows to increase the return on investment (ROI) by 0.5 to 2 percentage points in most of the cases (4 of 5). Indeed, the interface converter by shortening the interconnection process allows to accelerate revenues while reducing interconnection costs. Added to the reduced cost of the required generator these savings trade favorably the capital cost of the converter. The analysis also showed that the profitability of the converter-interfaced CHP is highly sensitive to the energy price, interconnection delay, and converter cost. However, it appears that if the interface converter can shorten the interconnection process by at least 6 months, adopting this solution will be more economically viable than directly-coupled configuration in almost all the +23,000 sites of the U.S Technical Potential CHP. The evaluation of the benefits of a converter-interfaced CHP also showed that it enables higher ROI when coupled with other distributed energy resources (DER) such as battery energy systems (BESS) or solar photovoltaic (PV). Indeed, in those scenario, the grid-ready inverter included in the interface converter eliminates the need of separate inverters if DC-coupling is used. On the technical performance, it has been verified that the presence of the interface converter allows to reduce by 70% to 80% the CHP short-circuit contribution to grid faults. This not only reduces the mechanical and thermal stresses exposed to the CHP electrical components but also increases the grid hosting capacity which ultimately enables higher penetrations CHP. Another key benefit of the interface converter validated with hardware-in-the-loop simulations and testing is its superior capability for reactive power support. Indeed, using a power hardware testbed with two +700kW inverters configured in back-to-back, a microgrid controller and actual facilities loads it was demonstrated that the presence of the interface converter can help maintain a power factor near ~1 or regulate the voltage to ~1.0pu at the point of common coupling. This benefit can be highly valuable if in the future, due to higher penetration of renewable distributed energy resources (DER), utilities start billing demand charge based on kVA instead of kW as currently. It was also validated that converter-interfaced CHP can dispatch heat and power commands and seamlessly switch between the two modes while consistently controlling the power factor or voltage at PCC. Indeed, the power hardware testing showed that grid-connected converter-interfaced CHP can follow either the power or heat demand while maintaining a unity power factor at converter output. This research proved that the adoption of an interface converter as the solution for interconnection of CHP system into the distribution grid can greatly improve the economic feasibility of small to medium-sized CHP as well as the plant power quality, flexibility and resiliency. Additionally, it allows increased penetrations of CHP into the distribution grid, extends their grid support capability, and facilitates the integration of BESS and PV DER by streamlining their collocation within the same facilities. This ultimately provides an opportunity for commercial and small industrial facilities in the U.S to accelerate their energy transition thanks to the high energy efficiency of CHP systems and its reliable, flexible, and resilient microgrid operation when interconnected with an interface converter.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Reinforcement Learning Approach to Parameter Selection for Distributed Optimal Power Flow

With the increasing penetration of distributed energy resources, distributed optimization algorithms have attracted significant attention for power systems applications due to their potential for superior scalability, privacy, and robustness to a single point-of-failure. The Alternating Direction Method of Multipliers (ADMM) is a popular distributed optimization algorithm; however, its convergence performance is highly dependent on the selection of penalty parameters, which are usually chosen heuristically. In this work, we use reinforcement learning (RL) to develop an adaptive penalty parameter selection policy for alternating current optimal power flow (ACOPF) problem solved via ADMM with the goal of minimizing the number of iterations until convergence. We train our RL policy using deep Q-learning and show that this policy can result in significantly accelerated convergence (up to a 59% reduction in the number of iterations compared to existing, curvatureinformed penalty parameter selection methods). Furthermore, we show that our RL policy demonstrates promise for generalizability, performing well under unseen loading schemes as well as under unseen losses of lines and generators (up to a 50% reduction in iterations). This work thus provides a proof-of-concept for using RL for parameter selection in ADMM for power systems applications.

alternating current optimal power flow↗

Sizing battery energy storage and PV system in an extreme fast charging station considering uncertainties and battery degradation

In this paper, we present mixed integer linear programming (MILP) formulations to obtain optimal sizing for a battery energy storage system (BESS) and solar generation system in an extreme fast charging station (XFCS) to reduce the annualized total cost. The proposed model characterizes a typical year with eight representative scenarios and obtains the optimal energy management for the station and BESS operation to exploit the energy arbitrage for each scenario. Contrasting extant literature, this paper proposes a constant power constant voltage (CPCV) based improved probabilistic approach to model the XFCS charging demand for weekdays and weekends. This paper also accounts for the monthly and annual demand charges based on realistic utility tariffs. Furthermore, BESS life degradation is considered in the model to ensure no replacement is needed during the considered planning horizon. Different from the literature, this paper offers pragmatic MILP formulations to tally BESS charge/discharge cycles using the cumulative charge/discharge energy concept. McCormick relaxations and the Big-M method are utilized to relax the bi-linear terms in the BESS operational constraints. Finally, a robust optimization-based MILP model is proposed and leveraged to account for uncertainties in electricity price, solar generation, and XFCS demand. Case studies were performed to signify the efficacy of the proposed formulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Bulk Power System Dynamics with Varying Levels of Synchronous Generators and Grid-Forming Power Inverters

Inverters using phase-locked loops for control depend on voltages generated by synchronous machines to operate. This might be problematic if much of the conventional generation fleet is displaced by inverters. To solve this problem, grid-forming control for inverters has been proposed as being capable of autonomously regulating grid voltages and frequency. Presently, the performance of bulk power systems with massive penetration of grid-forming inverters has not been thoroughly studied as to elucidate benefits. Hence, this paper presents inverter models with two grid-forming strategies: virtual oscillator control and droop control. The two models are specifically developed to be used in positive-sequence simulation packages and have been implemented in PSLF. The implementations are used to study the performance of bulk power grids incorporating inverters with gridforming capability. Specifically, simulations are conducted on a modified IEEE 39-bus test system and the microWECC test system with varying levels of synchronous and inverter-based generation. The dynamic performance of the tested systems with gridforming inverters during contingency events is better than cases with only synchronous generation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Rethinking the Price Formation Problem–Part 1: Participant Incentives under Uncertainty

Operators of organized wholesale electricity markets attempt to form prices in such a way that the private incentives of market participants are consistent with a socially optimal commitment and dispatch schedule. In the U.S. context, several competing price formation schemes have been proposed to address the non-convex production cost functions characteristic of most generation technologies. Here, this paper considers how the design and analysis of price formation policies for non-convex markets are affected by the uncertainty inherent in electricity demand and supply. We argue that by excluding uncertainty, the analytical framework underlying existing policies mischaracterizes the incentives of market participants, leading to inefficient price formation and poor incentives for flexibility. We establish favorable theoretical properties of a new construct, ex ante convex hull pricing , and demonstrate the difference between this idealized benchmark and existing methods on a large-scale test system. Given increased operational uncertainty with a transition to wind and solar generation, distortions caused by poor incentives for flexibility are likely to grow without improved price formation in organized wholesale markets.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Failure Analysis for Molten Salt Thermal Energy Storage Tanks for In-Service CSP Plants

Thermal Energy Storage (TES) is a fundamental component in concentrating solar power (CSP) plants to increase the plant's dispatchability, capacity factor, while reducing the levelized cost of electricity. In central receivers CSP plants, nitrate molten salts have been used for several years for operation temperatures of up to 565 degrees C. Despite many efforts to advance nitrate salt to higher operation temperatures (even considering a replacement with molten chloride salts) to achieve higher energy conversion efficiencies, the 565 degrees C temperature is currently considered the state-of-the art. Although molten salt tanks have been broadly deployed in commercial CSP plants worldwide, several failures have been reported in these tanks after a few months or years of operation, causing significant economic loss and mistrust in CSP technologies. Most of these failures are associated with the infancy of the technology and multiple issues related to tank design, fabrication, commissioning, and aggressive operation. A technical standard dedicated to the design and fabrication of molten nitrate TES tanks does not exist today. Current in-service molten salt tanks have been generally designed based on the American Petroleum Institute's (API) 650 and ASME Section II standards. The API 650 code provides guidelines for dimensions and fabrication for oil storage tanks up to 260 degrees C. The ASME standard provides allowable stress values for various materials at a range of temperatures and conditions. Both standards seem to be limited for molten salt TES tanks where high temperatures, thermal cycling, and transient conditions are expected. In 2020, NREL released the Concentrating Solar Power Best Practices Study (NREL/TP-5500-75763) that summarized multiple issues in CSP plants, along with potential alternatives and recommendations to address those issues based on information collected from participants representing about 80% of operating CSP plants in the world. One of the recommendations from this study was the development of accurate and validated models to evaluate the plant's transient operation, capable of capturing the effect of short-term clouds and operator response, while being flexible in being adapted to various spatial and temporal resource data. The "Failure Analysis for Molten Salt Thermal Energy Tanks for In-Service CSP Plants" project was inspired on this recommendation and was focused on (1) the development and validation of a physics-based model for a representative, commercial-scale molten salt tank, (2) performing simulations to evaluate the behavior of the tank as a function of typical plant operation conditions, (3) understanding tank failures mechanisms, (4) determining the residual stress and distortion in the tank floor after welding fabrication and evaluating their impact in the stresses developed in the tank during operation, (5) assessing the impact of key operation parameters on the temperature and stress distribution, (6) conduct a preliminary evaluation of design features to reduce stress and improve tank's reliability, and (7) estimate the tank's service life based on the stress developed under diverse operation scenarios. From the analysis conducted in the project and presented in this report, it was found that maximum stresses surpassing the yield strength point of the stainless steel (SS) 347H are developed on the tank floor near the perimeter. These large stresses are strongly influenced by the initial residual stresses and distortion of the tank floor after welding fabrication. During operation, large stresses are developed in the tank floor at high operation temperatures with large salt inventory levels during transient operation. High stresses are also related to elevated temperature gradients in the tank floor that could be attributed to insufficient mixing within the salt inflow and the salt inventory. Based on the analysis, creep is the predominant failure mechanism. However, the large stress levels could favor the plastic deformation into buckles, and crack formation due to stress relaxation cracking during cycle operation. A lifetime below 3 years was estimated for the typical plant operation conditions and a specific initial residual stress and deformation distribution of the tank floor. The estimated life agrees with the service time to failure reported in several commercial molten salt tanks. Desing and operation guidelines can be extracted from the analysis presented in this report, which could be adopted by tank manufacturers and CSP operators to advance toward an ultimate solution for tank failures by reducing residual and operational stresses to achieve a tank service life of more than 30 years. Addressing failures in molten salt TES tanks is fundamental for the CSP industry's survivability, but it is also important for other industrial and power generation applications using this technology, including nuclear and concentrating solar thermal.

14 SOLAR ENERGY↗

Distributed Grid Control of Flexible Loads and DERs for Optimized Provision of Synthetic Regulating Reserves

Over the course of this project, we have successfully de-risked our distributed microgrid control architecture by tightly integrating its associated control algorithms into a unified software library, installing the software library on several industrial-grade target hardware platforms, and validating the performance of the resulting microgrid controller in a real-life microgrid. Upon completion of the project, we demonstrated that our distributed control architecture is resilient against (i) failures in control devices, (ii) unreliable communication links, (iii) delays in transmitted data, and (iv) imperfect knowledge of the number of (and state of) generation and load assets in the microgrid. In this final report, we present results from all the milestones that were accomplished over the course of this project.

24 POWER TRANSMISSION AND DISTRIBUTION↗