Search NASA⌕ Search

SEARCH · Search NASA

Results for “dispatch”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

A computational framework for uncertainty quantification and stochastic optimization in unit commitment with wind power generation.

We present a computational framework for integrating a state-of-the-art numerical weather prediction (NWP) model in stochastic unit commitment/economic dispatch formulations that account for wind power uncertainty. We first enhance the NWP model with an ensemble-based uncertainty quantification strategy implemented in a distributed-memory parallel computing architecture. We discuss computational issues arising in the implementation of the framework and validate the model using real wind-speed data obtained from a set of meteorological stations. We build a simulated power system to demonstrate the developments.

17 WIND ENERGY↗
DOE OSTI2015

Enhanced Security-Constrained OPF With Distributed Battery Energy Storage

This paper discusses how fast-response distributed battery energy storage could be used to implement post-contingency corrective control actions. Immediately after a contingency, the injections of distributed batteries could be adjusted to alleviate overloads and reduce flows below their short-term emergency rating. This ensures that the post-contingency system remains stable until the operator has redispatched the generation. Implementing this form of corrective control would allow operators to take advantage of the difference between the short-and long-term ratings of the lines and would therefore increase the available transmission capacity. This problem is formulated as a two-stage, enhanced security-constrained OPF problem, in which the first-stage optimizes the pre-contingency generation dispatch, while the second-stage minimizes the corrective actions for each contingency. Case studies based on a six-bus test system and on the RTS 96 demonstrate that the proposed method provides effective corrective actions and can guarantee operational reliability and economy.

Wen, YF↗
DOE OSTI2015

Rapid Small-Signal Stability Assessment and Enhancement Following Changes in Topology

The paper proposes a scalable and tractable algorithm for dynamic topology optimization of power systems involving changes in branch on/off status, while respecting small-signal stability (SSS) constraints. A procedure for fast updates of the system matrices (in descriptor form) and without additional full matrix inversions is proposed. To additionally reduce the computation time, only critical eigenvalues (right-most or those in a specified damping ratio and frequency range) are calculated. A quadratic optimization approach is proposed for optimized generation re-dispatch to satisfy SSS constraints. The approach is applied to two (medium- and large-scale) real-world test power systems.

Saric, AT↗
DOE OSTI2015

Stochastic Optimization for Unit Commitment-A Review

Optimization models have been widely used in the power industry to aid the decision-making process of scheduling and dispatching electric power generation resources, a process known as unit commitment (UC). Since UC's birth, there have been two major waves of revolution on UC research and real life practice. The first wave has made mixed integer programming stand out from the early solution and modeling approaches for deterministic UC, such as priority list, dynamic programming, and Lagrangian relaxation. With the high penetration of renewable energy, increasing deregulation of the electricity industry, and growing demands on system reliability, the next wave is focused on transitioning from traditional deterministic approaches to stochastic optimization for unit commitment. Since the literature has grown rapidly in the past several years, this paper is to review the works that have contributed to the modeling and computational aspects of stochastic optimization (SO) based UC. Relevant lines of future research are also discussed to help transform research advances into real-world applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Capacity Adequacy and Revenue Sufficiency in Electricity Markets With Wind Power

We present a computationally efficient mixed-integer program (MIP) that determines optimal generator expansion decisions, as well as periodic unit commitment and dispatch. The model is applied to analyze the impact of increasing wind power capacity on the optimal generation mix and the profitability of thermal generators. In a case study, we find that increasing wind penetration reduces energy prices while the prices for operating reserves increase. Moreover, scarcity pricing for operating reserves through reserve shortfall penalties significantly impacts the prices and profitability of thermal generators. Without scarcity pricing, no thermal units are profitable, however scarcity pricing can ensure profitability for peaking units at high wind penetration levels. Capacity payments can also ensure profitability, but the payments required for baseload units to break even increase with the amount of wind power. The results indicate that baseload units are most likely to experience revenue sufficiency problems when wind penetration increases and new baseload units are only developed when natural gas prices are high and wind penetration is low.

capacity adequacy↗
DOE OSTI2016

A robust approach to chance constrained optimal power flow with renewable generation

Optimal Power Flow (OPF) dispatches controllable generation at minimum cost subject to operational constraints on generation and transmission assets. The uncertainty and variability of intermittent renewable generation is challenging current deterministic OPF approaches. Recent formulations of OPF use chance constraints to limit the risk from renewable generation uncertainty, however, these new approaches typically assume the probability distributions which characterize the uncertainty and variability are known exactly. We formulate a robust chance constrained (RCC) OPF that accounts for uncertainty in the parameters of these probability distributions by allowing them to be within an uncertainty set. The RCC OPF is solved using a cutting-plane algorithm that scales to large power systems. We demonstrate the RRC OPF on a modified model of the Bonneville Power Administration network, which includes 2209 buses and 176 controllable generators. In conclusion, deterministic, chance constrained (CC), and RCC OPF formulations are compared using several metrics including cost of generation, area control error, ramping of controllable generators, and occurrence of transmission line overloads as well as the respective computational performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Optimal Regulation of Virtual Power Plants

This paper develops a real-time algorithmic framework for aggregations of distributed energy resources (DERs) in distribution networks to provide regulation services in response to transmission-level requests. Leveraging online primal-dual-type methods for time-varying optimization problems and suitable linearizations of the nonlinear AC power-flow equations, we believe this work establishes the system-theoretic foundation to realize the vision of distribution-level virtual power plants. The optimization framework controls the output powers of dispatchable DERs such that, in aggregate, they respond to automatic-generation-control and/or regulation-services commands. This is achieved while concurrently regulating voltages within the feeder and maximizing customers' and utility's performance objectives. Convergence and tracking capabilities are analytically established under suitable modeling assumptions. Simulations are provided to validate the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Optimal Transmission Line Switching under Geomagnetic Disturbances

Recently, there have been increasing concerns about how geomagnetic disturbances (GMDs) impact electrical power systems. Geomagnetically-induced currents (GICs) can saturate transformers, induce hot spot heating and increase reactive power losses. These effects can potentially cause catastrophic damage to transformers and severely impact the ability of a power system to deliver power. To address this problem, we develop a model of GIC impacts to power systems that includes 1) GIC thermal capacity of transformers as a function of normal Alternating Current (AC) and 2) reactive power losses as a function of GIC. We also use this model to derive an optimization problem that protects power systems from GIC impacts through line switching, generator dispatch, and load shedding. We then employ state-of-the-art convex relaxations of AC power flow equations to lower bound the objective. We demonstrate the approach on a modified RTS96 system and UIUC 150-bus system and show that line switching is an effective means to mitigate GIC impacts. We also provide a sensitivity analysis of decisions with respect to GMD direction.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Optimizing DER Participation in Inertial and Primary-Frequency Response

This paper develops an approach to enable the optimal participation of distributed energy resources (DERs) in inertial and primary-frequency response alongside conventional synchronous generators. Leveraging a reduced-order model description of frequency dynamics, DERs' synthetic inertias and droop coefficients are designed to meet time-domain performance objectives of frequency overshoot and steady-state regulation. Furthermore, an optimization-based method centered around classical economic dispatch is developed to ensure that DERs share the power injections for inertial- and primary-frequency response in proportion to their power ratings. Simulations for a modified New England test-case system composed of ten synchronous generators and six instances of the IEEE 37-node test feeder with frequency-responsive DERs validate the design strategy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

The Role of Concentrating Solar Power Toward High Renewable Energy Penetrated Power Systems

Achieving high renewable energy penetrated power systems requires considerable operational flexibility to hedge the variability and uncertainty of variable renewable energy (VRE) generation. Compared with VRE sources, concentrating solar power (CSP) is an emerging controllable renewable generation technique that utilizes solar thermal power to generate electricity. The operational dispatchability of CSP would contribute to the power system transition toward high renewable penetration. In this paper, we explore how the generation portfolio will change toward high renewable energy penetrations, how much cost is involved, and what role CSP will play in realizing a high renewable energy penetrated power system. This study relies on a stochastic two-stage generation and transmission expansion planning model with CSP plants. The model captures the uncertainty and variability of renewable generation and the flexibility limits of thermal plants. With the target of achieving a renewable-dominated minimum-cost system with an expected renewable energy penetration level, the investments of both generation and transmission facilities are optimized. A case study on IEEE test systems with renewable technology cost data in 2050 is performed to analyze the value of CSP toward high renewable energy penetrated power systems.

14 SOLAR ENERGY↗
DOE OSTI2018

Optimizing Service Restoration in Distribution Systems With Uncertain Repair Time and Demand

This paper proposes a novel method to co-optimize the distribution system operation and repair crew routing for outage restoration after extreme weather events. A two-stage stochastic mixed integer linear program is developed. The first stage is to dispatch the repair crews to the damaged components. The second stage is distribution system restoration using distributed generators, and reconfiguration. We consider demand uncertainty in terms of a truncated normal forecast error distribution, and model the uncertainty of the repair time using a lognormal distribution. A new decomposition approach, combined with the progressive hedging algorithm, is developed for solving large-scale outage management problems in an effective and timely manner. Furthermore, the proposed method is validated on modified IEEE 34- and 8500-bus distribution test systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Operation of a High Renewable Penetrated Power System With CSP Plants: A Look-Ahead Stochastic Unit Commitment Model

The integration of variable renewable energy (VRE) generation, i.e., wind power and solar photovoltaic, brings significant uncertainty for the power system operation. Different with VRE techniques, concentrating solar power (CSP) is an appealing renewable generation technology due to its dispatch ability through the use of thermal energy storage and is thus expected to play a significant role in high renewable energy penetrated power systems. In this paper, we propose a look-ahead stochastic unit commitment model to operate power systems with CSP under high renewable energy penetration. It has a three-stage structure. The first stage optimizes the operational decisions in a day-ahead framework based on forecasts; the second stage minimizes the expected generation cost for possible realizations in the real time; and the third stage accounts for look-ahead operation in future operating days. This paper has a dual purpose: first, exploring how CSP plants operate in high renewable penetrated power systems; and second, analyzing the benefits of CSP in accommodating VRE generation. A case study on a modified IEEE RTS-79 system with actual solar and wind power data is provided to validate the proposed method.

14 SOLAR ENERGY↗
DOE OSTI2018

Toward a MILP Modeling Framework for Distribution System Restoration

Large-scale blackouts and extreme weather events in recent decades raise the concern for improving the resilience of electric power infrastructures. Distribution service restoration (DSR), a fundamental application in outage management systems, allows restoration solutions for system operators when power outages happen. As distribution generators (DGs) and remotely controllable devices are increasingly installed in distribution systems, an advanced DSR framework is critical to perform optimally coordinated restoration that can achieve maximal restoration performance. This work introduces a DSR modeling framework, which can generate optimal switching sequences and estimated time of restoration in the presence of remotely controllable switches, manually operated switches, and dispatchable DGs. Two mathematical models, a variable time step model and a fixed time step model, are presented and compared. The proposed models are formulated as a mixed-integer linear programming model, and their effectiveness is evaluated via the IEEE 123 node test feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Multi-operator Production Cost Modeling

As contiguous power systems are often operated by several regional system operators, optimization models have traditionally been designed to generate optimal system-wide scheduling decisions. This report introduces an approach to reflect the existence of multiple system operators making scheduling decisions within an interconnected power system. The approach is explicitly designed to reflect each operator's limited knowledge about other regions when making scheduling decisions. Detailed analysis using a modified IEEE Reliability Test System reveals that the approach mimics real system operations by providing imperfect information to each operator about external operations and external constraints. The approach scales to a 78,000-bus model of the Eastern Interconnection, where a regression analysis provides quantitative insight into which constraints cause inefficiencies when improperly managed in a multi-operator simulation. Because the approach generates distinct regional scheduling problems, unit commitment and economic dispatch simulations can be applied to individual regions and solved in parallel, enabling production cost simulations at a previously intractable scale.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Real-Time Optimized Load Recovery Considering Frequency Constraints

A self-healing power grid can mitigate the impact of power outages and recover the affected area swiftly. To properly size the optimal amount and location of de-energized loads in the presence of both conventional and renewable sources, a precise optimization-based load recovery tool is proposed herein. The steady-state and transient behaviors of loads have been taken into account. The proposed tool contains three separate problems that interact with each other during the restoration period. The first-level problem determines the dispatching of generation units. The second-level problem comprises the non-linear algebraic equations, whose task is to provide the initial conditions for the third-level problem. Finally, the third-level problem intends to determine the optimal location and amount of load pickup through modeling the governor of generators as well as loads' dynamic behaviors. To examine the effectiveness of the proposed tool, a modified IEEE 39-system under a partial blackout condition has been tested. The results are verified by a commercial time-domain simulation software (PSS/E) to demonstrate the accuracy of the proposed approach. Ultimately, the impact of wind turbine frequency control on the load recovery process has been studied under different penetration levels.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Accelerated Voltage Regulation in Multi-Phase Distribution Networks Based on Hierarchical Distributed Algorithm

Here, we introduce a hierarchical distributed algorithm to solve optimal power flow (OPF) problems that aim at dispatching controllable distributed energy resources (DERs) for voltage regulation at minimum cost. The proposed algorithm highlights unprecedented scalability to large multi-phase distribution networks by jointly exploring the tree/subtrees structure of a large radial distribution network and the structure of the linearized distribution power flow (LinDistFlow) model to derive a hierarchical, distributed implementation of the primal-dual gradient algorithm that solves OPF. The proposed implementation significantly reduces the computation loads compared to the centrally coordinated implementation of the same primal-dual algorithm without compromising optimality. Numerical findings on a 4,521-node test feeder show that the designed algorithm achieves more than 10-fold acceleration in the speed of convergence compared to the centrally coordinated primal-dual algorithm through reducing and distributing computational loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗