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At least 217 records · Page 12

Analysis of the Effects of a Flexible Ramping Ancillary Service Product on Power System Operations: Preprint

The recent increased interest in utilizing variable generation (VG) resources such as wind and solar in power systems has motivated investigations into new operating procedures. Although these resources provide desirable value to a system (e.g., no fuel costs or emissions), interconnecting them provides unique challenges. Their variable, non-controllable nature in particular requires significant attention, because it directly results in increased power system variability and uncertainty. One way to handle this is via new operating reserve schemes. Operating reserves provide upward and downward generation and ramping capacity to counteract uncertainty and variability prior to their realization. For instance, uncertainty and variability in real-time dispatch can be accounted for in the hour-ahead unit commitment. New operating reserve methodologies that specifically account for the increased variability and uncertainty caused by VG are currently being investigated and developed by academia and industry. This paper examines one method inspired by the new operating reserve product being proposed by the California Independent System Operator. The method is based on examining the potential ramping requirements at any given time and enforcing those requirements via a reserve demand curve in the market-clearing optimization as an additional ancillary service product.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Decentralized wind uncertainty management: Alternating direction method of multipliers based distributionally-robust chance constrained optimal power flow

How to manage wind power uncertainty in system operation is an urgent and important issue, especially under substantially increasing penetration levels of wind generation in electric power systems. With increasing numbers of wind power plants (WPPs) integrated into power systems, their variability and uncertain power outputs become a challenge to maintaining system reliability. Traditional stochastic optimization-based models face the curse of dimensionality when the number of WPPs increases. This paper proposes a novel decentralized wind power uncertainty management model. In this model, conventional generators optimize their power capacity output and their participation to mitigate wind power uncertainty locally with only limited information exchange with the system operators. First, a distributionally-robust chance-constrained optimal power flow (DRCC-OPF) model is deployed to schedule the generation and reserve considering the wind power forecast uncertainty. Then, the alternating direction method of multipliers (ADMM) is used to reformulate the DRCC-OPF model into the distributed optimization model for each conventional generator and WPP. The tests on a small PJM 5-bus system and the IEEE 118-bus system demonstrate that the proposed decentralized model can increase the operation reliability without sacrificing system operating cost, especially when the wind power penetration levels are high. Using the proposed model, the optimal solutions can be obtained within one minute, for all studied cases, which verifies the computation efficiency of the proposed decentralized model. Furthermore, considering a large number of WPPs integrated into the system, the proposed decentralized method obtains a lower operating cost within one minute which demonstrates its efficiency to deal with high dimension of uncertainties.

17 WIND ENERGY↗

Design analysis of a particle-based thermal energy storage system for concentrating solar power or grid energy storage

Energy storage is becoming indispensable for expanding renewable energy integration, and it is critical to the future low-carbon energy supply. Large-capacity, grid scale energy storage can support the integration of solar and wind power and support grid resilience with the diminishing capacity of baseload fossil power plants. With the development of thermal energy storage (TES) for concentrating solar power systems, standalone TES for grid integration becomes attractive due to the declining renewable generation cost and an increasing need for energy storage. The standalone TES system introduced in this paper can play a big role in the carbon-free energy future with capacity larger than batteries and cost likely lower than other energy storage methods such as pumped storage hydropower and compressed air energy storage, both of which also have geological limitations. To this end, we describe a TES system that uses stable, inexpensive solid particles as a TES media to provide scalable, low cost energy storage. The particle-based TES has the ability to drive various thermal power cycles including conventional steam-Rankine, air Brayton turbine with combined-cycle ability, or the emerging supercritical carbon dioxide Brayton power cycle. This work describes the containment design method including a concrete silo and an internal-insulation layer for the particle-TES system. The economic analysis shows significantly low storage cost when the particle-TES is integrated with Brayton combined-cycle power generation. The paper shows the design approach of the particle-TES system and its economic potential for bulk energy storage. The advantage of the particle-TES system as a promising bulk energy storage method is its ability to economically support dispatchable renewable grid penetration for larger capacity and longer discharging hours than current battery storage technologies.

25 ENERGY STORAGE↗

Iterative methods in GPU-resident linear solvers for nonlinear constrained optimization

Linear solvers are major computational bottlenecks in a wide range of decision support and optimization computations. The challenges become even more pronounced on heterogeneous hardware, where traditional sparse numerical linear algebra methods are often inefficient. For example, methods for solving ill-conditioned linear systems have relied on conditional branching, which degrades performance on hardware accelerators such as graphical processing units (GPUs). To improve the efficiency of solving ill-conditioned systems, our computational strategy separates computations that are efficient on GPUs from those that need to run on traditional central processing units (CPUs). Our strategy maximizes the reuse of expensive CPU computations. Iterative methods, which thus far have not been broadly used for ill-conditioned linear systems, play an important role in our approach. In particular, we extend ideas from Arioli et al., (2007) to implement iterative refinement using inexact LU factors and flexible generalized minimal residual (FGMRES), with the aim of efficient performance on GPUs. In conclusion, we focus on solutions that are effective within broader application contexts, and discuss how early performance tests could be improved to be more predictive of the performance in a realistic environment.

97 MATHEMATICS AND COMPUTING↗

Multi-parametric analysis for mixed integer linear programming: An application to transmission upgrade and congestion management

Upgrading the capacity of existing transmission lines is essential for meeting the growing energy demands, facilitating the integration of renewable energy, and ensuring the security of the transmission system. This study focuses on the selection of lines whose capacities and by how much should be expanded from the perspective of the Independent System Operators (ISOs) to minimize the total system cost. We employ advanced multi-parametric programming and an enhanced branch-and-bound algorithm to address complex mixed-integer linear programming (MILP) problems, considering multi-period time constraints and physical limitations of generators and transmission lines. To characterize the various decisions in transmission expansion, we model the increased capacity of existing lines as parameters within a specified range. This study first relaxes the binary variables to continuous variables and applies the Lagrange method and Karush-Kuhn-Tucker (KKT) conditions to obtain optimal solutions and identify critical regions associated with active and inactive constraints. Moreover, we extend the traditional branch-and-bound (B&B) method by determining the problem’s upper and lower bounds at each node of the B&B decision tree, helping to manage computational challenges in large-scale MILP problems. Here, we compare the difference between the upper and lower bounds to obtain an approximate optimal solution within the decision-makers’ tolerable error range. In addition, the first derivative of the objective function on the parameters of each line is used to inform the selection of lines for easing congestion and maximizing social welfare. Finally, the capacity upgrades are selected by weighing the reductions in system costs against the expense of upgrading line capacities. The findings are supported by numerical simulations and provide transmission-line planners with decision-making guidance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Bidding Curve Design for Hybrid Power Plants with Uncertain Solar Forecast

This paper presents a novel bidding curve design algorithm tailored for hybrid power plants (HPPs) to participate in the wholesale electricity market. Utilizing forecasts for photovoltaic (PV) generation and available battery power, our algorithm strategically computes the bidding curve to maximize HPP profit while adeptly managing the inherent uncertainty associated with PV power generation. In addition, the introduction of the penalty cost in HPP bidding curves provides the system operator a tool to effectively manage the system-level uncertainty that caused by HPPs. Numerical analysis through Monte Carlo simulations confirms that our bidding curve methodology outperforms the benchmark across various scenarios.

bidding curve↗

Integration of Uncertainty Information into Power System Operations

Contemporary power systems face uncertainties coming from multiple sources, including forecast errors of load, wind and solar generation, uninstructed deviation and forced outage of traditional generators, loss of transmission lines, and others. With increasing amounts of wind and solar generation being integrated into the system, these uncertainties have been growing significantly. It is critical important to build knowledge of major sources of uncertainty, learn how to simulate them, and then incorporate this information into the decision-making processes and power system operations, for better reliability and efficiency. This paper gives a comprehensive view on the sources of uncertainty in power systems, important characteristics, available models, and ways of their integration into system operations. It is primarily based on previous works conducted at the Pacific Northwest National Laboratory (PNNL).

24 POWER TRANSMISSION AND DISTRIBUTION↗

Three-Stage Production Cost Modeling Approach for Evaluating the Benefits of Intra-Hour Scheduling Between Balancing Authorities

This paper introduces a production cost modeling approach for evaluating the benefits of intra-hour scheduling among Balancing Authorities (BAs). System operation is modeled in a three-stage sequential manner: day ahead (DA)-hour ahead (HA) real time (RT). In addition to contingency reserve, each BA will need to carry out 'up' and 'down' load following and regulation reserve capacity requirements in the DA and HA time frames. In the RT simulation, only contingency and regulation reserves are carried out as load following is deployed. To model current RT operation with hourly schedules, a new constraint was introduced to force each BA net exchange schedule deviation from HA schedules to be within North American Electric Reliability Corporation (NERC) area control error (ACE) limits. Case studies that investigate the benefits of moving from hourly exchange schedules between Western Electricity Coordinating Council (WECC) BAs into 10-minute exchange schedules under two different levels of wind and solar penetration (11% and 33%) are presented.

17 WIND ENERGY↗

Modeling Imperfect Generator Behavior in Power System Operation Models

A key component in power system operations is the use of computer models to quickly study and analyze different operating conditions and futures in an efficient manner. The output of these models are sensitive to the data used in them as well as the assumptions made during their execution. One typical assumption is that generators and load assets perfectly follow operator control signals. While this is a valid simulation assumption, generators may not always accurately follow control signals. This imperfect response of generators could impact cost and reliability metrics. This paper proposes a generator model that capture this imperfect behavior and examines its impact on production costs and reliability metrics using a steady-state power system operations model. Preliminary analysis shows that while costs remain relatively unchanged, there could be significant impacts on reliability metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Evaluation of Production Cost Savings from Consolidation of Balancing Authorities in the US Western Interconnection under High Wind and Solar Penetration

This paper introduces a comprehensive analysis to quantify the potential savings in production cost due to consolidation of 32 US western interconnection Balancing Authorities (BAs). Three simulation scenarios are developed: current Western Electricity Coordinating Council (WECC) BAs structure, full copper-sheet consolidation, and full consolidation with transmission congestion considered. The study uses WECC Transmission Expansion Planning Policy Committee (TEPPC) model that was developed for the year 2020. The model assumes 8% wind and 3% solar energy penetration as percentage of total WECC demand in 2020. Sensitivity analyses are carried out to assess the impact of transmission hurdle rates between WECC BAs on potential benefits. The study shows savings that ranges from $400 Million (2.4% of total one year production cost) to $600 Million (3.2%) per year in thermal units production cost due to consolidation can be achieved. The copper sheet consolidation scenario shows an extra savings of $240 Million (1.4%) per year.

Balancing authorities, hurdle rates, economic disp↗

Impacts of Short-Term Solar Power Forecasts in System Operations

Solar generation is experiencing an exponential growth in power systems worldwide and, along with wind power, is posing new challenges to power system operations. Those challenges are characterized by an increase of system variability and uncertainty across many time scales: from days, down to hours, minutes, and seconds. Much of the research in the area has focused on the effect of solar forecasting across hours or days. This paper presents a methodology to capture the effect of short-term forecasting strategies and analyzes the economic and reliability implications of utilizing a simple, yet effective forecasting method for solar PV in intra-day operations.

14 SOLAR ENERGY↗

A Comprehensive Comparison of Current Operating Reserve Methodologies

Electric power systems are currently experiencing a paradigm shift from a traditionally static system to a system that is becoming increasingly more dynamic and variable. Emerging technologies are forcing power system operators to adapt to their performance characteristics. These technologies, such as distributed generation and energy storage systems, have changed the traditional idea of a distribution system with power flowing in one direction into a distribution system with bidirectional flows. Variable generation, in the form of wind and solar generation, also increases the variability and uncertainty in the system. As such, power system operators are revisiting the ways in which they treat this evolving power system, namely by modifying their operating reserve methodologies. This paper intends to show an in-depth analysis on different operating reserve methodologies and investigate their impacts on power system reliability and economic efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Introducing Uncertainty Components in Locational Marginal Prices for Pricing Wind Power and Load Uncertainties

With substantially increasing penetration levels of wind power, electric power system flexibility is needed to address the variability and uncertainty of wind power output. Thus, it has become an urgent issue to obtain an optimal trade-off between economics and reliability, and to price system uncertainties. This paper proposes a new electricity market-clearing mechanism based on locational marginal prices (LMPs) for pricing uncertain generation and load. The uncertainty contained locational marginal price (U-LMP) is derived from a distributionally robust chance-constrained optimal power flow (DRCC-OPF) model in which only the first-order and second-order moments of the uncertain sources' probability distribution are needed. Compared with traditional LMPs, the proposed U-LMP formulation includes two new uncertainty components: transmission line overload uncertainty price and generation violation uncertainty price. These LMP uncertainty components are the price signals reflecting the system costs as a result of wind generation and demand uncertainty at different locations. Finally, using parametric case studies, the relationship among uncertainty levels, system generation cost, and LMP uncertainty components are established. Case studies performed on the PJM 5-bus and IEEE 118-bus systems verify the proposed U-LMP method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Using price-based signals to control plug-in electric vehicle fleet charging

We study decentralized plug-in electric vehicle (PEV) charging control, wherein the system operator (SO) sends price-based signals to a load aggregator (LA) that optimizes charging of a PEV fleet. We study a pricing scheme that conveys price and quantity information to the LA and compare it to a simpler price-only scheme. We prove that the price/quantity-based mechanism can yield a socially optimal solution. We also examine several numerical case studies to demonstrate the superior performance of the price/quantity-based scheme. The price/quantity scheme yields nearly identical PEV charging costs compared to the social optima, whereas the price-only scheme is highly sensitive to the choice of a regularization penalty term that is needed to ensure convergence. As a result, we also show that the time to compute an equilibrium with the price-only mechanism can be up to two orders of magnitude greater than with the price/quantity scheme and can involve 24 times more information exchange between the SO and LA.

99 GENERAL AND MISCELLANEOUS↗

HERON

HERON is a modeling toolset and plugin for RAVEN to accelerate stochastic technoeconomic assessment of the economic viability of various grid-energy system configurations, especially with application to electrical grids and integrated energy systems (IES). The frameworks enabling this toolset are INL's RAVEN and its TEAL plugin. The toolset includes automated RAVEN workflow generation tools for performing stochastic analysis and optimization driven by technoeconomic factors. The workflows generated employ RAVEN for parametric or optimizing study of grid component characteristics, and again for stochastic sampling of regulated and deregulated markets, load, and weather histories. The toolset further provides methods for economically-optimal dispatch of system components given the stochastic samples of market, load, and weather histories. The toolset allows assembling of existing and new models through the RAVEN interface to the Modelica process modeling language.

Talbot, PaulW↗

Profile of Resource Adequacy in the MISO Region

MISO is facing a number of generation resource challenges, ranging from large amounts of retirements, behind schedule retrofit projects, and internal resources committed to exporting power to PJM's capacity market. This report identifies potential issues with generator retirements and retrofits, as well as potential transmission issues, including the impact of imports and exports in a short-term outlook for resource adequacy in the MISO region, including specific concerns with the generation capacity expected to be available in the MISO North and Central regions from 2014 to 2016, as well as additional risks from proposed environmental regulations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Impacts Analysis of Amendments to Mexico's Unit Commitment and Dispatch Rules

In Mexico, there are various amendments, approved and under discussion to significantly modify the order in which generation units are committed and dispatched. This report quantifies the potential impacts on Mexico's power system, utilizing a production cost model of the Mexican power system that analyzes the hourly optimal electricity dispatch of the Mexican electricity system for 1 year under four scenarios, a reference scenario, and three alternative scenarios. These scenarios are meant to evaluate the potential impacts of increasing participation of the state-owned power plants in generation mix, electricity production costs, emissions, and renewable curtailment.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗