2018 Community Commitment Plan Allocations
Summary of community commitment funding allocations for 2018.
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Summary of community commitment funding allocations for 2018.
As electricity markets begin to shift from reliance on large, centralized power plants and towards distributed energy resources (DERs), there is a growing acknowledgement that more efficient planning, operations, and oversight is needed in the distribution system. This paper addresses one step in that direction by proposing an auction mechanism that uses a detailed distribution system planning model that allocates permits to end-used customers who request capacity to install new devices at their location and network upgrade contracts to utilities or 3rd-party companies who offer to upgrade system components. The resulting plan maximizes market surplus, that is, maximizes the total benefit to consumers minus the cost of network upgrades. We apply a marginal pricing scheme to the auction’s results such that the cost of each permits or contracts is differentiated by time and location, based on the Lagrangian multipliers of binding network constraints. These prices are shown to be no greater than the bid price of any awarded contract and no less than the offered cost of any awarded upgrade contract. Furthermore, the nonlinearity of power flows in the planning model result in an additional surplus that would be collected by the entity that hosts the auction, which could then be refunded to market participants or used to cover overhead costs of running the market. We provide four example auction results in a simple three-node distribution feeder to demonstrate the properties of the design. Results suggest that larger or more realistic case studies could be a promising next step.
Existing regulatory approaches to DER lack the precision and granularity necessary to ensure that DER can continue to scale in a cost-effective manner that is aligned with the public interest. To address this need, with the support of the U.S. Department of Energy’s Office of Electricity, Berkeley Lab and Current Energy Group developed an illustrative regulatory framework. By adopting a technology-neutral and modular approach, the framework enables flexibility and scalability for DER providers, utilities, and regulators. Clear price signals and incentives encourage the provision of valuable grid services, while equitable cost allocation promotes efficient use of distribution capacity and interconnection resources. This approach mirrors traditional ratemaking principles for importing customers and positions DERs as integral components of a dynamic and cost-effective energy future.
Exercise facilities have been proven to have numerous physical, mental, and psychological benefits, yet exercise facilities are still inaccessible to a large portion of the population. This study serves to explore the accessibility of fitness centres through geographical, demographic, and temporal lenses through an expansion of the UrbanPop framework that seeks to allocate simulated agents to fitness centres in the Clarksville metro to explore the effects of travel distances on different demographics throughout the week. Findings indicate that senior and retired demographics consistently travel longer distances to exercise in the larger Clarksville area, likely due to tendencies to live further from the center of the metropolitan area. Furthermore, all demographics tend to travel further distances to exercise on the weekends rather than the weekdays, indicating that travel distance can affect likelihood of agents to travel, especially on weekdays when many agents are in the workforce or participating in schooling.
This report introduces recovery simulator and analysis (RSA), a framework aimed at enhancing the resilience of electrical grids post-disruption. The RSA model leverages an optimization problem formulation that focuses on maximizing the load served (or optionally customers served) through a coordinated and cooptimized recovery of non-black start generation, transmission lines, feeders and substations subject to labor budget constraints. By integrating advanced linear programming techniques, the simulator selects efficient reocovery pathways, optimizing both short-term and long-term grid recovery strategies. The mathematical framework guides decision-making through a comprehensive evaluation of potential recovery actions, factoring in the trade-offs between labor constraints and load (or optionally customer) restoration efficacy. This enables grid operators to simulate diverse outage scenarios and delineate optimal recovery pathways, thereby prioritizing critical repair tasks and ensuring resource allocation is both economical and effective. The intended use case of RSA is to allow planners to explore many recovery scenarios quickly and determine assets most critical across a wide range of scenarios, and therefore strong candidates for hardening or additional investment. RSA might also be used in an operational setting, following a single event, for exploring efficient recovery pathways.
Recent advances in quantum hardware offer new approaches to solve various optimization problems that can be computationally expensive when classical algorithms are employed. We propose a hybrid quantum-classical algorithm to solve a dynamic asset allocation problem where a target return and a target risk metric (expected shortfall) are specified. We propose an iterative algorithm that treats the target return as a constraint in a Markowitz portfolio optimization model, and dynamically adjusts the target return to satisfy the targeted expected shortfall. The Markowitz optimization is formulated as a Quadratic Unconstrained Binary Optimization (QUBO) problem. The use of the expected shortfall risk metric enables the modeling of extreme market events. We compare the results from D-Wave’s 2000Q and Advantage quantum annealers using real-world financial data. Both quantum annealers are able to generate portfolios with more than 80% of the return of the classical optimal solutions, while satisfying the expected shortfall. We observe that experiments on assets with higher correlations tend to perform better, which may help to design practical quantum applications in the near term.
Stoichiometric genome-scale metabolic models (generally abbreviated GSM, GSMM, or GEM) have had many applications in exploring phenotypes and guiding metabolic engineering interventions. Nevertheless, these models and predictions thereof can become limited as they do not directly account for protein cost, enzyme kinetics, and cell surface or volume proteome limitations. Lack of such mechanistic detail could lead to overly optimistic predictions and engineered strains. Initial efforts to correct these deficiencies were by the application of precursor tools for GSMs, such as flux balance analysis with molecular crowding. In the past decade, several frameworks have been introduced to incorporate proteome-related limitations using a genome-scale stoichiometric model as the reconstruction basis, which herein are called resource allocation models (RAMs). This review provides a broad overview of representative or commonly used existing RAM frameworks. This review discusses increasingly complex models, beginning with stoichiometric models to precursor to RAM frameworks to existing RAM frameworks. RAM frameworks are broadly divided into two categories: coarse-grained and fine-grained, with different strengths and challenges. Discussion includes pinpointing their utility, data needs, highlighting framework strengths and limitations, and appropriateness to various research endeavors, largely through contrasting their mathematical frameworks. Finally, promising future applications of RAMs are discussed.
Disclosed herein are representative embodiments of methods, apparatus, and systems for distributing a resource (such as electricity) using a resource allocation system. In one exemplary embodiment, a plurality of requests for electricity are received from a plurality of end-use consumers. The requests indicate a requested quantity of electricity and a consumer-requested index value indicative of a maximum price a respective end-use consumer will pay for the requested quantity of electricity. A plurality of offers for supplying electricity are received from a plurality of resource suppliers. The offers indicate an offered quantity of electricity and a supplier-requested index value indicative of a minimum price for which a respective supplier will produce the offered quantity of electricity. A dispatched index value is computed at which electricity is to be supplied based at least in part on the consumer-requested index values and the supplier-requested index values.
Disclosed herein are representative embodiments of methods, apparatus, and systems for distributing a resource (such as electricity) using a resource allocation system. In one exemplary embodiment, a plurality of requests for electricity are received from a plurality of end-use consumers. The requests indicate a requested quantity of electricity and a consumer-requested index value indicative of a maximum price a respective end-use consumer will pay for the requested quantity of electricity. A plurality of offers for supplying electricity are received from a plurality of resource suppliers. The offers indicate an offered quantity of electricity and a supplier-requested index value indicative of a minimum price for which a respective supplier will produce the offered quantity of electricity. A dispatched index value is computed at which electricity is to be supplied based at least in part on the consumer-requested index values and the supplier-requested index values.
Disclosed herein are representative embodiments of methods, apparatus, and systems for distributing a resource (such as electricity) using a resource allocation system. In one exemplary embodiment, a plurality of requests for electricity are received from a plurality of end-use consumers. The requests indicate a requested quantity of electricity and a consumer-requested index value indicative of a maximum price a respective end-use consumer will pay for the requested quantity of electricity. A plurality of offers for supplying electricity are received from a plurality of resource suppliers. The offers indicate an offered quantity of electricity and a supplier-requested index value indicative of a minimum price for which a respective supplier will produce the offered quantity of electricity. A dispatched index value is computed at which electricity is to be supplied based at least in part on the consumer-requested index values and the supplier-requested index values.
The invention provides coding and promoter sequences for a VS-1 and AP-2 gene, which affects the developmental process of senescence in plants. Vectors, transgenic plants, seeds, and host cells comprising heterologous VS-1 and AP-2 genes are also provided. Additionally provided are methods of altering nutrient allocation and composition in a plant using the VS-1 and AP-2 genes.
Disclosed herein are representative embodiments of methods, apparatus, and systems for distributing a resource (such as electricity) using a resource allocation system. In one exemplary embodiment, a plurality of requests for electricity are received from a plurality of end-use consumers. The requests indicate a requested quantity of electricity and a consumer-requested index value indicative of a maximum price a respective end-use consumer will pay for the requested quantity of electricity. A plurality of offers for supplying electricity are received from a plurality of resource suppliers. The offers indicate an offered quantity of electricity and a supplier-requested index value indicative of a minimum price for which a respective supplier will produce the offered quantity of electricity. A dispatched index value is computed at which electricity is to be supplied based at least in part on the consumer-requested index values and the supplier-requested index values.
Disclosed herein are representative embodiments of methods, apparatus, and systems for distributing a resource (such as electricity) using a resource allocation system. In one exemplary embodiment, a plurality of requests for electricity are received from a plurality of end-use consumers. The requests indicate a requested quantity of electricity and a consumer-requested index value indicative of a maximum price a respective end-use consumer will pay for the requested quantity of electricity. A plurality of offers for supplying electricity are received from a plurality of resource suppliers. The offers indicate an offered quantity of electricity and a supplier-requested index value indicative of a minimum price for which a respective supplier will produce the offered quantity of electricity. A dispatched index value is computed at which electricity is to be supplied based at least in part on the consumer-requested index values and the supplier-requested index values.
Disclosed herein are representative embodiments of methods, apparatus, and systems for distributing a resource (such as electricity) using a resource allocation system. In one exemplary embodiment, a plurality of requests for electricity are received from a plurality of end-use consumers. The requests indicate a requested quantity of electricity and a consumer-requested index value indicative of a maximum price a respective end-use consumer will pay for the requested quantity of electricity. A plurality of offers for supplying electricity are received from a plurality of resource suppliers. The offers indicate an offered quantity of electricity and a supplier-requested index value indicative of a minimum price for which a respective supplier will produce the offered quantity of electricity. A dispatched index value is computed at which electricity is to be supplied based at least in part on the consumer-requested index values and the supplier-requested index values.
Shunt FACTS devices, such as, a Static Var Compensator (SVC), are capable of providing local reactive power compensation. They are widely used in the network to reduce the real power loss and improve the voltage profile. This paper proposes a planning model based on mixed integer conic programming (MICP) to optimally allocate SVCs in the transmission network considering load uncertainty. The load uncertainties are represented by a number of scenarios. Reformulation and linearization techniques are utilized to transform the original non-convex model into a convex second order cone programming (SOCP) model. Numerical case studies based on the IEEE 30-bus system demonstrate the effectiveness of the proposed planning model.
In this presentation we overview a methodology for dynamic security risk quantification and optimal resource allocation of security assets for high profile venues. This methodology is especially applicable to venues that require security screening operations such as mass transit (e.g., train or airport terminals), critical infrastructure protection (e.g., government buildings), and largescale public events (e.g., concerts or professional sports). The method starts by decomposing the three core components of risk -- threat, vulnerability, and consequence -- into their various subcomponents. For instance, vulnerability can be decomposed into availability, accessibility, organic security, and target hardness and each of these can be evaluated against the potential threats of interest for the given venue. Once evaluated, these subcomponents are rolled back up to compute the specific value for the vulnerability core risk component. Likewise, the same is done for consequence and threat, and then risk is computed as the product of these three components. A key aspect of our methodology is dynamically quantifying risk. That is, we incorporate the ability to uniquely allow the subcomponents and core components, and in turn, risk, to be quantified as a continuous function of time throughout the day, week, month, or year as appropriate.
A system, method, and computer program product are provided for providing prioritized access for multithreaded processing. The method includes the steps of allocating threads to process a workload and assigning a set of priority tokens to at least a portion of the threads. Access to a resource, by each one of the threads, is based on the priority token assigned to the thread and the threads are executed by a multithreaded processor to process the workload.
A processing system employs a memory module as a temporary write buffer to store write requests when a write buffer at a memory controller reaches a threshold capacity, and de-allocates the temporary write buffer when the write buffer capacity falls below the threshold. Upon receiving a write request, the memory controller stores the write request in a write buffer until the write request can be written to main memory. The memory controller can temporarily extend the memory controller's write buffer to the memory module, thereby accommodating temporary periods of high memory activity without requiring a large permanent write buffer at the memory controller.