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309 records · Page 18

Robust Distributed State Estimator for Interconnected Transmission and Distribution Networks (Final Report RPPR-1)

This project’s objective is to develop a combined transmission and distribution state estimator which accounts for very large system size and model complexity (by way of distributing the computations) and large number of solar PV units connected to the distribution system on multiple feeders. The project not only provides a robust formulation and solution to this problem but also tests the solution by implementing it on a well-established large utility system. It introduces several improvements with respect to the state of the art in existing state estimation software: (a) The developed state estimator (SE) allows robust and accurate monitoring of bidirectional flows in distribution systems which result due to the distributed energy sources which are not observable and thus not incorporated in generation dispatch; (b) Large utility systems with tens of thousands of transmission buses and hundreds of thousands of distribution nodes are difficult to model as a single integrated system. This shortcoming is addressed by developing a “scalable distributed computational framework” which allows splitting the ultra large system models into several small subsystems and coordinating their solution by a robust and practical state estimation formulation; (c) Measurement errors irrespective of their locations are detected and removed by the developed state estimator. Historically, transmission and distribution systems were analyzed and operated as two independent systems. Given the non-transposed short feeder sections, unevenly loaded phases, strictly radial configuration and unidirectional power flows in the absence of remote generation, distribution system analysis was customized to account for these characteristics. However, some of these assumptions are no longer valid (non-radial configuration, bidirectional power flows) and thus distribution system analysis should be revisited. Furthermore, in the past, the interaction between the transmission and distribution systems was quite passive, where distribution substations were modeled as lumped loads in the transmission system model. With substantial generation injected by renewable generation located in the distribution systems, such modeling will no longer be accurate. The developed state estimator facilitates proper monitoring of the interactions between the transmission and distribution systems and enables smart dispatch of these units which are made observable by the state estimator.

24 POWER TRANSMISSION AND DISTRIBUTION↗

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Final Report)

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs). In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation (SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Where Have All of the Electrons Gone? Understanding the Role of Alternative Electron Flow and O 2 Reduction in Balancing Cellular Redox (Final Technical Report)

An informed understanding of the fundamentals of light-driven electron transfer reactions in photoautotrophic organisms is necessary to enable improved photosynthetic efficiencies for the production of renewable fuels and novel biomaterials. To obtain high photosynthetic yields, light energy must be efficiently coupled to the fixation of CO 2 . Sub-optimal environmental conditions and metabolic routing (caused by blocks in biosynthetic routes) can severely impact the conversion of light energy to biomass and lead to reactive oxygen production, which in turn can cause cellular damage and productivity losses. Hence, plants, algae, and photosynthetic bacteria have evolved a network of alternative outlets to sustain the flow of photosynthetically derived-electrons. Our research was focused on the nature and integration of these outlets. The data obtained in this project will inform efforts to rationally engineer crop plants and algae to improve photosynthetic yields by enhancing electron transfer reactions to CO 2 reduction and targeted biomass accumulation. A major project research thrust was focused on identifying and quantifying the flow of photosynthetic reductant through electron transfer circuits that result in the light-dependent reduction of O 2 . New energy management strategies were identified that are used when normal carbon assimilation pathways are compromised due to nutrient deprivation, and/or by a reduction in starch synthesis/carbon storage, all conditions resulting in highly reduced intracellular redox pools. The green alga Chlamydomonas reinhardtii, and likely many other algae, have multiple O 2 -reducing pathways that play critical roles in maintaining cellular metabolic balance and scavenging electrons that could potentially cause cellular damage, which in some instances leads to reduced photosynthetic yields but increased fitness. We explored the activities of three essential outlets associated with Chlamydomonas reinhardtii photosynthetic electron transport: (1) reduction of O 2 to H 2 O through Flavodiiron proteins (FLVs) and (2) Plastid Terminal Oxidases (PTOX), and (3) the synthesis of starch. Real-time measurements of O 2 exchange demonstrated that FLVs immediately engage during dark to light transitions, allowing electron transport when the CBBC is not fully activated. Under these conditions, we quantified, for the first time, maximal FLV activity and its overall capacity to direct photosynthetic electrons towards O 2 reduction. However, when starch synthesis is compromised, a greater proportion of electrons is directed toward O 2 reduction through the FLVs, while PTOX, which is sensitive to the PQ pool redox state, is activated. This suggests, that starch synthesis has an important role in priming/regulating CBBC and electron transport. We also identified a biological ‘switch’ in the green alga Chlamydomonas reinhardtii that reversibly restricts photosynthetic electron transport (PET) at the cytochrome b 6 f complex when reductant and ATP generated by PET are in excess of the capacity of carbon metabolism to utilize these products; we specifically show a restriction at this switch when sta6 mutant cells, which cannot synthesize starch, are limited for nitrogen (growth inhibition) and subjected to a dark to light transition. This restriction causes diminished electron flow to PSI, which prevents PSI photodamage, and the plastid alternative oxidase (PTOX) becomes fully activated, serving as an electron valve that dissipates excitation energy absorbed by PSII, thereby lessening PSII photoinhibition. Furthermore, illumination of the cells following the dark acclimation gradually diminishes the restriction at the switch. Future engineering of these switches may allow more effective electron transfer to lipid (biofuel) pathways and diminish the number of electrons “wasted” in the reduction of O 2 to water. Lastly, we explored metabolic routing of electrons during algal fermentation and discovered multiple novel pathways that are activated when the preferred anoxic routes are blocked. These provide valuable products (e.g. lactate, glycerol) that can be used in broad portfolio of biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗