[ { "id": "authors:bns0y-j6t74", "collection": "authors", "collection_id": "bns0y-j6t74", "cite_using_url": "https://authors.library.caltech.edu/records/bns0y-j6t74", "type": "conference_item", "title": "Pricing Uncertainty in Stochastic Multi-Stage Electricity Markets", "book_title": "2023 62nd IEEE Conference on Decision and Control (CDC)", "author": [ { "family_name": "Werner", "given_name": "Lucien", "clpid": "Werner-Lucien" }, { "family_name": "Christianson", "given_name": "Nicolas", "orcid": "0000-0001-8330-8964", "clpid": "Christianson-Nicolas" }, { "family_name": "Zocca", "given_name": "Alessandro", "orcid": "0000-0001-6585-4785", "clpid": "Zocca-Alessandro" }, { "family_name": "Wierman", "given_name": "Adam", "orcid": "0000-0002-5923-0199", "clpid": "Wierman-A" }, { "family_name": "Low", "given_name": "Steven", "orcid": "0000-0001-6476-3048", "clpid": "Low-S-H" } ], "abstract": "
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This work proposes a pricing mechanism for multi-stage electricity markets that does not explicitly depend on the choice of dispatch procedure or optimization method. Our approach is applicable to a wide range of methodologies for the economic dispatch of power systems under uncertainty, including multi-interval dispatch, multi-settlement markets, scenario-based dispatch, and chance-constrained dispatch policies. We prove that our pricing scheme provides both ex-ante and expost dispatch-following incentives by simultaneously supporting per-stage and ex-post competitive equilibria. In numerical experiments on a ramp-constrained test system, we demonstrate the benefits of scheduling under uncertainty and show how our price decomposes into components corresponding to energy, intertemporal coupling, and uncertainty.
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", "doi": "10.1109/cdc49753.2023.10384022", "isbn": "979-8-3503-0124-3", "publisher": "IEEE", "place_of_publication": "Piscataway, NJ", "publication_date": "2023-12", "pages": "1580-1587" }, { "id": "authors:jedfs-0zx20", "collection": "authors", "collection_id": "jedfs-0zx20", "cite_using_url": "https://authors.library.caltech.edu/records/jedfs-0zx20", "type": "conference_item", "title": "Convergence of Backward/Forward Sweep for Power Flow Solution in Radial Networks", "book_title": "2023 62nd IEEE Conference on Decision and Control (CDC)", "author": [ { "family_name": "Fang", "given_name": "Bohang", "orcid": "0009-0004-1055-4872", "clpid": "Fang-Bohang" }, { "family_name": "Zhao", "given_name": "Changhong", "clpid": "Zhao-Changhong" }, { "family_name": "Low", "given_name": "Steven H.", "orcid": "0000-0001-6476-3048", "clpid": "Low-S-H" } ], "abstract": "
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Solving power flow is perhaps the most fundamental calculation related to the steady state behavior of alternating-current (AC) power systems. The normally radial (tree) topology of a distribution network induces a spatially recursive structure in power flow equations, which enables a class of efficient solution methods called backward/forward sweep (BFS). In this paper, we revisit BFS from a new perspective, focusing on its convergence. Specifically, we describe a general formulation of BFS, interpret it as a special Gauss-Seidel algorithm, and then illustrate it in a single-phase power flow model. We prove a sufficient condition under which the BFS is a contraction mapping on a closed set of safe voltages and thus converges geometrically to a unique power flow solution. We verify the convergence condition, as well as the accuracy and computational efficiency of BFS, through numerical experiments in IEEE test systems.
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", "doi": "10.1109/cdc49753.2023.10383981", "isbn": "979-8-3503-0124-3", "publisher": "IEEE", "place_of_publication": "Piscataway, NJ", "publication_date": "2023-12", "pages": "4034-4039" }, { "id": "authors:2sgyc-4rz86", "collection": "authors", "collection_id": "2sgyc-4rz86", "cite_using_url": "https://authors.library.caltech.edu/records/2sgyc-4rz86", "type": "conference_item", "title": "Modeling Unbalanced Power Flow with \u0394-connected Devices", "book_title": "2023 62nd IEEE Conference on Decision and Control (CDC)", "author": [ { "family_name": "Low", "given_name": "Steven H.", "orcid": "0000-0001-6476-3048", "clpid": "Low-S-H" } ], "abstract": "
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In this tutorial we present a simple approach to modeling unbalanced three-phase power flows. We allow general non-ideal models of voltage sources, ZIP loads as well as distribution lines and transformers. The basic idea is to explicitly separate a device/transformer model into an internal model, that depends on the characteristics of the single-phase devices or transformers, and a conversion rule, that depends on their configuration. This approach provides two benefits. First it facilitates the modeling of secondary distribution circuits where only the end devices are directly controllable, not the currents or powers at the secondary transformers. Second it allows us to exploit common structures across different device/transformer variants and derive their external models that are general and unified. We illustrate these benefits by extending a three-phase backward forward sweep method in the literature to allow secondary circuits and formulating a three-phase optimal power flow problem as a quadratically constrained quadratic program.
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", "doi": "10.1109/cdc49753.2023.10383695", "isbn": "979-8-3503-0124-3", "publisher": "IEEE", "place_of_publication": "Piscataway, NJ", "publication_date": "2023-12", "pages": "4026-4033" }, { "id": "authors:4h351-qdc18", "collection": "authors", "collection_id": "4h351-qdc18", "cite_using_url": "https://authors.library.caltech.edu/records/4h351-qdc18", "type": "conference_item", "title": "DeepOPF-AL: Augmented Learning for Solving AC-OPF Problems with a Multi-Valued Load-Solution Mapping", "book_title": "Proceedings of the 14th ACM International Conference on Future Energy Systems", "author": [ { "family_name": "Pan", "given_name": "Xiang", "orcid": "0000-0001-9108-944X", "clpid": "Pan-Xiang" }, { "family_name": "Huang", "given_name": "Wanjun", "orcid": "0000-0002-6851-3705", "clpid": "Huang-Wanjun" }, { "family_name": "Chen", "given_name": "Minghua", "orcid": "0000-0003-4763-0037", "clpid": "Chen-Minghua" }, { "family_name": "Low", "given_name": "Steven H.", "orcid": "0000-0001-6476-3048", "clpid": "Low-S-H" } ], "abstract": "

The existence of multi-valued load-solution mapping in general non-convex problems poses a fundamental challenge to deep neural network (DNN) schemes. A well-trained DNN in the existing supervised learning framework fails to learn the multi-valued mapping accurately and generates inferior solutions. We propose augmented learning as a methodological framework to tackle this challenge. We focus on AC-OPF as an important example and develop DeepOPF-AL to solve it. The main idea is to train a DNN to learn a single-valued mapping from an augmented input, i.e., (load, initial point), to the solution generated by an iterative OPF solver with the load and initial point as intake. We then apply the learned augmented mapping to solve AC-OPF problems much faster than conventional solvers. Simulation results over IEEE test cases show that DeepOPF-AL achieves noticeably better optimality and similar feasibility and speedup performance as compared to a recent DNN scheme, with the same DNN size yet larger training-data size. We believe the augmented-learning approach will find applications in various problems with a multi-valued input-solution mapping.

", "doi": "10.1145/3575813.3576874", "isbn": "9798400700323", "publisher": "ACM", "place_of_publication": "New York, NY", "publication_date": "2023-06", "pages": "42-47" }, { "id": "authors:y1yzt-cvx11", "collection": "authors", "collection_id": "y1yzt-cvx11", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20110614-094637693", "type": "conference_item", "title": "Geographical Load Balancing with Renewables", "author": [ { "family_name": "Liu", "given_name": "Zhenhua", "clpid": "Liu-Zhenhua" }, { "family_name": "Lin", "given_name": "Minghong", "clpid": "Lin-Minghong" }, { "family_name": "Wierman", "given_name": "Adam", "clpid": "Wierman-A" }, { "family_name": "Low", "given_name": "Steven H.", "orcid": "0000-0001-6476-3048", "clpid": "Low-S-H" }, { "family_name": "Andrew", "given_name": "Lachlan L. H.", "clpid": "Andrew-L-L-H" } ], "abstract": "Given the significant energy consumption of data centers, improving\ntheir energy efficiency is an important social problem.\nHowever, energy efficiency is necessary but not sufficient\nfor sustainability, which demands reduced usage of\nenergy from fossil fuels. This paper investigates the feasibility\nof powering internet-scale systems using (nearly) entirely\nrenewable energy. We perform a trace-based study\nto evaluate three issues related to achieving this goal: the\nimpact of geographical load balancing, the role of storage,\nand the optimal mix of renewables. Our results highlight\nthat geographical load balancing can significantly reduce the\nrequired capacity of renewable energy by using the energy\nmore efficiently with \"follow the renewables\" routing. Further,\nour results show that small-scale storage can be useful,\nespecially in combination with geographical load balancing,\nand that an optimal mix of renewables includes significantly\nmore wind than photovoltaic solar.", "publisher": "Caltech Library", "publication_date": "2011-06" }, { "id": "authors:1d5mx-wca85", "collection": "authors", "collection_id": "1d5mx-wca85", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170810-135412130", "type": "conference_item", "title": "WAN-in-Lab: Motivation, deployment and experiments", "author": [ { "family_name": "Lee", "given_name": "George S.", "clpid": "Lee-George-S" }, { "family_name": "Andrew", "given_name": "Lachlan L. H.", "clpid": "Andrew-L-L-H" }, { "family_name": "Tang", "given_name": "Ao", "orcid": "0000-0001-6296-644X", "clpid": "Tang-Ao" }, { "family_name": "Low", "given_name": "Steven H.", "orcid": "0000-0001-6476-3048", "clpid": "Low-S-H" } ], "abstract": "WAN-in-Lab is a hardware testbed for the design, development, testing and evaluation of high speed network protocols. It uses real carrier-class networking hardware to avoid the artifacts introduced by network simulation and emulation, while being localized to allow detailed measurement of network performance. WAN-in-Lab is an open resource, available for use by the networking community. This paper describes the structure of WAN-in-Lab and the rationale behind it, issues encountered, and experimental results that illustrate its applications.", "publisher": "Caltech Library", "publication_date": "2007-02" } ]