Engineering topics

O'Neill, Richard P.

Publications and source records attributed to O'Neill, Richard P..

6 records

DOE OSTI2024

Grid Optimization Competition Challenge 3 Problem Formulation

This report contains the problem formulation for the Grid Optimization (GO) Competition Challenge 3. The Grid Optimization Competition is run by a team of researchers from a number of organizations, including the sponsor Advanced Research Projects Agency - Energy (ARPA-E), lead organization Pacific Northwest National Laboratory (PNNL), and technical contributors from Los Alamos National Laboratory (LANL), National Renewable Energy Laboratory (NREL), Texas A&M University (TAMU), Georgia Institute of Technology (GT), University of Wisconsin (UW), and others. The GO Competition poses challenge problems in the field of power grid management, invites entrants to develop solvers for these problems, invokes the solvers on a set of problem instances using common hardware, ranks the solvers according to their performance, and awards prizes according to the rankings. The overall goal of the GO Competition is to spur innovative research on high impact and computationally challenging problems in power grid management from initial development through commercial deployment. Complete information about the GO Competition can be found online at [2]. The webpage covers previous Challenges, rules, timeline, registration information, data formats, scoring methods, computational platform information, information on supported solvers and languages, sponsor information, frequently asked questions, administrator contact information, publicly available problem instances, computer code for reading and evaluating problem and solution data, a sandbox for testing solvers, and a solver submission interface, results, and publications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Average Incremental Cost Pricing for the AC Unit Commitment Problem [Rev. 1]

Unit Commitment (UC) problems that consider the Alternating Current (AC) model of the transmission network have long been considered intractable to solve at scale by the power system community. Recently, the Grid-Optimization (GO) Competition held by the Advanced Research Project Agency-Energy (ARPA-E) has facilitated the development of the first algorithms to solve large-scale ACUC problems. This new capability opens a path towards the explicit consideration of the AC transmission network model in UC problems used to clear day-ahead electricity markets. This calls for the analysis of electricity market structures that accommodate both the continuous non-linearity of the AC transmission network and the discrete non-linearity of the UC problem simultaneously. This paper serves as an initial effort to do so by proposing an Average Incremental Cost (AIC) pricing structure that is designed around the ACUC problem. In particular, an AIC one-pass pricing problem is proposed that represents a continuously constrained variant of the ACUC problem and allows for the computation of Locational Incremental Prices (LIPs) for both real and reactive power as the local optimal Lagrange multipliers of the power balance constraints. To avoid degeneracy, the pricing problem includes a small parameter ϵ > 0. Under certain assumptions market participants are shown to realize profit that converges to a non-negative value as ϵ approaches zero, practically ensuring profitability for small values of ϵ. We additionally provide many simple and important examples that provide intuition and insights into the proposed prices. Examples illustrate the basic concept of AIC pricing, the derived profitability results, the existence of multiple LIPs, the importance of including reactive power in the dispatch and pricing problems, the need for reactive power prices, and the improved incentives exhibited by LIPs as compared to traditional Locational Marginal Prices (LMPs). We additionally indicate many directions for future work including analysis of larger test cases.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Grid Optimization Competition on Synthetic and Industrial Power Systems

This paper summarizes a grid optimization (GO) competition effort in the United States to find the best solution strategies for up to interconnect-scale power system networks with around 32,000 buses. The optimization problem is a mixedinteger, non-convex non-linear problem, (MINLP) and includes discrete variables such as unit commitment and line switching, control settings (transformer taps and phase shifters with impedance correction tables), and bus shunts. The case study includes six actual industry grids as well as 16 realistic synthetic grids created by three different dataset teams. The winners are selected and ranked based on scoring criteria, which consider the solution quality (such as objective functions) within time limits. Nine winner teams are selected from 26 competitor teams. The results achieved by different teams are described and the performance of different algorithms on synthetic grids and actual industry grids are compared and analyzed.

mixed-integer non-linear programming↗

DOE OSTI2016

Marginal Loss Calculations for the DCOPF

The purpose of this paper is to explain some aspects of including a marginal line loss approximation in the DCOPF. The DCOPF optimizes electric generator dispatch using simplified power flow physics. Since the standard assumptions in the DCOPF include a lossless network, a number of modifications have to be added to the model. Calculating marginal losses allows the DCOPF to optimize the location of power generation, so that generators that are closer to demand centers are relatively cheaper than remote generation. The problem formulations discussed in this paper will simplify many aspects of practical electric dispatch implementations in use today, but will include sufficient detail to demonstrate a few points with regard to the handling of losses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

Dual pricing algorithm in ISO markets

The challenge to create efficient market clearing prices in centralized day-ahead electricity markets arises from inherent non-convexities in unit commitment problems. When this aspect is ignored, marginal prices may result in economic losses to market participants who are part of the welfare maximizing solution. In this essay, we present an axiomatic approach to efficient prices and cost allocation for a revenue neutral and non-confiscatory day-ahead market. Current cost allocation practices do not adequately attribute costs based on transparent cost causation criteria. Instead we propose an ex post multi-part pricing scheme, which we refer to as the Dual Pricing Algorithm. Lastly, our approach can be incorporated into current dayahead markets without altering the market equilibrium.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Optimal Transmission Switching Using the IV-ACOPF Linearization

In this paper we seek to investigate the performance of transmission switching using the iterative linear program approximation to the Current Voltage AC Optimal Power Flow (IV-ACOPF). Several different methods of using this switching are investigated to find a method that addresses the MIP challenges and is both fast and accurate. We consider opening only one line, opening up to five lines, and progressively opening one line at a time. The linear method with switching is much faster than the nonlinear ACOPF and generally finds solutions within 1% of the nonlinear ACOPF.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗