Article
Computer Science, Information Systems
Moises Flores, Leonardo H. Macedo, Ruben Romero
Summary: This article optimizes the operation cost of an electrical power system by solving the optimal transmission switching (OTS) problem, reducing the number of disconnected lines and avoiding system islanding. The proposals have been proven effective in increasing the system's operational efficiency.
IEEE SYSTEMS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Peijie Li, Xiaoqian Huang, Junjian Qi, Hua Wei, Xiaoqing Bai
Summary: This study incorporates network connectivity into the mixed-integer linear programming model to solve the optimal transmission switching problem, effectively reducing the number of constraints. Case studies validate the effectiveness of the proposed model.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Automation & Control Systems
Chin-Yao Chang, Sonia Martinez, Jorge Cortes
Summary: This article presents an approach to tackle optimal transmission switching (OTS) problems using semidefinite programming formulation for optimal power flow (OPF) problem. It introduces a physically inspired, virtual-voltage approximation and a graph partition-based algorithm to handle the complexity caused by discrete variables. Simulation results show high accuracy and affordable computational requirements of the proposed approach on IEEE bus test cases.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Bahriye Akay, Dervis Karaboga, Beyza Gorkemli, Ebubekir Kaya
Summary: This paper reviews the use of Artificial Bee Colony algorithm for solving discrete numeric optimization problems, discussing various encoding types, search operators and selection operators integrated into ABC. It is the first comprehensive survey study on this topic and aims to benefit readers interested in utilizing ABC for binary, integer and mixed integer discrete optimization problems.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Interdisciplinary Applications
Seolhee Cho, Can Li, Ignacio E. Grossmann
Summary: This paper reviews the basic concepts and optimization models for expansion planning of power systems, and introduces simplification methods for addressing computational challenges. It also discusses the definition of power system reliability. The goal of this paper is to provide a research overview, discuss trends, and suggest directions for future research in power system expansion planning.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Article
Operations Research & Management Science
Mateus Martin, Fabio Luiz Usberti, Christiano Lyra
Summary: In this paper, we propose a new method to solve the Maintenance Resources Allocation Problem (MRAP) by establishing a mathematical model and utilizing an integer linear programming (ILP) solver. This method can be applied to single or multiple distribution networks and achieves optimal maintenance trade-offs in a short running time.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Ahmad M. Alshamrani
Summary: This research focuses on developing a mathematical methodology for joint transmission network and wind power investment problem under a centralized approach. The objective function is defined as the ratio of total cost to total wind power generation, allowing the operator to minimize overall cost while maximizing wind power output.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Anton Hinneck, David Pozo
Summary: This paper proposes a method to solve the optimal transmission switching problem (OTSP) by changing the topology of a power grid to improve dispatch. The method uses parallel heuristics to generate candidate solutions and combines them with branch-and-bound (B & B) algorithms. Experimental results show that the method performs well on large problem instances and consistently improves upon off-the-shelf solver performance.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Ilya Tyuryukanov, Marjan Popov, Jorrit A. Bos, Mart A. M. M. van der Meijden, Vladimir Terzija
Summary: This paper presents a new formulation for intentional controlled islanding (ICI) of power transmission grids based on mixed-integer linear programming (MILP) DC optimal power flow (OPF) model. It proposes several improvements to address deficiencies in the existing formulation, such as a new optimization objective, island connectivity constraints, constraints for DC OPF with switching, and a heuristic to find initial feasible solutions. The proposed improvements reduce the optimality gaps compared to the benchmark model on multiple test instances.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Management
Thomas L. Magnanti
Summary: Optimization is one of the most fundamental contributions of management science/operations research, with early researchers laying the foundations for fields such as linear programming and integer programming. With the development of computational methods, optimization has been widely applied in various fields.
MANAGEMENT SCIENCE
(2021)
Article
Computer Science, Software Engineering
Ilias Zadik, Miles Lubin, Juan Pablo Vielma
Summary: We investigate the structural geometric properties of mixed-integer convex representable (MICP-R) sets and compare them with the class of mixed-integer linear representable (MILP-R) sets. We provide examples of MICP-R sets that are countably infinite unions of convex sets with countably infinitely many different recession cones, and countably infinite unions of polytopes with different shapes. These examples highlight the differences between MICP-R sets and MILP-R sets.
MATHEMATICAL PROGRAMMING
(2023)
Article
Computer Science, Interdisciplinary Applications
Arturo J. Fernandez
Summary: In industrial settings, determining the optimal inspection time for reliability testing is crucial. By using constrained optimization problems and Weibull failure counts as decision criteria, the best reliability sampling plan can be developed to assess the acceptability of lots and production processes.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Arman Amini Badr, Amin Safari, Sajad Najafi Ravadanegh
Summary: This paper investigates the impact of microgrids on power system islanding and proposes an algorithm that utilizes slow coherency theory and mixed integer linear programming to determine appropriate islanding schemes in a splitting power system. An optimization model is developed by considering the features of microgrids, and it finds cut-sets and islands arrangement. The performance of the proposed algorithm is validated through time domain simulation on the IEEE118 bus test system.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Computer Science, Software Engineering
Felix Bestehorn, Christoph Hansknecht, Christian Kirches, Paul Manns
Summary: We explored an extension of Mixed-Integer Optimal Control Problems by introducing switching costs, allowing for penalization of chattering and expanding modeling capabilities. By reformulating the rounding problem as a shortest path problem, we achieved minimization of switching costs while maintaining approximability. The effectiveness of our approach was demonstrated through comparison with an integer programming method on a benchmark problem.
MATHEMATICAL PROGRAMMING
(2021)
Article
Environmental Studies
Nelson Morales, Diego Mancilla, Roberto Miranda, Javier Vallejos
Summary: This study proposes an improved method for designing a sublevel stoping mine, which determines the optimal layout of stopes through enumeration and optimization models. The method ensures the profitability and geotechnical stability of the generated stopes, and organizes them into drifts and levels for a more operational layout. The method is suitable for algorithmic and theoretical contributions, and has been tested on different block models, showing both feasibility and efficiency of the resulting optimal layouts. Sensibility analyses demonstrate the robustness of the optimal solutions to variations in economic values and geometric locations of the stopes.
Article
Automation & Control Systems
Mahdi Khodayar, Jianhui Wang
Summary: This study proposes a new deep generative architecture (DGA) based on the LSTM network for probabilistic time-varying parameter identification. By learning the continuous probability density function, composite load modeling is achieved, showing accurate estimation of uncertain power resources.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Quantum Science & Technology
Rebekah Herrman, James Ostrowski, Travis S. Humble, George Siopsis
Summary: This study identifies how the structure of problem instances can be used to determine lower bounds for the circuit depth required for each iteration of QAOA, and examines the relationship between problem structure and a variety of combinatorial optimization problems. By analyzing the scaling of circuit depth, it is suggested that MaxCut, MaxIndSet, and some instances of vertex covering and Boolean satisfiability problems are suitable for QAOA approaches, while knapsack and traveling salesperson problems are not.
QUANTUM INFORMATION PROCESSING
(2021)
Review
Green & Sustainable Science & Technology
S. Yin, J. Wang, Z. Li, X. Fang
Summary: With the increasing penetration of solar energy in the energy systems, the correct modeling of solar generation in the market and addressing uncertainty-based operational problems have become crucial issues. Unlike other renewable resources, solar power can be easily integrated in a distributed manner on the demand side with potential for significant future expansion. The electricity markets are transitioning from a deterministic and centralized framework to a stochastic and decentralized one, driven by the development of deregulated power markets.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Automation & Control Systems
Liudong Chen, Nian Liu, Chenchen Li, Jianhui Wang
Summary: This interdisciplinary P2P energy sharing framework proposed in this article considers both technical and sociological aspects, based on prospect theory and stochastic game theory. Under this framework, producers and consumers participate with different roles and strategies, addressing problems arising from social attributes.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Quantum Science & Technology
Rebekah Herrman, Lorna Treffert, James Ostrowski, Phillip C. Lotshaw, Travis S. Humble, George Siopsis
Summary: The performance of QAOA algorithm on MaxCut problem is studied under different graph characteristics, revealing correlations with graph symmetries, odd cycles, and density. Data analysis demonstrates some factors that can predict the success of QAOA.
QUANTUM INFORMATION PROCESSING
(2021)
Article
Quantum Science & Technology
Phillip C. Lotshaw, Travis S. Humble, Rebekah Herrman, James Ostrowski, George Siopsis
Summary: The study numerically simulates the performance of the QAOA algorithm on small to medium-sized graphs for the MaxCut problem, finding that parameter concentration leads to two median-angle heuristics that help overcome difficulties in QAOA parameter optimization. Additionally, the study analyzes the probability of measuring an optimal solution, revealing increasing variations between graphs as depth increases.
QUANTUM INFORMATION PROCESSING
(2021)
Article
Computer Science, Artificial Intelligence
Rebekah Herrman, Lorna Treffert, James Ostrowski, Phillip C. Lotshaw, Travis S. Humble, George Siopsis
Summary: Researchers have developed a global variable substitution method to simplify n-variable monomials in combinatorial optimization problems, reducing the quantum unitary circuit depth needed. They found that using the substitution method in 3-SAT problems can decrease the upper bound of the unitary circuit depth.
Article
Energy & Fuels
Najmaddin Akhundov, Marzieh Bakhshi, James Ostrowski
Summary: This study proposes using convex hull pricing to address the risk associated with uncertainty in large power systems scheduling problems. By pricing the uncertainty risk a priori, it can provide a solution to the challenges of computational time and achieving a balanced cost-benefit equilibrium.
ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS
(2023)
Article
Computer Science, Theory & Methods
Ruslan Shaydulin, Phillip C. Lotshaw, Jeffrey Larson, James Ostrowski, Travis S. Humble
Summary: Researchers propose a simple rescaling scheme to overcome the difficulty of parameter optimization in the weighted MaxCut problem. They show that the empirical parameters can be successfully applied to weighted MaxCut instances, achieving approximation ratios equivalent to exhaustive optimization in 96.35% of cases among a dataset of nearly 34,701 instances.
ACM TRANSACTIONS ON QUANTUM COMPUTING
(2023)
Article
Energy & Fuels
Amelia McIlvenna, Ben Ollis, James Ostrowski
Summary: By studying a residential microgrid, it is found that the value of using stochastic scheduling methods compared to deterministic methods is minimal. Instead, considering longer time horizons is a more effective use of computational resources.
ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS
(2022)
Proceedings Paper
Computer Science, Theory & Methods
Mahdi Khodayar, Jianhui Wang
Summary: This paper proposes a deep GDL algorithm for learning the topological patterns of power grids by capturing the probability density functions of nodes and edges. Simulation results demonstrate the significant accuracy of the created synthetic power grids in terms of topological metrics and power flow measurements.
2021 INTERNATIONAL CONFERENCE ON SMART ENERGY SYSTEMS AND TECHNOLOGIES (SEST)
(2021)
Proceedings Paper
Energy & Fuels
Shengfei Yin, Jianhui Wang, Yanling Lin, Xin Fang, Jin Tan, Haoyu Yuan
Summary: With renewable resources increasingly entering power systems, energy storage systems (ESSs) have become essential for providing energy arbitrage and ancillary services. This paper proposes a general framework in the current electricity market environment to model the participation of multi-type ESSs and evaluate their performance, demonstrating the excellent potential of ESSs in providing ancillary services for the bulk power system.
2020 52ND NORTH AMERICAN POWER SYMPOSIUM (NAPS)
(2021)
Proceedings Paper
Energy & Fuels
Xin Fang, Jin Tan, Haoyu Yuan, Shengfei Yin, Jianhui Wang
Summary: With the increasing penetration of photovoltaic generation, electric power systems require more flexible resources and renewable generation, including PV, to provide more flexible ancillary services to improve system reliability and increase PV profitability.
2020 52ND NORTH AMERICAN POWER SYMPOSIUM (NAPS)
(2021)
Article
Engineering, Electrical & Electronic
Mingjian Cui, Jianhui Wang
Summary: This paper proposed a new defense mechanism called DH-MTD to hide the reactance of each phase in unbalanced AC distribution system and ensure system voltage stability. By using data-driven methods to combat cyberattacks, the effectiveness of DH-MTD was demonstrated in an unbalanced IEEE 123-bus distribution system.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Review
Energy & Fuels
Mandi Khodayar, Guangyi Liu, Jianhui Wang, Mohammad E. Khodayar
Summary: With the rapid growth of power systems measurements, utilizing deep learning algorithms for power systems data processing has become a research trend. The study reveals the theoretical advantages of deep learning in power systems research and discusses solutions under various problem settings.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2021)
