Article
Management
Lucien Bobo, Lesia Mitridati, Josh A. Taylor, Pierre Pinson, Jalal Kazempour
Summary: This study introduces a novel price-region bid format that can better accommodate non-conventional sources of flexibility and facilitate their market access. The research shows that this new bid format is compatible with existing market structures and satisfies desirable market properties under common assumptions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Yesim A. Baysal, Seniha Ketenci, Ismail H. Altas, Temel Kayikcioglu
Summary: The study introduces a non-dominated sorting multi-objective symbiotic organism search algorithm for feature selection in brain-computer interface systems, which shows promising results in improving classification accuracy and reducing the number of features in two datasets. It verifies the superior performance of the proposed method compared to existing techniques, indicating its efficiency and practicality for BCI applications.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Energy & Fuels
Hossein Chabok, Jamshid Aghaei, Morteza Sheikh, Mahmoud Roustaei, Mohsen Zare, Taher Niknam, Matti Lehtonen, Miadreza Shafi-khah, Joao P. S. Catalao
Summary: This paper proposes an optimal allocation scheme for a Wind-Storage Unit (WSU) by evaluating the optimal location of the generation unit based on the variation of transmission lines congestion. The method converts a tri-level optimization model into a bi-level optimization model, and uses binary particle swarm optimization algorithm and unscented transform to model the uncertainties associated with the output power of wind turbines.
Article
Thermodynamics
Yeong Geon Son, Byeong Chan Oh, Moses Amoasi Acquah, Sung Yul Kim
Summary: This paper focuses on reducing the curtailment of wind turbines (WT) and minimizing the investment cost of IES. The IES integrates various energies mix and aims to improve the acceptability and efficiency of renewable energy sources. Using Multi-Objective Optimization Programming (MOP), the paper proposes an optimal facility combination set (FCS) of IES that satisfies ISO and IPP requirements. The case study results provide the best configuration of the IES energy mix with the highest economic value and efficiency while meeting ISO and IPP perspectives.
Article
Engineering, Multidisciplinary
Sumit Verma, Aprajita Salgotra, Chandan Kumar Shiva, B. Vedik
Summary: This paper deals with the installation and framing of proper control strategy of flexible AC transmission systems (FACTs) devices by utilizing evolutionary optimization technique. The study implements the symbiotic organism search (SOS) algorithm for optimal FACTs devices planning under various loading conditions. The simulation results show that the proposed SOS algorithm can significantly reduce system operating cost, line loss, and congestion in the transmission lines.
INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT
(2023)
Article
Economics
Frederic Godin, Zinatu Ibrahim
Summary: This paper applies principal component analysis (PCA) to analyze congestion components in local electricity price data, aiming to detect congestion patterns in electricity transmission grids. Through data visualization tools, these patterns can be identified intuitively. The study focuses on three North American power systems and proposes a simple time series model representing the evolution of PCA scores.
Article
Economics
Rabindra Nepal, Ronald Sofe, Tooraj Jamasb, Vikash Ramiah
Summary: The small island economy of Papua New Guinea is facing electricity shortages and is implementing power sector reforms to attract private capital. However, there is a gap between the theory and practice of the reforms, and the insolvency of the state-owned utility poses a revenue risk to independent power producers.
Article
Multidisciplinary Sciences
Salisu Mohammed, Yusuf A. Sha'aban, Ime J. Umoh, Ahmed T. Salawudeen, Sami M. Ibn Shamsah
Summary: This paper presents a hybrid Smell Agent Symbiosis Organism Search Algorithm (SASOS) for optimal control of autonomous microgrids. The hybrid algorithm reduces the imbalance between exploitation and exploration and increases the effectiveness of control optimization in microgrids.
Article
Mathematics
Mikhail E. Semenov, Sergei Borzunov, Peter A. Meleshenko, Alexey Lapin
Summary: This article discusses a model that describes the hysteretic behavior of consumers in mono-product markets. The demand generation of individual consumers is modeled using a non-ideal relay with inverted thresholds, and the sales rate is defined analogously to the Preisach converter. The article examines the optimal production, storage, and distribution of goods, taking into account the hysteretic nature of the demand curve. The problem is transformed into a non-classical optimal control problem with hysteretic non-linearities and is solved using Pontryagin's maximum principle. Computational experiments are presented to illustrate the theoretical assumptions.
Article
Automation & Control Systems
Tianyang Zhao, Haoyuan Yan, Xiaochuan Liu, Zhaohao Ding
Summary: The electrification of vehicles has strengthened the interaction between power systems and transportation systems, resulting in the formation of coupled transportation power systems (CTPSs). A novel optimal traffic power flow (OTPF) problem is proposed to analyze the spatial and temporal congestion propagation on CTPSs. This problem considers congested roads, transmission lines, and charging stations. The spatial and temporal distribution of electric vehicles (EVs) on roads and charging stations, connected by multilayer time-space networks (TSNs), is used to depict the traffic flow. The distribution is obtained by optimizing the charging, discharging, routing, and origin-destination pairing of EV fleets on TSNs, while the power flow is captured using dynamic optimal power flow problems with security constraints. An algorithm combining the alternating direction multiplier method with the convex-concave procedure is proposed to solve OTPFs. The results validate the effectiveness of the proposed scheme for managing congestion on CTPSs.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Thermodynamics
Javad Salehi, Amin Namvar, Farhad Samadi Gazijahani, Miadreza Shafie-khah, Joao P. S. Catalao
Summary: Natural gas is considered a key player in the transition to a lower-carbon economy, serving as an alternative to coal and a backup resource to intermittent renewable energy sources. An innovative model was proposed to optimally manage electricity and natural gas grids, utilizing various technologies to reduce operational costs and alleviate gas network congestion while improving energy efficiency. The model incorporates demand response programs and Power-to-X technologies, demonstrating significant reductions in operation costs and improved performance in addressing network congestions.
Article
Management
Dario Paccagnan, Martin Gairing
Summary: In this work, the problem of minimizing social cost in atomic congestion games is addressed. Lower bounds on the approximation ratio achievable in polynomial time are presented, and it is demonstrated that efficiently computable taxes result in polynomial time algorithms matching such bounds. Surprisingly, these results show that indirect interventions, in the form of efficiently computed taxation mechanisms, yield the same performance achievable by the best polynomial time algorithm, even when the latter has full control over the agents' actions. In short: Judiciously chosen taxes achieve optimal approximation. Three technical contributions underpin this conclusion.
OPERATIONS RESEARCH
(2023)
Article
Automation & Control Systems
Manjulata Badi, Sheila Mahapatra, Saurav Raj
Summary: Optimizing power generation with load balancing is crucial for planning and operation of the electricity grid. This article proposes a hybrid butterfly optimization algorithm to address load balancing, demonstrating improved performance in practical applications.
OPTIMAL CONTROL APPLICATIONS & METHODS
(2023)
Article
Engineering, Multidisciplinary
Jun-Hua Zhu, Jie-Sheng Wang, Xing-Yue Zhang, Hao-Ming Song, Zhi-Hao Zhang
Summary: A mathematical distribution coyote optimization algorithm (MDCOA) is proposed, which improves the randomness and diversity of offspring by adding crossover operations. The step size is generated by random numbers with seven mathematical distributions to balance the exploration and exploitation process. The MDCOA effectively solves the optimal power flow (OPF) problem in power systems.
ALEXANDRIA ENGINEERING JOURNAL
(2023)
Article
Mathematics, Applied
Abhilipsa Sahoo, Prakash Kumar Hota, Preeti Ranjan Sahu, Faisal Alsaif, Sager Alsulamy, Taha Selim Ustun
Summary: In a deregulated electricity market, all market players have open access. The system operator ensures the dispatch of all contracted power, but excessive line flows may threaten system security. Therefore, congestion is checked when line flows exceed acceptable limits. Different curtailment strategies are used by the system operator to manage congestion and limit requested transactions. This study presents an optimal power dispatch model using a modified moth flame optimization technique and analyzes the impact of congestion management on power dispatch in both bilateral and multilateral markets. Furthermore, the effect of FACTS devices on reducing congestion and curtailing power is studied. Verification studies show significant reductions in congestion costs using the proposed solution.
Article
Engineering, Electrical & Electronic
Subhodip Saha, Vivekananda Mukherjee
IET GENERATION TRANSMISSION & DISTRIBUTION
(2016)
Article
Computer Science, Artificial Intelligence
Subhodip Saha, V. Mukherjee
Article
Engineering, Electrical & Electronic
Subhodip Saha, Vivekananda Mukherjee
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
(2019)
Article
Computer Science, Artificial Intelligence
Subhodip Saha, V. Mukherjee
Summary: This article introduces a novel optimization technique for allocating distributed generation units optimally in radial distribution systems, utilizing a new metaheuristic called multi-objective modified symbiotic organisms search. The proposed algorithm is tested on benchmark tests and real-world applications to demonstrate its global optimization capability.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Subhodip Saha, V Mukherjee
APPLIED INTELLIGENCE
(2018)
