Article
Computer Science, Artificial Intelligence
Yi Chen, Aimin Zhou
Summary: This study proposes a new algorithm, F-MOEA/D, for portfolio optimization problem, which combines exact methods and decomposition approaches to achieve better optimization results within a limited time.
COMPLEX & INTELLIGENT SYSTEMS
(2022)
Article
Operations Research & Management Science
Stephan Helfrich, Tyler Perini, Pascal Halffmann, Natashia Boland, Stefan Ruzika
Summary: This article explores the application of weighted Tchebycheff scalarization in multiobjective discrete optimization problems. By minimizing the weighted maximum distance between a feasible solution and a desirable reference point, any Pareto optimal image can be obtained. The article provides a comprehensive theory of eligible weights and analyzes the polyhedral and combinatorial structure of the weight set. These structural insights are linked to properties of the set of Pareto optimal solutions, contributing to a profound understanding of the weighted Tchebycheff scalarization method and its use in multiobjective optimization problems.
JOURNAL OF GLOBAL OPTIMIZATION
(2023)
Article
Energy & Fuels
Matteo Troncia, Jose Pablo Chaves Avila, Fabrizio Pilo, Tomas Gomez San Roman
Summary: The practices for procuring voltage control capability need to change due to the evolution of the power system driven by renewable sources, low carbon policies, and decentralisation. New mechanisms such as cost-based incentives and weighted auctions have been proposed to encourage effective investment in voltage control. The general mechanisms are designed to reduce overall procurement costs and can be applied in transmission and distribution networks, with a case study on the New-England power system demonstrating proof of concept.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2021)
Article
Energy & Fuels
Qunying Liu, Yingxing Song, Yazhou Jiang, Yin Xu, Shuheng Chen
Summary: This study proposes a reactive power compensation strategy for coordinated voltage control of PCC with large-scale wind farms to achieve the expected voltage quality of the power grid through a minimum amount of control actions in emergencies. In the event of an emergency, critical reactive power reserves are obtained to reduce the dimension and complexity of the control problem. The proposed technology has been validated on the IEEE 39-bus system.
FRONTIERS IN ENERGY RESEARCH
(2023)
Article
Energy & Fuels
Bukola Babatunde Adetokun, Christopher Maina Muriithi
Summary: This study investigates the impact of integrating large-scale DFIG-based WECS on the voltage stability of the Nigerian power grid, demonstrating the effectiveness of DFIG-based WECS in mitigating overvoltage issues while optimizing system stability. The optimal DFIG-based WECS penetration level that meets voltage criteria and system equipment loading requirements is found to be 35%, showing the potential of DFIG-based WECS as a viable solution for improving voltage stability in a weak national grid.
Article
Economics
Yi Wan, Tom Kober, Martin Densing
Summary: This paper investigates the use of nonlinear demand functions fitted to electricity market bid data in large-scale energy market models. The results show that the use of nonlinear demand curves improves the modeling performance, especially during high price load periods, and reduces levels of implied market power.
Article
Engineering, Environmental
Leyla Nourani, Seyed Nematolla Mosavi, Abdoulrasool Shirvanian
Summary: This study examines the economic impact of water market design on farmers' livelihood in Iran and finds that the formation of the water market leads to an increase in the gross margin of the total lands with irrigation network of Ramjerd plain.
Article
Energy & Fuels
Daniel Divenyi, Beata Polgari, Adam Sleisz, Peter Sores, David Raisz
Summary: The management of economically non-convex generators in deregulated electricity markets is a major challenge. The use of MICs as a method to represent non-convex generators on power exchanges has raised issues such as the lack of a direct mechanism to handle the Minimum Output Power (MOP) of generators, contradictory implications of bid price constraints and income criteria, and the potential for cheating opportunities due to distortions in social welfare calculation. New ways of MIC attachment are proposed to address these challenges, supported by comparative numerical simulations with realistic market data.
Article
Engineering, Electrical & Electronic
Alireza Nouri, Mohammad Jafarian, Andrew Keane
Summary: This study focuses on extracting the joint probability density function of uncertain parameters from historical data for emergency voltage control in power systems. By using data reconciliation and sampling techniques, the control can be achieved even with limited measurement data. A mixed-integer non-convex optimization problem, formulated as a stochastic programming problem, is solved using relaxation/approximation techniques. The results show that a novel combination of relaxation and approximation outperforms other methods in mitigating emergency under- and over-voltages.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
S. Rahman, S. Saha, M. E. Haque, S. N. Islam, M. T. Arif, M. Mosadeghy, A. M. T. Oo
Summary: This paper presents a framework for analyzing the voltage stability of the power grid considering the uncertainties of PV power generation and load demand using Monte Carlo simulation. The proposed methodology is validated by analyzing the voltage stability of the modified IEEE 14 bus test system with high penetration of PV energy sources and uncertainties associated with load demand. The results provide a holistic understanding of the voltage stability with different penetration levels of PV energy sources.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Review
Computer Science, Information Systems
Thomas Wolgast, Stephan Ferenz, Astrid Niesse
Summary: The liberalization of the energy system allows for market-based solutions in providing reactive power, but the procurement of reactive power through markets remains challenging. This survey provides a comprehensive overview of reactive power markets, including their characteristics, market design, analysis methods, and current research gaps.
Article
Green & Sustainable Science & Technology
Hanzhi Peng, Sheng Huang, Qiuwei Wu, Feifan Shen, Wu Liao, Xueping Li
Summary: This paper proposes a decentralized Volt/Var control method based on variable gradient projection (VGP) for the permanent magnet synchronous generator (PMSG)-based wind farm (WF). The method can achieve a fast Var response of each wind turbine (WT) to depress voltage fluctuations inside the WF caused by the stochastic wind and voltage disturbance of external grids, while considering the dynamic characteristics of the PMSGs and grid side converters (GSCs).
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Energy & Fuels
Justin Katigbak, Dahyeon Kang, Hwachang Song
Summary: As renewable energy sources become more widely used in modern power systems, the reliance on conventional generators is decreasing. This paper proposes an analysis method to identify critical buses in terms of voltage stability for power systems with high renewable energy penetration. The method combines modified continuation power flow and Q-V analysis to determine acceptable reactive power margins for each bus considering the intermittency of renewable energy sources. The study focuses on the future power systems in Korea with 16.05 GW of renewable energy, and various scenarios are studied to assess the voltage stability in different regions with high renewable energy penetration.
Article
Computer Science, Hardware & Architecture
Yue Zhuo, Zhiqiang Ge
Summary: Data-driven fault detection and classification systems are crucial for ensuring stability and security in modern industry. However, the security issue of these systems poses new challenges, as malicious adversarial attacks can severely damage the model's predictions. This article presents a scheme for formally and completely verifying the security properties of data-driven models using convex mathematical programming and a novel Pareto front approximation algorithm. The study covers both supervised and unsupervised models under different norms, providing deep insights into FDC systems' security. Comparison with related works validates the algorithm's performance in verification and Pareto front approximation.
IEEE TRANSACTIONS ON RELIABILITY
(2022)
Article
Automation & Control Systems
Xinxin Fang, Zhifang Yang, Juan Yu, Yi Wang
Summary: This article investigates the mismatch between DC and AC in the market clearing process, analyzes the physical properties and potential disadvantages of current industrial practices for handling this mismatch, and proposes a modified AC feasibility restoration framework based on optimal power flow algorithm and a strategy for selecting additional units to avoid price spikes.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Engineering, Electrical & Electronic
Mohammad Ghamsari-Yazdel, Hamid Reza Najafi, Nima Amjady
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
(2020)
Article
Computer Science, Information Systems
Shahab Dehghan, Nima Amjady, Petros Aristidou
IEEE SYSTEMS JOURNAL
(2020)
Article
Engineering, Electrical & Electronic
Moein Esfahani, Nima Amjady, Bahareh Bagheri, Nikos D. Hatziargyriou
IEEE TRANSACTIONS ON POWER SYSTEMS
(2020)
Article
Engineering, Electrical & Electronic
Payam Rabbanifar, Nima Amjady
IET GENERATION TRANSMISSION & DISTRIBUTION
(2020)
Article
Green & Sustainable Science & Technology
Mohammad Reza Ebrahimi, Nima Amjady
Summary: This paper presents a decision-driven stochastic adaptive-robust microgrid operation optimization model considering various uncertainties. It utilizes a combination of adaptive-robust optimization and stochastic programming to address continuous and binary uncertainties simultaneously. The proposed model and solution method are effectively demonstrated on the IEEE 69-bus test system in case studies.
IET RENEWABLE POWER GENERATION
(2021)
Article
Computer Science, Information Systems
Bahareh Bagheri, Nima Amjady, Shahab Dehghan
Summary: This article introduces a multi-scale multi-resolution uncertainty model for GMS problem in power system, addressing midterm and short-term uncertainties through plausible scenarios and polyhedral uncertainty sets. Affine policies are incorporated to make the approach tractable, and a stochastic affinely adjustable robust optimization (SAARO) problem is formulated to consider both midterm and short-term uncertainties. A new solution methodology involving stochastic optimization and probabilistic dual cut is presented, with numerical results confirming the effectiveness of the proposed model and approach.
IEEE SYSTEMS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Mohammad Ghamsari-Yazdel, Nima Amjady, Hamid Reza Najafi
Summary: This paper proposes a reintegration-based multi-objective intentional controlled islanding (ICI) model to enhance resiliency of electrical power systems under catastrophic events. The model relies on a mixed-integer linear programming approach and considers factors like charging reactive power, reliability, and capacity to reduce risks during reintegration. The model aims to address temporary load-generation imbalances in resulted islands to prevent frequency and voltage instability.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Tao Ding, Ming Qu, Nima Amjady, Fengyu Wang, Rui Bo, Mohammad Shahidehpour
Summary: This letter proposes a model for tracking the equilibrium point of the real-time locational marginal price based residential demand response program, where demand elasticity is modeled as a monotonically decreasing linear function of the LMP. The dual model, formulated as a convex quadratic problem using duality, is shown to be tractable to solve and find the global optimum. Numerical results on the IEEE 30-bus system verify the effectiveness of the demand response model.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Energy & Fuels
Juan Arteaga, Hamidreza Zareipour, Nima Amjady
Summary: This paper introduces a risk-based optimal sizing model for Storage as Transmission Alternative (SATA) for Transmission Congestion Relief (TCR) services. The model considers Energy Storage as a Service (ESaaS) concept, where SATA's idle capacity can be rented out for market participation and the fees collected are credited back to the ratepayers to offset the overall costs of removing network congestion. Simulation results provide insights into the financial benefits and risks of sharing SATA's excess capacity for additional revenues.
Editorial Material
Engineering, Electrical & Electronic
M. Esfahani, N. Amjady, B. Bagheri, Nikos D. Hatziargyriou
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Energy & Fuels
AmirAli Nazari, Reza Keypour, Nima Amjady
Summary: The paper proposes a cooperative community storage expansion plan to jointly invest in energy storage systems, alleviating the burden of high investment costs and increasing overall economic benefits. The modified Nash bargaining theory approach ensures fair implementation of the cooperative framework, highlighting the advantages of cooperation.
Article
Engineering, Electrical & Electronic
Fatemeh Teymoori Hamzehkolaei, Nima Amjady, Bahareh Bagheri
Summary: This paper addresses the planning problem of residential micro-CHP systems, modeling thermal and electrical load uncertainties using a two-stage adaptive robust optimization method. A solution method involving a C&CG algorithm and BCD method was proposed, showing effective performance in a practical case study.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2021)
Article
Engineering, Electrical & Electronic
Masoud Esmaili, Mohammad Ghamsari-Yazdel, Nima Amjady, C. Y. Chung
Summary: The proposed ICI-TEP method aims to improve the stability of islands by more efficient planning of transmission assets, resulting in more stable islands with lower load shedding and better coping with severe disturbances compared to conventional TEP.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Review
Engineering, Electrical & Electronic
Mehdi Izadi, Seyed Hossein Hosseinian, Shahab Dehghan, Ahmad Fakharian, Nima Amjady
Summary: This article presents a review of research works on evaluating power system resilience against disastrous and hazardous events. It discusses the differences between resilience and related concepts, presents resilience indices and techniques to increase power system resilience, reviews uncertainty handling approaches, and provides some concluding remarks.
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Masoud Esmaili, Mohammad Ghamsari-Yazdel, Nima Amjady, C. Y. Chung, Antonio J. Conejo
IEEE TRANSACTIONS ON POWER SYSTEMS
(2020)
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.
