Article
Computer Science, Artificial Intelligence
Hossein Jafari Siahroodi, Hamed Mojallali, Seyed Saeid Mohtavipour
Summary: This study presents a new stochastic multi-objective framework for utilizing plug-in electric vehicles (PEVs) in reactive power compensation in a distribution grid. The proposed framework can optimize the reactive capability curve and total network loss simultaneously, providing economic and technical advantages. Additionally, a hybrid algorithm combining gray wolf optimization and differential evolution algorithm is presented for solving the multi-objective problem, with the best compromise solution selected using fuzzy decision-making approach.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Energy & Fuels
Yi Guo, Xuejiao Han, Xinyang Zhou, Gabriela Hug
Summary: In this paper, a two-stage electricity market framework is proposed to explore the involvement of distributed energy resources (DERs) in both day-ahead (DA) and real-time (RT) markets. The optimal bidding strategies of the aggregated DERs in the DA market are determined using distributionally robust optimization, while online incentive signals are generated for DER-owners to optimize social-welfare in consideration of network operational constraints. A bi-level time-varying optimization problem is proposed in the RT market to design the online incentives for balancing services, taking into account the RT imbalance penalty for distribution system operators (DSOs) and the costs of individual DER-owners. Simulation results demonstrate the necessity and robustness of this two-stage design for network operations.
Article
Engineering, Electrical & Electronic
Dongliang Xiao, Haoyong Chen, Chun Wei, Xiaoqing Bai
Summary: This study proposes a statistical measure and a stochastic optimization model for generating risk-seeking wind power offering strategies in electricity markets. The statistical measure, called value at best (VaB), quantifies potential high profits in the best-case scenarios of a profit distribution. The stochastic optimization model based on VaB helps wind power producers manage potential high profits from a probabilistic perspective.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2022)
Article
Energy & Fuels
Yu Zhou, Zhengshuo Li, Guangrui Wang
Summary: This paper suggests leveraging the reactive power range embedded in wind farms to improve safety and optimality during the power system reactive power optimization process. An uncertain reactive power optimization problem involving wind farm reactive power range is introduced, which is recast as a deterministic optimization problem. The study confirms that wind farms are competent reactive power resources even with notable uncertainty.
Article
Energy & Fuels
Mohammad Farahani, Abouzar Samimi, Hossein Shateri
Summary: This paper presents a bidding strategy model for a Battery Energy Storage System (BESS) in a power market. The study shows that the participation of BESS in the market can reduce the prices of active and reactive power, as well as the overall cost of market execution, while ensuring a suitable profit level for the private owners of BESS.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Economics
Chin-Yi Tseng, Chia-Yen Lee, Qunwei Wang, Changsong Wu
Summary: This study investigates the impact of market power on economic efficiency and revenue sharing in a bi-level market, using stochastic programming and robust optimization to address price uncertainty. Results suggest that controlling price volatility in the upstream contract market can improve productivity and support policies.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Engineering, Electrical & Electronic
Sarthak Gupta, Vassilis Kekatos, Ming Jin
Summary: Coordinating inverters at scale under uncertainty is crucial for integrating renewables in distribution grids. This study proposes integrating DNN-based inverter policies into the OPF to guarantee feasibility. Two OPF alternatives are used to train the DNNs, confining voltage deviations and chance constraints. The trained DNNs can be driven by partial or noisy descriptors of grid conditions, and a gradient-free variant is also proposed for cases where computing gradients is challenging.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Computer Science, Information Systems
Mehdi Tavakkoli, Sajjad Fattaheian-Dehkordi, Mahdi Pourakbari-Kasmaei, Matti Liski, Matti Lehtonen
Summary: This article introduces a novel approach that allows wind power producers to participate in both energy and reserve markets alongside conventional generators, aiming to ensure a higher level of reliability. Simulation results demonstrate that both conventional generators and wind power producers will receive more revenue in both markets by the suggested scheme, despite the fact that demands should pay more.
IEEE SYSTEMS JOURNAL
(2022)
Article
Green & Sustainable Science & Technology
Devika Jay, K. S. Swarup
Summary: Modern power systems are becoming smarter and more competitive, with real-time pricing of active and reactive power considered an efficient energy management method. However, the procurement of reactive power through market mechanisms in real-time has not yet been implemented. This paper details the challenges faced in implementing reactive power markets and presents a review of existing mechanisms to address these challenges, as well as a framework for reactive power ancillary service in a smart grid.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Engineering, Electrical & Electronic
Dongliang Xiao, Mohamed Kareem AlAshery, Qiao Wei
Summary: This paper proposes a stochastic optimization model for generating the optimal price-maker trading strategy for a wind power producer using virtual bidding. The model uses virtual bidding to improve the wind power producer's market power by trading at multiple buses. The optimal strategy is generated by solving a bi-level nonlinear stochastic optimization model. The paper also proposes a method to reduce the computational cost by reducing the number of buses considered for virtual bidding.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2022)
Article
Energy & Fuels
Ehsan Heydarian-Forushani, Salah Bahramara, Pouria Sheikhahmadi, Mehdi Zeraati, Seifeddine Ben Elghali
Summary: This paper presents a novel framework for optimizing the operation strategy of a virtual power plant (VPP) involving various stakeholders. A proactive stochastic bi-level model is developed to simulate the behavior of private owners within the VPP, and it is converted to a mixed-integer linear programming problem. The impacts of different pricing schemes on the market trading strategy and interactions between the VPP and private owners are investigated through comparative case studies.
JOURNAL OF ENERGY STORAGE
(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
Engineering, Electrical & Electronic
Hyeong Jun Kim, Ramteen Sioshansi, Antonio J. Conejo
Summary: The study introduces a two-stage stochastic model for optimizing energy storage operation, considering uncertain real-time prices during day-ahead commitments and the price impact of charging and discharging. It demonstrates the value of stochastic modeling when prices respond to energy storage operation, showing that prices can influence decisions such as simultaneous charging and discharging. A practical case study illustrates how to calibrate price-response functions and apply the model.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2021)
Article
Engineering, Electrical & Electronic
Aayushya Agarwal, Priya L. Donti, J. Zico Kolter, Larry Pileggi
Summary: High penetrations of renewables and extreme weather phenomena have increased the need for large-scale stochastic optimization in power grid operations and planning. This study proposes a generic methodology based on robust optimization and minimax formulation to accommodate the probabilistic nature of loads and renewable generation sources. The authors use techniques from adversarial robustness in machine learning to improve scalability and convergence.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Nibha Rani, Tanmoy Malakar
Summary: The research focuses on understanding the Effective Reactive Reserve (ERR) under intermittent Wind Power (WP) and uncertain demand. A stochastic multivariate ERR assessment and optimization problem is proposed and solved by modeling multivariate uncertainty, studying the stochastic behavior of ERR, and optimizing ERR. The results show that the uncertainties in WP generation and consumer demand significantly impact ERR, and the proposed optimization strategy improves the expected value of ERR.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Mehrdad Aghamohamadi, Nima Amjady, Ahmad Attarha
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
(2020)
Article
Computer Science, Interdisciplinary Applications
Abdollah Ahmadi, Hani Mavalizadeh, Ali Esmaeel Nezhad, Pierluigi Siano, Heidar Ali Shayanfar, Branislav Hredzak
SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL
(2020)
Article
Engineering, Electrical & Electronic
Ali Akhavein, Heidarali Shayanfar
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
(2020)
Article
Engineering, Electrical & Electronic
Ebad Talebi Ghadikolaee, Ahad Kazemi, Heydar Ali Shayanfar
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
(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)
Article
Engineering, Electrical & Electronic
Sajjad Solat, Farrokh Aminifar, Heidarali Shayanfar
Summary: The high penetration of renewable distributed generations poses challenges for electric distribution networks due to uncertainties and limits in hosting capacity. The impact of correlated uncertainties on distributed generation hosting capacity is evaluated, with proposed methods for modelling and optimizing capacity improvement considering operational constraints. The results highlight the significant effect of uncertainty correlations on network capacity.
IET GENERATION TRANSMISSION & DISTRIBUTION
(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
Thermodynamics
Yong Cheng, Fukai Song, Lei Fu, Saishuai Dai, Zhiming Yuan, Atilla Incecik
Summary: This paper investigates the accessibility of wave energy absorption by a dual-pontoon floating breakwater integrated with hybrid-type wave energy converters (WECs) and proposes a hydraulic-pneumatic complementary energy extraction method. The performance of the system is validated through experiments and comparative analysis.
Article
Thermodynamics
Jing Gao, Chao Wang, Zhanwu Wang, Jin Lin, Runkai Zhang, Xin Wu, Guangyin Xu, Zhenfeng Wang
Summary: This study aims to establish a new integrated method for biomass cogeneration project site selection, with a focus on the application of the model in Henan Province. By integrating Geographic Information System and Multiple Criterion Decision Making methods, the study conducts site selection in two stages, providing a theoretical reference for the construction of biomass cogeneration projects.
Article
Thermodynamics
Mert Temiz, Ibrahim Dincer
Summary: The current study presents a hybrid small modular nuclear reactor and solar-based system for sustainable communities, integrating floating and bifacial photovoltaic arrays with a small modular reactor. The system efficiently generates power, hydrogen, ammonia, freshwater, and heat for residential, agricultural, and aquaculture facilities. Thermodynamic analysis shows high energy and exergy efficiencies, as well as large-scale ammonia production meeting the needs of metropolitan areas. The hybridization of nuclear and solar technologies offers advantages of reliability, environmental friendliness, and cost efficiency compared to renewable-alone and fossil-based systems.
Editorial Material
Thermodynamics
Wojciech Stanek, Wojciech Adamczyk
Article
Thermodynamics
Desheng Xu, Yanfeng Li, Tianmei Du, Hua Zhong, Youbo Huang, Lei Li, Xiangling Duanmu
Summary: This study investigates the optimization of hybrid mechanical-natural ventilation for smoke control in complex metro stations. The results show that atrium fires are more significantly impacted by outdoor temperature variations compared to concourse/platform fires. The gathered high-temperature smoke inside the atrium can reach up to 900 K under a 5 MW train fire energy release. The findings provide crucial engineering insights into integrating weather data and adaptable ventilation protocols for smoke prevention/mitigation.
Article
Thermodynamics
Da Guo, Heping Xie, Mingzhong Gao, Jianan Li, Zhiqiang He, Ling Chen, Cong Li, Le Zhao, Dingming Wang, Yiwei Zhang, Xin Fang, Guikang Liu, Zhongya Zhou, Lin Dai
Summary: This study proposes a new in-situ pressure-preserved coring tool and elaborates its pressure-preserving mechanism. The experimental and field test results demonstrate that this tool has a high pressure-preservation capability and can maintain a stable pressure in deep wells. This study provides a theoretical framework and design standards for the development of similar technologies.
Article
Thermodynamics
Aolin Lai, Qunwei Wang
Summary: This study assesses the impact of China's de-capacity policy on renewable energy development efficiency (REDE) using the Global-MSBM model and the difference-in-differences method. The findings indicate that the policy significantly enhances REDE, promoting technological advancements and marketization. Moreover, regions with stricter environmental regulations experience a higher impact.
Article
Thermodynamics
Mostafa Ghasemi, Hegazy Rezk
Summary: This study utilizes fuzzy modeling and optimization to enhance the performance of microbial fuel cells (MFCs). By simulating and analyzing experimental data sets, the ideal parameter values for increasing power density, COD elimination, and coulombic efficiency were determined. The results demonstrate that the fuzzy model and optimization methods can significantly improve the performance of MFCs.
Article
Thermodynamics
Zhang Ruan, Lianzhong Huang, Kai Wang, Ranqi Ma, Zhongyi Wang, Rui Zhang, Haoyang Zhao, Cong Wang
Summary: This paper proposes a grey box model for fuel consumption prediction of wing-diesel hybrid vessels based on feature construction. By using both parallel and series grey box modeling methods and six machine learning algorithms, twelve combinations of prediction models are established. A feature construction method based on the aerodynamic performance of the wing and the energy relationship of the hybrid system is introduced. The best combination is obtained by considering the root mean square error, and it shows improved accuracy compared to the white box model. The proposed grey box model can accurately predict the daily fuel consumption of wing-diesel hybrid vessels, contributing to operational optimization and the greenization and decarbonization of the shipping industry.
Article
Thermodynamics
Huayi Chang, Nico Heerink, Junbiao Zhang, Ke He
Summary: This study examines the interaction between off-farm employment decisions between couples and household clean energy consumption in rural China, and finds that two-paycheck households are more likely to consume clean energy. The off-farm employment of women is a key factor driving household clean energy consumption to a higher level, with wage-employed wives having a stronger influence on these decisions than self-employed ones.
Article
Thermodynamics
Hanguan Wen, Xiufeng Liu, Ming Yang, Bo Lei, Xu Cheng, Zhe Chen
Summary: Demand-side management is crucial to smart energy systems. This paper proposes a data-driven approach to understand the relationship between energy consumption patterns and household characteristics for better DSM services. The proposed method uses a clustering algorithm to generate optimal customer groups for DSM and a deep learning model for training. The model can predict the possibility of DSM membership for a given household. The results demonstrate the usefulness of weekly energy consumption data and household socio-demographic information for distinguishing consumer groups and the potential for targeted DSM strategies.
Article
Thermodynamics
Xinglan Hou, Xiuping Zhong, Shuaishuai Nie, Yafei Wang, Guigang Tu, Yingrui Ma, Kunyan Liu, Chen Chen
Summary: This study explores the feasibility of utilizing a multi-level horizontal branch well heat recovery system in the Qiabuqia geothermal field. The research systematically investigates the effects of various engineering parameters on production temperature, establishes mathematical models to describe their relationships, and evaluates the economic viability of the system. The findings demonstrate the significant economic feasibility of the multi-level branch well system.
Article
Thermodynamics
Longxin Zhang, Songtao Wang, Site Hu
Summary: This investigation reveals the influence of tip leakage flow on the modern transonic rotor and finds that the increase of tip clearance size leads to a decline in rotor performance. However, an optimal tip clearance size can extend the rotor's stall margin.
Article
Thermodynamics
Kristian Gjoka, Behzad Rismanchi, Robert H. Crawford
Summary: This paper proposes a framework for assessing the performance of 5GDHC systems and demonstrates it through a case study in a university campus in Melbourne, Australia. The results show that 5GDHC systems are a cost-effective and environmentally viable solution in mild climates, and their successful implementation in Australia can create new market opportunities and potential adoption in other countries with similar climatic conditions.
Article
Thermodynamics
Jianwei Li, Guotai Wang, Panpan Yang, Yongshuang Wen, Leian Zhang, Rujun Song, Chengwei Hou
Summary: This study proposes an orientation-adaptive electromagnetic energy harvester by introducing a rotatable bluff body, which allows for self-regulation to cater for changing wind flow direction. Experimental results show that the output power of the energy harvester can be greatly enhanced with increased rotatory inertia of the rotating bluff body, providing a promising solution for harnessing wind-induced vibration energy.
