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Article
Engineering, Electrical & Electronic
Olatunji Ahmed Lawal et al.
Summary: Optimal transmission line rating use is guaranteed with dynamic line rating (DLR), which is a smart grid technology that adjusts line rating based on predicted variations in meteorological conditions. This study compared different DLR forecasting techniques, including ensemble means forecasting, recurrent neural network (RNN), and convolution neural network (CNN), and found that ensemble forecasting is the most reliable and secure method.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Energy & Fuels
Ching-Ming Lai et al.
Summary: This study combines network topology optimization, dynamic thermal rating system, and battery storage system to evaluate their synergistic effects on wind integration and network reliability. The results show that the proposed combination of methods reduces system dispatch, load curtailment, and wind curtailment costs the most when compared to any combinations with fewer methods or using each method in isolation.
Article
Energy & Fuels
Matija Kostelac et al.
Summary: The latest European energy regulations highlight the active participation of household-level end users, but large industrial facilities are not fully exploiting market opportunities to decrease costs. Offering flexibility services can lead to significant cost reduction. Research identifies the potential of industrial consumers as multi-energy hubs.
Article
Computer Science, Information Systems
Bilkisu Jimada-Ojuolape et al.
Summary: The integration of smart infrastructures and the use of information and communication technology have improved the efficiency and sustainability of the power network. However, certain technologies have disadvantages such as infrastructure failures, interdependencies, and cyber intrusions, which contribute to reduced network reliability. This study investigates the impact of ICT contingencies on network reliability by combining dynamic thermal rating and system integrity protection schemes, using phasor measurement units. The evaluation is conducted using a Monte Carlo simulation approach on the IEEE-RTS, demonstrating the advantages of ICTs.
IEEE SYSTEMS JOURNAL
(2022)
Article
Green & Sustainable Science & Technology
Ling Zhou et al.
Summary: This paper presents a multi-objective approach to operating FCVs in a hybrid power-gas-hydrogen system to reduce operating costs and pollution emissions. By coupling power-to-gas (P2G) technology with FCVs, excess electrical energy can be converted into hydrogen and natural gas efficiently, contributing to carbon capture as well. The results show a reduction of 8.04% and 9.8% in cost and emission pollution, respectively, under the comprehensive operation approach of FCV and P2G technology.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Thermodynamics
S. A. Mansouri et al.
Summary: This paper presents a new framework for scheduling microgrids and distribution feeder reconfiguration, considering uncertainties from load demand, market price, and renewable power generation. The framework consists of a two-stage model, where the self-scheduling of microgrids is optimized in the first stage and the optimal configuration of the system is determined by the distribution system operator in the second stage. The results show that the deviation from optimal microgrid scheduling is significantly reduced when the system is reconfigured by the operator.
Review
Green & Sustainable Science & Technology
Tobi Michael Alabi et al.
Summary: This study provides a comprehensive review of the integrated optimization and machine learning techniques in the integrated energy system (IES). It highlights the main issues and trends, and emphasizes the need for further research exploration in this area.
Article
Construction & Building Technology
Yi-Peng Xu et al.
Summary: To achieve zero net emissions, multi-energy microgrids (MEMs) have experienced rapid growth. This paper proposes a hybrid robust-stochastic methodology to optimize the scheduling of energy sources in a MEM, aiming to minimize operation costs and emissions. The uncertain characteristics of the electricity market, energy demands, and renewable power production are controlled using a robust approach. Simulation results demonstrate that the proposed energy management strategy can effectively reduce operation costs and emissions.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Energy & Fuels
Seyed Amir Mansouri et al.
Summary: This study develops a multi-objective model for the design of energy hubs, considering the variable efficiency of converters, equipment degradation, and annual growth of load and energy prices. Simulation results show that the dynamic framework accurately determines equipment capacity and that power-to-gas technology reduces CO2 emissions and improves gas-fired converter efficiency.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Reza Hemmati et al.
Summary: This paper proposes a unified management framework for zero-energy buildings, integrating renewable resources, energy storage, AC/DC loads, and critical/non-critical loads. The framework controls various operations, including solar-cell and fuel-cell operation, battery charging-discharging, load energy and voltage regulation. It also has fault detection units for AC and DC buses, outage detection units, and cyber-attack detection units. The proposed method effectively achieves the objectives of supplying DC/AC loads, managing battery and resources, and identifying/dealing with outages, faults, and attacks.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Marcos Tostado-Veliz et al.
Summary: This paper presents a novel optimal scheduling model for robust scheduling of isolated microgrids, incorporating a green hydrogen-based storage system and various demand-response programs. The model incorporates logical rules, interval-based formulation, and iterative solution procedure to simulate the production of green hydrogen and the uncertainties in weather and demand parameters.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Arsalan Najafi et al.
Summary: This paper proposes a linear max-min-max robust optimization-based decision-making tool to address the uncertainties of electricity market prices and wind generation. The system's robustness is increased through the use of an electrical storage system and an uncertainty budget model. Additionally, the integration of a power to gas (P2G) storage system creates a link between the electrical and natural gas networks, resulting in cost savings.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
R. Ramadan et al.
Summary: This paper presents an IoT-based criterion using non-intrusive load monitoring (NILM) to transform modern buildings and homes into energy-efficient and smart ones. The Factorial Hidden Markov Model (FHMM) is used to disaggregate total power consumption into individual appliance load consumption, and real-time visualization and alerts are used to control energy consumption.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Thermodynamics
Xu Zhu et al.
Summary: This paper proposes an integrated energy pricing and management strategy and establishes multi-energy demand response models. Through simulation analysis, the feasibility of the proposed model is verified, and it is found that the application of multi-energy demand responses can improve the economic benefits of the energy system and reduce carbon emissions.
Article
Thermodynamics
Honghui Zhang et al.
Summary: This paper focuses on the concept of a hydrogen-based micro energy hub, considering integrated demand response and hydrogen storage system. By integrating different energy sources and introducing demand response and hydrogen storage, system performance and reliability can be improved. The proposed model uses a harmony search optimization algorithm to minimize the energy cost of the whole system, considering the uncertainty of the power price. Simulation and numerical results confirm the effectiveness of the model.
Article
Automation & Control Systems
Hasan Mehrjerdi et al.
Summary: This article addresses the operation of a microgrid based on a multicarrier energy hub, optimizing and utilizing various resources to reduce environmental pollution and operating costs while improving the resilience and flexibility of the energy hub.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Green & Sustainable Science & Technology
Mohammad Amin Mirzaei et al.
Summary: This study presents a unique risk-based hybrid two-stage operational model for an integrated energy distribution system that optimally engages in various energy markets. The model applies different risk-averse methods to lower the risk level based on uncertainties and data availability. It utilizes CVaR-SP technique to handle uncertainties in wind speed, vehicle behavior, energy prices, and demands. The model also employs IGDT to control real-time energy prices without the need for a probability distribution function or scenarios. The integrated energy distribution system is equipped with various local energy resources to provide flexibility and reduce operating costs.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Computer Science, Artificial Intelligence
Danial Bahmanyar et al.
Summary: This paper introduces a home energy management system based on IoT technology, which manages energy consumption by optimizing appliance scheduling and achieves demand side management. A multi-objective arithmetic optimization algorithm is used to find the optimal scheduling pattern, and the integration with renewable energy sources improves user comfort.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Siva Sankari Subbiah et al.
Summary: This paper proposes a deep learning-based Long Short Term Memory (LSTM) model with hybrid feature selection to improve the accuracy of short term load forecasting. Experimental results show that the proposed model outperforms other models.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Seyed Amir Mansouri et al.
Summary: This paper proposes a hierarchical model to enhance the resilience of decentralized microgrids by managing network outages and reducing energy not served. Different measures are taken at different stages to respond to different operating conditions. The simulation results show that these measures can significantly decrease the energy not served, and improve the supply service level and resilience index.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Review
Energy & Fuels
Ching-Ming Lai et al.
Summary: The dynamic thermal rating (DTR) system safely determines the thermal limits of power components based on environmental conditions. However, existing reviews of the DTR system only focus on transmission lines and networks, neglecting the thermal limits of transformers and distribution cables, and have limited research themes. This review article addresses these drawbacks by collecting and categorizing existing research articles, providing a comprehensive summary for prospective researchers of the DTR system.
Proceedings Paper
Green & Sustainable Science & Technology
Seyed Amir Mansouri et al.
Summary: This paper presents a bi-level bidding system for managing energy exchange between interconnected microgrids in the presence of traditional and smart consumers, in which the conditional value at risk (CVaR) method is employed to manage the risk arising from uncertainties of load demand and renewable generations (RGs). The simulation results demonstrate that risk-taker scheduling not only reduces the market-clearing price but also increases the comfort index of smart consumers. Also, the results illustrate that modifying the consumption pattern of regular consumers through the DRP leads to more available power during peak hours and increases the comfort index of smart consumers.
2022 IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2022 IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC / I&CPS EUROPE)
(2022)
Article
Energy & Fuels
Antonio Coelho et al.
Summary: A network-secure bidding optimization strategy is proposed in this paper to assist aggregators of multi-energy systems in calculating bids while considering network constraints. Results show that joint optimization of multi-energy systems can significantly reduce aggregator's costs. Sensibility studies also reveal the impact of certain conditions on aggregator's costs.
Article
Energy & Fuels
Chenjia Gu et al.
Summary: The paper proposes a joint planning approach for electrical and gas energy storage, taking into account the interdependency between power-gas distribution network and transportation network. By using semi-dynamic traffic assignment method and novel second-order cone formulation, the planning model is formulated as a mixed-integer second-order conic programming problem, ensuring exactness of all second-order cone relaxations and achieving peak charging load fulfillment with low investment cost.
Article
Thermodynamics
Shiyuan Bao et al.
Summary: This paper introduces a general pricing method for multi-energy systems, decomposes the components of multi-energy prices, and examines the temporal correlation of prices. The correlated relationship among prices of different energy forms is theoretically studied by analyzing the coupling mechanisms of different facilities.
Review
Green & Sustainable Science & Technology
Christian Klemm et al.
Summary: Around 75% of global energy consumption occurs in cities, but there is a lack of research on modeling energy systems in urban areas. This review evaluates existing energy system models and tools, revealing a scarcity of suitable tools for optimizing multienergy systems in mixed-use districts.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Engineering, Electrical & Electronic
Ali Esmaeel Nezhad et al.
Summary: This paper introduces a new model for self-scheduling problem using HEMS, aiming to minimize daily electricity bills through mixed-integer linear programming for optimizing home appliances. By integrating PV and EES systems to handle uncertain solar power generation, it effectively reduces energy consumption of AC and other appliances during peak hours, resulting in lower bills.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
H. J. Kim et al.
Summary: This study evaluates a risk-based hybrid energy management problem by creating a staircase bidding profile for microgrid operators under a confidence-based incentive demand response program, achieving operation cost reduction and reliability enhancement through demand response. It applies stochastic/information gap decision theory-based optimization technique to model photovoltaic, wind turbine, and local loads, considering price uncertainty and demonstrating superior solution quality with reduced computational burden.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Bin Zhou et al.
Summary: This paper proposes a multi-energy forecasting framework based on deep learning methodology to predict the electrical, thermal and gas net load of integrated local energy systems. By qualitatively analyzing, clustering, and predicting heterogeneous prosumers, accurate forecasts for multiple energy producers are achieved.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Wang Xuan et al.
Summary: This paper proposes a novel multi-energy load prediction model based on deep multi-task learning and ensemble approach for regional integrated energy systems (RIES). The model can dig deeper into the coupling relations among various energy systems and explore the temporal and spatial correlation of multi energy loads further, achieving higher prediction accuracy and better prediction applicability than other current advanced models.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Chemistry, Physical
Amir Saman Godazi Langeroudi et al.
Summary: This paper investigates the optimal scheduling of a multi-energy system, including renewable energy sources and plug-in electric vehicles, to improve energy efficiency and mitigate fluctuations, while also developing hydrogen-based technologies. The results show that integrating hydrogen storage and plug-in electric vehicles can significantly reduce daily costs.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2021)
Article
Construction & Building Technology
Reza Hemmati et al.
Summary: This paper presents a flexible model for microgrid formation in the integrated electricity-gas system by optimal sizing, siting and operation of combined heat and power (CHPs) to improve system operation/resilience and reduce operational/energy cost. Results show that end-buses of the grid are the best locations for CHPs to achieve the defined objectives, reducing overall cost by 11.6% and supplying all critical loads under single and multiple events.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Construction & Building Technology
Seyed Amir Mansouri et al.
Summary: This paper presents a tri-objective optimization framework for energy management of microgrids in the presence of smart homes and demand response program. The model is implemented on an 83-bus distribution system with uncertainties of renewable energy resources output power and load demand taken into account. Results show that considering smart homes in the network reduces the operation cost and emission by about 16% and 17% respectively, with the best results obtained from the tri-objective model.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Computer Science, Information Systems
Elham Mokaramian et al.
Summary: The paper proposes a new energy hub framework considering both economic and pollution emission objectives, optimizing operation with various energy sources and hybrid energy storage facilities. Uncertainties are modeled using the Mont-Carlo method and risk level is analyzed using CVaR approach, while the MINLP method in GAMS is utilized to minimize operation cost and pollution emission. The effectiveness of a new E-fuel energy storage system and uncertainties on energy hub operation is proven through comparison with other reported models.
Article
Energy & Fuels
Jie Mei et al.
Summary: This paper proposes an economic two-stage stochastic optimization method for optimal scheduling of a real multi-energy system, including hydrogen-based vehicle applications. Simulation results indicate that the proposed scheduling method can help quantify daily operating costs and achieve significant cost savings by appropriately arranging and utilizing devices in the system.
ADVANCES IN APPLIED ENERGY
(2021)
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Xue Li et al.
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Thermodynamics
Seyed Amir Mansouri et al.
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Bilkisu Jimada-Ojuolape et al.
SUSTAINABLE CITIES AND SOCIETY
(2020)
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Energy & Fuels
Xiong Wu et al.
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Energy & Fuels
Jiashen Teh et al.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2019)
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Computer Science, Information Systems
Basheer Qolomany et al.
Article
Engineering, Electrical & Electronic
Shanshan Ma et al.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2018)
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Energy & Fuels
Xiaojin Zhang et al.
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Energy & Fuels
Nicholas Good et al.
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Dong Zhang et al.
ELECTRIC POWER SYSTEMS RESEARCH
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