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Hongjie Jia - One of the best experts on this subject based on the ideXlab platform.

  • A double-layer planning method for integrated Community Energy Systems with varying Energy conversion efficiencies
    Applied Energy, 2020
    Co-Authors: Wanqing Chen, Kai Hou, Hongjie Jia, Congshan Wang, Xianjun Meng
    Abstract:

    Abstract The Energy hub is considered a unit where multiple Energy carriers can be converted, conditioned, and stored, thereby providing the functions of input, output, conversion, and storage of multiple Energy carriers using a defined coupling matrix. Thus, the Energy hub is widely used in the planning and operation of integrated Energy Systems. However, the coupling factors (or the efficiencies of the Energy conversion devices) in the Energy hub coupling matrix are usually assumed to be constant for the sake of simplicity, which may result in unreasonable planning and operation schemes for the integrated Energy System. For this reason, an integrated Energy System planning method at the Community level that considers varying coupling factors was developed in this study. First, a dynamic Energy hub model was developed, where an efficiency correction model was built to determine the time-varying coupling factors with the variation in load rate. On this basis, a double-layer planning model was built to determine the optimal planning and operation schemes for the integrated Community Energy System. A typical integrated Community Energy System was employed as a test System to illustrate the effectiveness of the planning method, and the results were analysed.

  • Reliability modeling for Integrated Community Energy System considering dynamic process of thermal loads
    IET Energy Systems Integration, 2019
    Co-Authors: Kai Hou, Yue Wang, Yunkai Lei, Hongjie Jia, Lewei Zhu, Xiaonan Liu
    Abstract:

    The Integrated Community Energy System (ICES) has developed rapidly, but the reliability assessment models of ICES are somehow out of date. A new reliability assessment model for ICES is proposed incorporating electricity, gas and heat, considering dynamic process of thermal loads. First, the static model of ICES consisting of three subSystems is constructed based on the Energy hub model. Then the inertial features of loads are incorporated in the reliability of ICES. Thereafter, a quasi-sequential simulation based on a decomposed optimisation method is proposed to assess the reliability of ICES. Case studies are conducted on an ICES with four Energy hubs to validate the performance of the presented model. Results show that the proposed reliability assessment model is more practical and the identified weak points of each subSystem have changed after utilising the new model.

  • A Reliability Assessment Approach for Integrated Community Energy System Based on Hierarchical Decoupling Optimization Framework
    2018 IEEE Power & Energy Society General Meeting (PESGM), 2018
    Co-Authors: Kai Hou, Yue Wang, Xiaonan Liu, Yunkai Lei, Hongjie Jia, Lewei Zhu
    Abstract:

    This paper presents a reliability assessment approach for Integrated Community Energy System (ICES). The complex Energy couplings and interactions in the ICES is simulated by the Energy hub model, which connects electricity, gas and heat Systems. The quasi-sequential Monte Carlo simulation technique is utilized to select the System state of ICES. A hierarchical decoupling optimization framework is then implemented to calculate the Energy loss after outage occurs. Case studies show that the proposed method can accurately evaluate the reliability of ICES.

  • A two-stage multi-objective scheduling method for integrated Community Energy System
    Applied Energy, 2018
    Co-Authors: Wei Lin, Xiaolong Jin, Hongjie Jia, Bo Zhao
    Abstract:

    In order to determine the optimal day-ahead scheduling schemes of the integrated Community Energy System (ICES), a two-stage multi-objective scheduling method (TMSM) was proposed, which consists of a multi-objective optimal power flow (MOPF) calculation stage and a multiple attributes decision making (MADM) stage. Firstly, the electric distribution network, the natural gas network and the Energy centers (ECs) of the ICES were modelled. Secondly, five typical indices are considered to characterize the operation of ICES, namely the operation cost (OC) and total emission (TE) of ICES, the power loss (PL) and sum of voltage deviation (SVD) of electric distribution network, the sum of pressure deviation (SPD) of natural gas network. In order to tackle the computation problems resulted by the increasing number of objectives, the dimension reduction of objectives is employed. The indices of OC and TE are selected based on the analytic hierarchy process (AHP) method and set as the objectives at the MOPF calculation stage. Thirdly, all the five indices are considered during the MADM stage to determine the final day-ahead scheduling schemes from the alternative solutions obtained in MOPF. Numerical studies demonstrate that the TMSM is able to provide flexibility for the operation of ICES. The determined optimum day-ahead scheduling schemes are capable of satisfying and balancing operational needs in aspects of security, economy and environmental friendliness.

  • multi objective optimal hybrid power flow algorithm for integrated Community Energy System
    Energy Procedia, 2017
    Co-Authors: Wei Lin, Xiaolong Jin, Hongjie Jia
    Abstract:

    A multi-objective optimal hybrid power flow algorithm was proposed for multi-objective scheduling and management of the integrated local area Energy System (ILAES). Firstly, an Energy flow analysis model for the Energy center was developed based on the Energy hub model. Then, a multi-objective optimal hybrid power flow algorithm was proposed to minimize the operation cost and total emission of the ILAES considering the constraints from unbalanced three-phase electric distribution network, the natural gas network and the Energy centers. The proposed multi-objective optimal hybrid power flow algorithm can be further used in the optimal day-ahead scheduling for the ILAES, which considers the ILAES’s multiple operation needs in aspects of security, economy and environmental friendliness. Numerical results show that the proposed algorithm can be used in the steady-state analysis of the ILAES and multi-objective optimal scheduling for the ILAES.

Xiaolong Jin - One of the best experts on this subject based on the ideXlab platform.

  • Stochastic Multi-Objective Scheduling Approach for Integrated Community Energy System
    2018 IEEE International Conference on Energy Internet (ICEI), 2018
    Co-Authors: Wei Lin, Xiaolong Jin, Qian Zhou, Bingcheng Cen
    Abstract:

    In order to achieve economic and environmental benefits of Energy management at Community level, a stochastic multi-objective scheduling approach (SMSA) for integrated Community Energy System (ICES) considering the uncertainties from renewable Energy resources (RES) and electric/heating loads is proposed in this paper. The ICES is composed of three Energy networks, namely the electric distribution network, the natural gas network and the Energy centers (ECs). Mathematical model of the ICES is established firstly. Then, a multi-objective scheduling method considering the operational constraints of the electric distribution network, the natural gas network and ECs is developed. The chance-constrained programming (CCP) method is used to develop the probabilistic constraints which incorporate the uncertainties of the RES and electric/heating loads into the SMSA to a certain confidence level. Numerical studies demonstrate that the proposed SMSA can provide robust scheduling schemes for ICES in aspect of economy, environmental friendliness and security with the uncertainties from the forecasting data being considered.

  • A two-stage multi-objective scheduling method for integrated Community Energy System
    Applied Energy, 2018
    Co-Authors: Wei Lin, Xiaolong Jin, Hongjie Jia, Bo Zhao
    Abstract:

    In order to determine the optimal day-ahead scheduling schemes of the integrated Community Energy System (ICES), a two-stage multi-objective scheduling method (TMSM) was proposed, which consists of a multi-objective optimal power flow (MOPF) calculation stage and a multiple attributes decision making (MADM) stage. Firstly, the electric distribution network, the natural gas network and the Energy centers (ECs) of the ICES were modelled. Secondly, five typical indices are considered to characterize the operation of ICES, namely the operation cost (OC) and total emission (TE) of ICES, the power loss (PL) and sum of voltage deviation (SVD) of electric distribution network, the sum of pressure deviation (SPD) of natural gas network. In order to tackle the computation problems resulted by the increasing number of objectives, the dimension reduction of objectives is employed. The indices of OC and TE are selected based on the analytic hierarchy process (AHP) method and set as the objectives at the MOPF calculation stage. Thirdly, all the five indices are considered during the MADM stage to determine the final day-ahead scheduling schemes from the alternative solutions obtained in MOPF. Numerical studies demonstrate that the TMSM is able to provide flexibility for the operation of ICES. The determined optimum day-ahead scheduling schemes are capable of satisfying and balancing operational needs in aspects of security, economy and environmental friendliness.

  • multi objective optimal hybrid power flow algorithm for integrated Community Energy System
    Energy Procedia, 2017
    Co-Authors: Wei Lin, Xiaolong Jin, Hongjie Jia
    Abstract:

    A multi-objective optimal hybrid power flow algorithm was proposed for multi-objective scheduling and management of the integrated local area Energy System (ILAES). Firstly, an Energy flow analysis model for the Energy center was developed based on the Energy hub model. Then, a multi-objective optimal hybrid power flow algorithm was proposed to minimize the operation cost and total emission of the ILAES considering the constraints from unbalanced three-phase electric distribution network, the natural gas network and the Energy centers. The proposed multi-objective optimal hybrid power flow algorithm can be further used in the optimal day-ahead scheduling for the ILAES, which considers the ILAES’s multiple operation needs in aspects of security, economy and environmental friendliness. Numerical results show that the proposed algorithm can be used in the steady-state analysis of the ILAES and multi-objective optimal scheduling for the ILAES.

  • Hierarchical management for integrated Community Energy Systems
    Applied Energy, 2015
    Co-Authors: Xiaolong Jin, Hongjie Jia
    Abstract:

    Due to the presence of combined heat and power plants (CHP) and thermostatically control loads, heat, natural gas, and electric power Systems are tightly coupled in Community areas. However, the coordination among these Systems has not yet been fully researched, especially with the integration of renewable Energy. This paper aims to develop a hierarchical approach for an integrated Community Energy System (ICES). The proposed hierarchical framework is presented as day-ahead scheduling and two-layer intra-hour adjustment Systems. Two objectives, namely the operating cost minimization and tie-line power smoothing, are integrated into the framework. In the intra-hour adjustment, a master–client structure is designed. The CHP and thermostatically controlled loads are coordinated by a method with two different time scales in order to execute the schedule and handle uncertainties from the load demand and the renewable generation. To obtain the optimal set-points for the CHP, an integrated optimal power flow method is developed, which also incorporates three-phase electric power flow and natural gas flow constraints. Furthermore, based on a time priority list method, a three-phase demand response approach is proposed to dispatch thermostatically controlled loads at different phases and locations. Numerical studies confirm that the ICES can be economically operated, and the tie-line power between the ICES and external Energy network can be effectively smoothed.

Mo Chung - One of the best experts on this subject based on the ideXlab platform.

  • Estimation of the building Energy loads and LNG demand for a cogeneration-based Community Energy System: A case study in Korea
    Energy Conversion and Management, 2014
    Co-Authors: Mo Chung, Hwa-choon Park, Carlos F.m. Coimbra
    Abstract:

    Abstract We analyzed Energy consumption by a newly constructed part of a city in Korea to forecast the LNG demand for 14 years. The electricity, heating, cooling, and hot-water demands for a cogeneration-based CES (Community Energy System) accommodating 86,000 people in 29,000 houses are estimated using load models developed through direct measurements and statistical surveys. Based on published occupancy rates and forecasts of the rate of increase in Energy consumption by third parties through independent study, the Energy demands were driven in the form of 8760-h time series for each of the 14 years. Next, we simulate the demand–supply matching processes of a specifically chosen cogeneration engine for the CES to forecast the LNG consumption and the electricity trade for each year. We simulated the demand–supply matching processes with an automation tool specifically developed for this study. The methodology we established in this study can be applied to similar problems which may arise anywhere in the world.

  • a decision support assessment of cogeneration plant for a Community Energy System in korea
    Energy Policy, 2012
    Co-Authors: Mo Chung, Hwa-choon Park, Chuhwan Park, Sukgyu Lee, Youngho Chang
    Abstract:

    We have undertaken a case study of a Combined Heat and Power (CHP) plant applied to a mixture of buildings comprising residential premises, offices, hospitals, stores, and schools in Korea. We proposed five Plans for grouping buildings in the complex and estimated the annual 8760-hourly demands for electricity, cooling, heating, and hot water. For each Plan, we built about ten Scenarios for System construction. Then, we simulated the operation of the System to find the fuel consumption, electricity purchase, and heat recovery. Applying the local rates to the amounts of fuel and electricity, we estimated the operating costs. Combining the operating cost with the initial cost associated with the purchase and construction of the System, we calculated the payback periods for the scenarios. We found that the payback period can be as short as two years for smartly grouped buildings with a generator capacity of around 50% of the peak electricity demand. A progressive electricity rate that applies only to residential premises currently plays a key role in the economic merits. We recommend extending a sound progressive System to other types of building in Korea to promote distributed power production and enhance Energy saving practices in general.

  • development of a software package for Community Energy System assessment part i building a load estimator
    Energy, 2010
    Co-Authors: Mo Chung, Hwa-choon Park
    Abstract:

    As part of an assessment software package for Community Energy Systems, a database application is developed to Systematically calculate the Energy demands for mixes of 12 different types of building in Korea. The program generates the hourly demands for electricity, heating, cooling, and hot water for the mix of building types for 8760h of a year. The calculation is based on field and measured data from major cities throughout the country. The Energy demand curves generated by the package can be applied to the basic design processes of CESs (Community Energy Systems).

  • Development of a software package for Community Energy System assessment – Part I: Building a load estimator
    Energy, 2010
    Co-Authors: Mo Chung, Hwa-choon Park
    Abstract:

    As part of an assessment software package for Community Energy Systems, a database application is developed to Systematically calculate the Energy demands for mixes of 12 different types of building in Korea. The program generates the hourly demands for electricity, heating, cooling, and hot water for the mix of building types for 8760h of a year. The calculation is based on field and measured data from major cities throughout the country. The Energy demand curves generated by the package can be applied to the basic design processes of CESs (Community Energy Systems).

Hwa-choon Park - One of the best experts on this subject based on the ideXlab platform.

  • Estimation of the building Energy loads and LNG demand for a cogeneration-based Community Energy System: A case study in Korea
    Energy Conversion and Management, 2014
    Co-Authors: Mo Chung, Hwa-choon Park, Carlos F.m. Coimbra
    Abstract:

    Abstract We analyzed Energy consumption by a newly constructed part of a city in Korea to forecast the LNG demand for 14 years. The electricity, heating, cooling, and hot-water demands for a cogeneration-based CES (Community Energy System) accommodating 86,000 people in 29,000 houses are estimated using load models developed through direct measurements and statistical surveys. Based on published occupancy rates and forecasts of the rate of increase in Energy consumption by third parties through independent study, the Energy demands were driven in the form of 8760-h time series for each of the 14 years. Next, we simulate the demand–supply matching processes of a specifically chosen cogeneration engine for the CES to forecast the LNG consumption and the electricity trade for each year. We simulated the demand–supply matching processes with an automation tool specifically developed for this study. The methodology we established in this study can be applied to similar problems which may arise anywhere in the world.

  • a decision support assessment of cogeneration plant for a Community Energy System in korea
    Energy Policy, 2012
    Co-Authors: Mo Chung, Hwa-choon Park, Chuhwan Park, Sukgyu Lee, Youngho Chang
    Abstract:

    We have undertaken a case study of a Combined Heat and Power (CHP) plant applied to a mixture of buildings comprising residential premises, offices, hospitals, stores, and schools in Korea. We proposed five Plans for grouping buildings in the complex and estimated the annual 8760-hourly demands for electricity, cooling, heating, and hot water. For each Plan, we built about ten Scenarios for System construction. Then, we simulated the operation of the System to find the fuel consumption, electricity purchase, and heat recovery. Applying the local rates to the amounts of fuel and electricity, we estimated the operating costs. Combining the operating cost with the initial cost associated with the purchase and construction of the System, we calculated the payback periods for the scenarios. We found that the payback period can be as short as two years for smartly grouped buildings with a generator capacity of around 50% of the peak electricity demand. A progressive electricity rate that applies only to residential premises currently plays a key role in the economic merits. We recommend extending a sound progressive System to other types of building in Korea to promote distributed power production and enhance Energy saving practices in general.

  • development of a software package for Community Energy System assessment part i building a load estimator
    Energy, 2010
    Co-Authors: Mo Chung, Hwa-choon Park
    Abstract:

    As part of an assessment software package for Community Energy Systems, a database application is developed to Systematically calculate the Energy demands for mixes of 12 different types of building in Korea. The program generates the hourly demands for electricity, heating, cooling, and hot water for the mix of building types for 8760h of a year. The calculation is based on field and measured data from major cities throughout the country. The Energy demand curves generated by the package can be applied to the basic design processes of CESs (Community Energy Systems).

  • Development of a software package for Community Energy System assessment – Part I: Building a load estimator
    Energy, 2010
    Co-Authors: Mo Chung, Hwa-choon Park
    Abstract:

    As part of an assessment software package for Community Energy Systems, a database application is developed to Systematically calculate the Energy demands for mixes of 12 different types of building in Korea. The program generates the hourly demands for electricity, heating, cooling, and hot water for the mix of building types for 8760h of a year. The calculation is based on field and measured data from major cities throughout the country. The Energy demand curves generated by the package can be applied to the basic design processes of CESs (Community Energy Systems).

Wei Lin - One of the best experts on this subject based on the ideXlab platform.

  • Stochastic Multi-Objective Scheduling Approach for Integrated Community Energy System
    2018 IEEE International Conference on Energy Internet (ICEI), 2018
    Co-Authors: Wei Lin, Xiaolong Jin, Qian Zhou, Bingcheng Cen
    Abstract:

    In order to achieve economic and environmental benefits of Energy management at Community level, a stochastic multi-objective scheduling approach (SMSA) for integrated Community Energy System (ICES) considering the uncertainties from renewable Energy resources (RES) and electric/heating loads is proposed in this paper. The ICES is composed of three Energy networks, namely the electric distribution network, the natural gas network and the Energy centers (ECs). Mathematical model of the ICES is established firstly. Then, a multi-objective scheduling method considering the operational constraints of the electric distribution network, the natural gas network and ECs is developed. The chance-constrained programming (CCP) method is used to develop the probabilistic constraints which incorporate the uncertainties of the RES and electric/heating loads into the SMSA to a certain confidence level. Numerical studies demonstrate that the proposed SMSA can provide robust scheduling schemes for ICES in aspect of economy, environmental friendliness and security with the uncertainties from the forecasting data being considered.

  • A two-stage multi-objective scheduling method for integrated Community Energy System
    Applied Energy, 2018
    Co-Authors: Wei Lin, Xiaolong Jin, Hongjie Jia, Bo Zhao
    Abstract:

    In order to determine the optimal day-ahead scheduling schemes of the integrated Community Energy System (ICES), a two-stage multi-objective scheduling method (TMSM) was proposed, which consists of a multi-objective optimal power flow (MOPF) calculation stage and a multiple attributes decision making (MADM) stage. Firstly, the electric distribution network, the natural gas network and the Energy centers (ECs) of the ICES were modelled. Secondly, five typical indices are considered to characterize the operation of ICES, namely the operation cost (OC) and total emission (TE) of ICES, the power loss (PL) and sum of voltage deviation (SVD) of electric distribution network, the sum of pressure deviation (SPD) of natural gas network. In order to tackle the computation problems resulted by the increasing number of objectives, the dimension reduction of objectives is employed. The indices of OC and TE are selected based on the analytic hierarchy process (AHP) method and set as the objectives at the MOPF calculation stage. Thirdly, all the five indices are considered during the MADM stage to determine the final day-ahead scheduling schemes from the alternative solutions obtained in MOPF. Numerical studies demonstrate that the TMSM is able to provide flexibility for the operation of ICES. The determined optimum day-ahead scheduling schemes are capable of satisfying and balancing operational needs in aspects of security, economy and environmental friendliness.

  • multi objective optimal hybrid power flow algorithm for integrated Community Energy System
    Energy Procedia, 2017
    Co-Authors: Wei Lin, Xiaolong Jin, Hongjie Jia
    Abstract:

    A multi-objective optimal hybrid power flow algorithm was proposed for multi-objective scheduling and management of the integrated local area Energy System (ILAES). Firstly, an Energy flow analysis model for the Energy center was developed based on the Energy hub model. Then, a multi-objective optimal hybrid power flow algorithm was proposed to minimize the operation cost and total emission of the ILAES considering the constraints from unbalanced three-phase electric distribution network, the natural gas network and the Energy centers. The proposed multi-objective optimal hybrid power flow algorithm can be further used in the optimal day-ahead scheduling for the ILAES, which considers the ILAES’s multiple operation needs in aspects of security, economy and environmental friendliness. Numerical results show that the proposed algorithm can be used in the steady-state analysis of the ILAES and multi-objective optimal scheduling for the ILAES.