Distribution networks denote important public infrastructure necessary for people’s livelihoods.However,extreme natural disasters,such as earthquakes,typhoons,and mudslides,severely threaten the safe and stable opera...Distribution networks denote important public infrastructure necessary for people’s livelihoods.However,extreme natural disasters,such as earthquakes,typhoons,and mudslides,severely threaten the safe and stable operation of distribution networks and power supplies needed for daily life.Therefore,considering the requirements for distribution network disaster prevention and mitigation,there is an urgent need for in-depth research on risk assessment methods of distribution networks under extreme natural disaster conditions.This paper accessesmultisource data,presents the data quality improvement methods of distribution networks,and conducts data-driven active fault diagnosis and disaster damage analysis and evaluation using data-driven theory.Furthermore,the paper realizes real-time,accurate access to distribution network disaster information.The proposed approach performs an accurate and rapid assessment of cross-sectional risk through case study.The minimal average annual outage time can be reduced to 3 h/a in the ring network through case study.The approach proposed in this paper can provide technical support to the further improvement of the ability of distribution networks to cope with extreme natural disasters.展开更多
World energy consumption increased by 56 percent, from 524 quadrillion Btu in 2010 to 820 quadrillion Btu in 2040. The increased demand in energy consumption is fulfilled by different renewable and non-renewable sourc...World energy consumption increased by 56 percent, from 524 quadrillion Btu in 2010 to 820 quadrillion Btu in 2040. The increased demand in energy consumption is fulfilled by different renewable and non-renewable sources such as petroleum, natural gas, electricity, nuclear etc. Natural gas is one of the most important sources of energy. SNGPL has been managing a 94,263 km long gas pipelines network covering approximately the northern part of Pakistan. In this paper we have presented the use of condition based maintenance (CBM) management techniques with a?geographical information system (GIS) for asset management of a gas distribution network of?SNGPL. The continuous monitoring and updating of asset data reveal where the assets are located and which needs maintenance or which lies in critical condition. The system helps to save time and reduce visits to the sites and labour reduction.展开更多
Traditional seawater desalination requires high amounts of energy, with correspondingly high costs and limited benefits, hindering wider applications of the process. To further improve the comprehensive economic benef...Traditional seawater desalination requires high amounts of energy, with correspondingly high costs and limited benefits, hindering wider applications of the process. To further improve the comprehensive economic benefits of seawater desalination, the desalination load can be combined with renewable energy sources such as solar energy, wind energy, and ocean energy or with the power grid to ensure its effective regulation. Utilizing energy internet(EI) technology, energy balance demand of the regional power grid, and coordinated control between coastal multi-source multi-load and regional distribution network with desalination load is reviewed herein. Several key technologies, including coordinated control of coastal multi-source multi-load system with seawater desalination load, flexible interaction between seawater desalination and regional distribution network, and combined control of coastal multi-source multi-load storage system with seawater desalination load, are discussed in detail. Adoption of the flexible interaction between seawater desalination and regional distribution networks is beneficial for solving water resource problems, improving the ability to dissipate distributed renewable energy, balancing and increasing grid loads, improving the safety and economy of coastal power grids, and achieving coordinated and comprehensive application of power grids, renewable energy sources, and coastal loads.展开更多
The volatile and intermittent nature of distributed generators(DGs) in active distribution networks(ADNs) increases the uncertainty of operating states. The introduction of distribution phasor measurement units(D-PMUs...The volatile and intermittent nature of distributed generators(DGs) in active distribution networks(ADNs) increases the uncertainty of operating states. The introduction of distribution phasor measurement units(D-PMUs) enhances the monitoring level. The trade-offs of computational performance and robustness of state estimation in monitoring the network states are of great significance for ADNs with D-PMUs and DGs. This paper proposes a second-order cone programming(SOCP) based robust state estimation(RSE) method considering multi-source measurements. Firstly, a linearized state estimation model related to the SOCP state variables is formulated. The phase angle measurements of D-PMUs are converted to equivalent power measurements. Then, a revised SOCP-based RSE method with the weighted least absolute value estimator is proposed to enhance the convergence and bad data identification. Multi-time slots of D-PMU measurements are utilized to improve the estimation accuracy of RSE. Finally, the effectiveness of the proposed method is illustrated in the modified IEEE 33-node and IEEE 123-node systems.展开更多
Harmonic state estimation in distribution networks is essential for identifying harmonic sources.However,issues such as limited measurement redundancy,asynchronous measurements,and unbalanced load distributions in thr...Harmonic state estimation in distribution networks is essential for identifying harmonic sources.However,issues such as limited measurement redundancy,asynchronous measurements,and unbalanced load distributions in three-phase networks undermine the reliability of existing methods in practical applications.To address these issues,this paper proposes an interval harmonic state estimation method in three-phase unbalanced distribution networks,integrating data from multiple sources.First,the interval multi-source harmonic measurement dataset is constructed by integrating asynchronous harmonic measurement data from multiple sources.The time asynchrony of measurement data from power quality monitoring devices is calibrated using the sliding window weighted dynamic time warping algo-rithm.Second,the interval harmonic state estimation model for the three-phase asymmetric distribution network is constructed.The model is solved using the interval-weighted least squares method,enhanced by the improved Krawczyk operator,thereby minimizing the expansion resulting from interval operations.Finally,the feasibility and accuracy of the proposed interval harmonic state estimation method are validated.展开更多
文摘Distribution networks denote important public infrastructure necessary for people’s livelihoods.However,extreme natural disasters,such as earthquakes,typhoons,and mudslides,severely threaten the safe and stable operation of distribution networks and power supplies needed for daily life.Therefore,considering the requirements for distribution network disaster prevention and mitigation,there is an urgent need for in-depth research on risk assessment methods of distribution networks under extreme natural disaster conditions.This paper accessesmultisource data,presents the data quality improvement methods of distribution networks,and conducts data-driven active fault diagnosis and disaster damage analysis and evaluation using data-driven theory.Furthermore,the paper realizes real-time,accurate access to distribution network disaster information.The proposed approach performs an accurate and rapid assessment of cross-sectional risk through case study.The minimal average annual outage time can be reduced to 3 h/a in the ring network through case study.The approach proposed in this paper can provide technical support to the further improvement of the ability of distribution networks to cope with extreme natural disasters.
文摘World energy consumption increased by 56 percent, from 524 quadrillion Btu in 2010 to 820 quadrillion Btu in 2040. The increased demand in energy consumption is fulfilled by different renewable and non-renewable sources such as petroleum, natural gas, electricity, nuclear etc. Natural gas is one of the most important sources of energy. SNGPL has been managing a 94,263 km long gas pipelines network covering approximately the northern part of Pakistan. In this paper we have presented the use of condition based maintenance (CBM) management techniques with a?geographical information system (GIS) for asset management of a gas distribution network of?SNGPL. The continuous monitoring and updating of asset data reveal where the assets are located and which needs maintenance or which lies in critical condition. The system helps to save time and reduce visits to the sites and labour reduction.
基金supported by the State Grid Science and Technology Project, “Study on Multi-source and Multiload Coordination and Optimization Technology Considering Desalination of Sea Water” (No. SGTJDK00DWJS1800011)
文摘Traditional seawater desalination requires high amounts of energy, with correspondingly high costs and limited benefits, hindering wider applications of the process. To further improve the comprehensive economic benefits of seawater desalination, the desalination load can be combined with renewable energy sources such as solar energy, wind energy, and ocean energy or with the power grid to ensure its effective regulation. Utilizing energy internet(EI) technology, energy balance demand of the regional power grid, and coordinated control between coastal multi-source multi-load and regional distribution network with desalination load is reviewed herein. Several key technologies, including coordinated control of coastal multi-source multi-load system with seawater desalination load, flexible interaction between seawater desalination and regional distribution network, and combined control of coastal multi-source multi-load storage system with seawater desalination load, are discussed in detail. Adoption of the flexible interaction between seawater desalination and regional distribution networks is beneficial for solving water resource problems, improving the ability to dissipate distributed renewable energy, balancing and increasing grid loads, improving the safety and economy of coastal power grids, and achieving coordinated and comprehensive application of power grids, renewable energy sources, and coastal loads.
基金supported by the National Key R&D Program of China (No. 2020YFB0906000 and 2020YFB0906001)。
文摘The volatile and intermittent nature of distributed generators(DGs) in active distribution networks(ADNs) increases the uncertainty of operating states. The introduction of distribution phasor measurement units(D-PMUs) enhances the monitoring level. The trade-offs of computational performance and robustness of state estimation in monitoring the network states are of great significance for ADNs with D-PMUs and DGs. This paper proposes a second-order cone programming(SOCP) based robust state estimation(RSE) method considering multi-source measurements. Firstly, a linearized state estimation model related to the SOCP state variables is formulated. The phase angle measurements of D-PMUs are converted to equivalent power measurements. Then, a revised SOCP-based RSE method with the weighted least absolute value estimator is proposed to enhance the convergence and bad data identification. Multi-time slots of D-PMU measurements are utilized to improve the estimation accuracy of RSE. Finally, the effectiveness of the proposed method is illustrated in the modified IEEE 33-node and IEEE 123-node systems.
基金supported by the National Natural Science Foundation of China(No.52377087).
文摘Harmonic state estimation in distribution networks is essential for identifying harmonic sources.However,issues such as limited measurement redundancy,asynchronous measurements,and unbalanced load distributions in three-phase networks undermine the reliability of existing methods in practical applications.To address these issues,this paper proposes an interval harmonic state estimation method in three-phase unbalanced distribution networks,integrating data from multiple sources.First,the interval multi-source harmonic measurement dataset is constructed by integrating asynchronous harmonic measurement data from multiple sources.The time asynchrony of measurement data from power quality monitoring devices is calibrated using the sliding window weighted dynamic time warping algo-rithm.Second,the interval harmonic state estimation model for the three-phase asymmetric distribution network is constructed.The model is solved using the interval-weighted least squares method,enhanced by the improved Krawczyk operator,thereby minimizing the expansion resulting from interval operations.Finally,the feasibility and accuracy of the proposed interval harmonic state estimation method are validated.
