Abstract: A method for making a spatio-temporal combined optimal scheduling strategy of a mobile energy storage (MES) system includes: inputting data of a power system, a traffic system, and an MES system; setting a time interval, and initializing a time interval counter; inputting real-time fault, traffic, and MES data; and performing rolling optimization and solving, and delivering regulation decision instructions of the MES system, till a fault is removed. The core of the present disclosure is to propose a spatio-temporal combined optimal model of the MES system to describe spatio-temporal coupling statuses of an energy storage vehicle, a traffic network, and a power distribution network. The present disclosure provides guidance for an optimal scheduling decision of the MES system by properly regulating a traveling path and charging and discharging power of the MES system, thereby supporting high-reliability operation of the power distribution network.

Abstract: A control method and system for a distribution network with distributed mobile energy storage systems is disclosed which relates to the power field. The present invention manages the multiple distributed mobile energy storage systems in the distribution network in a unified way, to improve the flexibility of the distribution network, and enable the distributed mobile energy storage systems to fully smooth new energy generation fluctuations, implement peak cut, facilitate grid auxiliary services, and improve the power quality. The control method includes: acquiring, by a sub-station coordination system, data of the distributed mobile energy storage systems; receiving, by a master-station dispatching system, the data of the distributed mobile energy storage systems, and obtaining external data; generating, by the master-station dispatching system, a control instruction; and controlling, by the sub-station coordination system, the distributed mobile energy storage systems.

Abstract: A control method and system for a distribution network with distributed mobile energy storage systems is disclosed which relates to the power field. The present invention manages the multiple distributed mobile energy storage systems in the distribution network in a unified way, to improve the flexibility of the distribution network, and enable the distributed mobile energy storage systems to fully smooth new energy generation fluctuations, implement peak cut, facilitate grid auxiliary services, and improve the power quality. The control method includes: acquiring, by a sub-station coordination system, data of the distributed mobile energy storage systems; receiving, by a master-station dispatching system, the data of the distributed mobile energy storage systems, and obtaining external data; generating, by the master-station dispatching system, a control instruction; and controlling, by the sub-station coordination system, the distributed mobile energy storage systems.

Abstract: Provided is a source-load cooperation access method for a power distribution region. The method includes: establishing a timing feature model of a distributed generator and a timing feature model of a load respectively, acquiring a timing feature of the distributed generator in an access power distribution region by using maximum likelihood estimation and acquiring a timing feature of a user which accesses the power distribution region by using classification and regression trees; and inputting the timing feature of the distributed generator and the timing feature of the user which access the power distribution region into a combination optimization model, and determining a source-load access feeder through optimization.

Abstract: A method for making a spatio-temporal combined optimal scheduling strategy of a mobile energy storage (MES) system includes: inputting data of a power system, a traffic system, and an MES system; setting a time interval, and initializing a time interval counter; inputting real-time fault, traffic, and MES data; and performing rolling optimization and solving, and delivering regulation decision instructions of the MES system, till a fault is removed. The core of the present disclosure is to propose a spatio-temporal combined optimal model of the MES system to describe spatio-temporal coupling statuses of an energy storage vehicle, a traffic network, and a power distribution network. The present disclosure provides guidance for an optimal scheduling decision of the MES system by properly regulating a traveling path and charging and discharging power of the MES system, thereby supporting high-reliability operation of the power distribution network.

Abstract: Disclosed are a distribution transformer terminal and a method for monitoring a state of a distribution transformer court device. The distribution transformer terminal includes an ARM core processor, a carrier communication module connected to a court device, a sub-G wireless communication module connected to the court device and a GPS module connected to the court device. The ARM core processor is connected to the carrier communication module, the sub-G wireless communication module and the GPS module. The ARM core processor is configured to identify a phase of the court device and a court to which the court device belongs, acquire an operating state and fault information of the court device through the sub-G wireless communication module, and acquire geographical location information of the court device through the GPS module.

Abstract: The invention relates to a method for real-time scheduling of multi-energy complementary micro-grids based on a Rollout algorithm, which is technically characterized by comprising the following steps of: Step 1, setting up a moving-horizon Markov decision process model for the real-time scheduling of the multi-energy complementary micro-grids with random new-energy outputs, and establishing constraint conditions for the real-time scheduling; Step 2, establishing a target function of the real-time scheduling; Step 3, dividing a single complete scheduling cycle into a plurality of scheduling intervals, and finding one basic feasible solution meeting the constraint conditions for the real-time scheduling based on a greedy algorithm; and Step 4, finding a solution to the moving-horizon Markov decision process model for the real-time scheduling of the multi-energy complementary micro-grids by using the Rollout algorithm based on the basic feasible solution from Step 3.

Abstract: Disclosed are a distribution transformer terminal and a method for monitoring a state of a distribution transformer court device. The distribution transformer terminal includes an ARM core processor, a carrier communication module connected to a court device, a sub-G wireless communication module connected to the court device and a GPS module connected to the court device. The ARM core processor is connected to the carrier communication module, the sub-G wireless communication module and the GPS module. The ARM core processor is configured to identify a phase of the court device and a court to which the court device belongs acquire an operating state and fault information of the court device through the sub-G wireless communication module, and acquire geographical location information of the court device through the GPS module.

Abstract: Provided is a source-load cooperation access method for a power distribution region. The method includes: establishing a timing feature model of a distributed generator and a timing feature model of a load respectively, acquiring a timing feature of the distributed generator in an access power distribution region by using maximum likelihood estimation and acquiring a timing feature of a user which accesses the power distribution region by using classification and regression trees; and inputting the timing feature of the distributed generator and the timing feature of the user which access the power distribution region into a combination optimization model, and determining a source-load access feeder through optimization.

Abstract: The invention relates to a method for real-time scheduling of multi-energy complementary micro-grids based on a Rollout algorithm, which is technically characterized by comprising the following steps of: Step 1, setting up a moving-horizon Markov decision process model for the real-time scheduling of the multi-energy complementary micro-grids with random new-energy outputs, and establishing constraint conditions for the real-time scheduling; Step 2, establishing a target function of the real-time scheduling; Step 3, dividing a single complete scheduling cycle into a plurality of scheduling intervals, and finding one basic feasible solution meeting the constraint conditions for the real-time scheduling based on a greedy algorithm; and Step 4, finding a solution to the moving-horizon Markov decision process model for the real-time scheduling of the multi-energy complementary micro-grids by using the Rollout algorithm based on the basic feasible solution from Step 3.