22 results about "Fixed energy" patented technology

The invention discloses an energy management method and device for a trailer, a storage medium and a program product, and the method comprises the steps: dividing any historical route through which the trailer travels, and obtaining sub-road sections of the historical route; determining the optimal motor power of each sub-road section according to the historical driving parameters corresponding to the sub-road sections of the historical route; according to the optimal motor power of each sub-road section and the fixed energy requirement of the trailer, different battery electric quantities corresponding to the optimal motor power in the historical route are calculated, and the corresponding relation between the optimal motor power and the battery electric quantities serves as an energy management strategy of the historical route; wherein when the driving route of the trailer is the historical route, the energy output of a battery in the trailer is controlled according to the energy management strategy corresponding to the historical route. According to the technical scheme, the technical effects that energy management is conducted on the battery of the trailer, and the energy of the battery is reasonably distributed are achieved.

The invention discloses a power grid and energy storage battery collaborative energy supply strategy for normal drilling operation of oil and gas drilling, and mainly solves the problems that in a power grid and energy storage battery collaborative energy supply mode, the power grid and energy storage battery collaborative energy supply effect is poor due to a fixed energy storage battery charging and discharging power threshold value, and equipment is impacted by sudden power change. According to the scheduling strategy, on the basis that a sliding window method is combined to analyze power change rate characteristics of adjacent data acquisition points, two indexes of a power threshold value and a power change rate threshold value corresponding to discharging of the energy storage battery are dynamically adjusted, the charging and discharging state of the energy storage battery is judged, and the charging and discharging power of the energy storage battery is calculated. According to the scheduling strategy, energy supply safety of normal drilling operation of oil and gas drilling under the condition of capacity reduction of the power grid can be achieved, the cooperative energy supply effect of the power grid and the energy storage battery can be improved by dynamically adjusting the power threshold value and the power change rate threshold value, the drilling operation cost is reduced, and impact of power transmission and distribution equipment is reduced.

The invention discloses a V2G-microgrid cooperative scheduling system and method based on an improved particle swarm algorithm, and belongs to the technical field of intelligent microgrid and electric vehicle energy management. In order to solve the problems of slow response of fixed energy storage, low utilization rate of V2G mobile energy storage, uncontrollable battery loss and the like, a V2G electric vehicle and a fixed storage battery are constructed into a hybrid energy storage system, and an improved particle swarm optimization algorithm is adopted for optimization. According to the method, the frequency modulation precision, the operation economy and the battery life are synchronously optimized in a fitness function through a double-layer architecture of optimizing the total power through an upper layer and dynamically distributing instructions through a lower layer. Finally, the V2G cluster responds to high-frequency power fluctuation in a millisecond level, and a basic load is supported in a fixed energy storage minute level, so that advantage complementation is formed. According to the invention, the frequency modulation response speed and the renewable energy consumption capability of the system are effectively improved, the operation cost is reduced, and the service life of the battery is prolonged.

The invention provides an energy storage DC-DC control module structure device, and relates to the technical field of energy storage equipment, the energy storage DC-DC control module structure device comprises a module shell, the left side and the right side of the module shell are both provided with fixing supports, the left side of the module shell is provided with a first connector, the right side of the module shell is provided with a second connector, and the module shell is provided with a module upper cover. A sealing ring and a module PCBA are arranged in the module shell, the module shell is made of a high-strength alloy material, an installation groove matched with the installation of the module PCBA is formed in the module shell, a limiting structure is arranged on the wall of the groove, and the fixing support is assembled in the module shell. The space occupation and the carrying cost of the energy storage equipment are greatly reduced, the device is not only suitable for a fixed energy storage power station, but also can be flexibly applied to mobile energy storage scenes such as a portable energy storage power supply, a mobile charging station and a vehicle-mounted energy storage system, and the market application range of the product is effectively expanded.

The invention provides an EV-V2G and fixed energy storage cooperative discharge scheduling method and device, relates to the technical field of power system scheduling, and solves the technical problem that it is difficult to realize global optimal scheduling of a power distribution network through EV-V2G and fixed energy storage cooperative discharge in a multi-source uncertainty scene in the prior art. The method specifically comprises the following steps: acquiring a scheduling power parameter; constructing a collaborative optimization problem based on the scheduling power parameters; the collaborative optimization problem is divided into an EV-V2G discharge sub-problem and a fixed energy storage discharge sub-problem; converting a non-convex problem of each round of iteration of the fixed energy storage discharge problem into a standard convex optimization problem based on an iterative conversion method of continuous convex approximation; and outputting the optimal EV-V2G discharge power and the optimal fixed energy storage discharge power by alternately solving the EV-V2G discharge sub-problem and the standard convex optimization problem. The method is used for EV-V2G and fixed energy storage discharge scheduling.

The application discloses a power grid and energy storage battery collaborative energy supply strategy for normal drilling operation of oil and gas drilling, and mainly solves the problems of poor collaborative energy supply effect of the power grid and the energy storage battery, impact on equipment caused by power mutation and the like caused by the fixed energy storage battery charging and discharging power threshold in the collaborative energy supply mode of the power grid and the energy storage battery. The scheduling strategy is based on the analysis of the power change rate characteristics of adjacent data collection points by combining the sliding window method, dynamically adjusts the power threshold and the power change rate threshold corresponding to the energy storage battery discharging, judges the energy storage battery charging and discharging state, and calculates the energy storage battery charging and discharging power. The scheduling strategy can solve the energy supply safety of the normal drilling operation of oil and gas drilling under the condition of power grid capacity reduction, can improve the collaborative energy supply effect of the power grid and the energy storage battery by dynamically adjusting the power threshold and the power change rate threshold, reduce the drilling operation cost, and reduce the impact on power transmission and distribution equipment.

This invention discloses a method and apparatus for calibrating the total energy consumption of any industrial sector using electricity consumption, specifically including the following steps: obtaining the energy consumption of various types of energy in each year of the fixed production line industry to be calibrated; converting the energy consumption of each type of energy into the consumption of standard coal, calculating the steady-state percentage of electricity consumption after conversion to standard coal consumption to obtain the electricity proportion; obtaining the current real-time total electricity consumption of each enterprise included in the fixed production line industry to be calibrated, denoted as E. a E a Converted to standard coal consumption equivalent to electricity; based on the electricity share and E a The standard coal consumption corresponding to the converted electrical energy is used to calculate the current real-time total energy consumption of the industry with the fixed production line to be calibrated. Utilizing the characteristic that each industrial enterprise in each sub-industry has a fixed energy consumption ratio, real-time dynamic and accurate electricity consumption data is introduced to extrapolate the real-time dynamic and accurate total energy consumption of each enterprise in the industry, thereby obtaining the total energy consumption of the industry in real-time dynamic.

The invention discloses a dynamic carbon price coupled office building flexible load cooperative control method and system, and is applied to the technical field of intelligent calculation, and the method comprises the steps: constructing an equivalent carbon emission factor model of a target building according to the local photovoltaic power generation power consumption of the target building and the power grid purchase power consumption; the total electricity consumption in the equivalent carbon emission factor model is decomposed into indoor temperature power supply electric quantity, vehicle energy storage electric quantity, fixed energy storage electric quantity and other electric quantity; a thermal inertia model based on indoor temperature energy storage is constructed for the indoor temperature power supply electric quantity, and an energy storage model based on charging and discharging power is constructed for the vehicle energy storage electric quantity and the fixed energy storage electric quantity; and solving the equivalent carbon emission factor model by taking the minimum total generalized cost as a target to obtain control parameters of different time periods. According to the invention, the electricity price cost and the carbon emission cost are comprehensively considered to regulate and control the related data of the building, and the optimal balance point between the electricity price valley and the photovoltaic peak can be found according to the cost saving and carbon emission demands of the user.

The invention discloses a power distribution system collaborative optimization operation method and device, and the method comprises the steps: constructing a generalized energy storage collaborative optimization model of a power distribution system according to the charging and discharging characteristics of an electric vehicle, the charging and discharging characteristics of a fixed energy storage device, and the load characteristics; constructing a context vector learning model containing a mapping relation between context vectors and optimization parameters by using historical operation data of the power distribution system and a generalized energy storage collaborative optimization model of the power distribution system and adopting a Gaussian process regression method; according to the mapping relation, a context vector of the current scene is extracted, initial distribution of parameters is predicted and optimized, and an initial mean vector and a covariance matrix of a CMA-ES algorithm are obtained; and executing a CMA-ES iterative optimization process by adopting the initial mean vector and the covariance matrix, and outputting a scheduling scheme of the electric vehicle and the fixed energy storage device containing the charging and discharging power of each time period. According to the scheme, hot start of the CMA-ES algorithm is realized through context vector learning, the optimization efficiency is improved, and falling into a local optimal solution is avoided.

The application discloses a kind of cluster control methods of mobile emergency energy storage charging station, obtain the traffic information corresponding to the preset area and objective adjustment information, according to traffic information and initial configuration information, generate the initial charging site of mobile energy storage charging station in preset area;According to the site adjustment strategy of mobile energy storage charging station in preset area is generated according to objective adjustment information;According to site adjustment strategy, the initial charging site in preset area is adjusted in different time section, and the final charging site of mobile energy storage charging station is obtained.It can be based on the charging demand of new energy in population-intensive scene, comprehensive existing fixed energy storage charging station and mobile energy storage charging station, consider the demand of power distribution network reliability and economy, realize the configuration of mobile energy storage charging station in emergency power supply and daily operation two scenes, while being able to provide diversified application and service to local power energy load, improve the utilization of mobile energy storage charging station.

The invention discloses a clearing method and system for multi-element resources of a micro market, and the method comprises the steps: obtaining the electricity purchasing demand information of a power user in a region to be cleared, the electricity selling demand information of a distributed power supply, and the declaration information of distributed energy storage equipment; a fixed energy block and a translational energy block are constructed based on electricity purchasing demand information and electricity selling demand information, a variable energy block is constructed according to declaration information, distributed energy storage resources are effectively integrated by constructing the energy blocks, a clearing optimization model is constructed, the energy blocks are used for solving, and a solving result is obtained. And the solution result is used as a clearing result to clear the multi-element resources of the micro market, and unified expression and executable constraint of the multi-type resources are realized on the premise of not increasing the solution complexity, so that efficient clearing is realized.

The invention relates to the technical field of charging scheduling, and provides a privacy protection type multi-agent electric vehicle charging scheduling method and system, and the method comprises the steps: enabling each charging pile agent to determine an adjustment ratio through a deep reinforcement learning method of flexible motion-evaluation, performing privacy protection confusion processing on the arrival time and the departure time through a discrete Gaussian noise mechanism; based on the confused arrival time and departure time, a centralized training-decentralized execution multi-agent deep reinforcement learning method is adopted, and a plurality of charging pile agents cooperatively determine the charging energy of the charging piles in each time period; the method comprises the following steps: acquiring photovoltaic generating capacity and fixed energy consumption of a light storage charging station, combining charging energy of a charging pile, and determining charging and discharging capacity of an energy storage system in each time period through a deep reinforcement learning algorithm of an energy storage system agent; and the multi-target requirements of user privacy protection, station profit optimization, load smoothing and the like are met.

The invention relates to the technical field of new energy optimization scheduling, and discloses a power distribution network source-load collaborative scheduling method considering multiple types of flexible resources, which considers the diversity and space-time difference of the flexible resources, introduces multiple flexible resources, enriches the resource types of source-load bilateral collaboration, and improves the resource utilization rate. The feasibility and effectiveness of source-load cooperation in different scenes are expanded. In addition to considering fixed energy storage resources, a demand response mechanism is also introduced, and user-side flexible resources are brought into a scheduling process; and meanwhile, the space flexibility and the time sequence adjustment capability of the mobile energy storage equipment are considered, and a source-load collaborative scheduling model considering multiple types of flexible resources is constructed. Further, aiming at the time-space characteristics that the mobile energy storage equipment needs to decide a destination and charging and discharging power at the same time, a PDQN algorithm based on a mixed action space is introduced; the method can effectively promote source-load coordination, reduce network loss, promote new energy consumption, and improve the operation economy of the power distribution network.

The invention discloses an energy scheduling method and device based on traffic flow prediction, and the method achieves the dynamic movement of the electric energy of an electric point location with a small power demand to an electric point location with a large power demand through a mobile energy storage unit, assists the stable operation of the electric point location in urgent need of the electric energy, and improves the operation efficiency. And the energy utilization rate of the electric point with less electric demand is greatly improved. In addition, the mobility of the mobile energy storage unit enables the mobile energy storage unit to dynamically realize energy coordination among different electric point locations. Therefore, dynamic energy coordination among a large number of electric point locations can be realized based on a small number of mobile energy storage units, the energy supply cost is greatly reduced, the problem that the fixed energy storage equipment is idle for a long time due to the addition of a large number of fixed energy storage equipment or a small number of fixed energy storage equipment cannot support sudden energy demands is avoided, and the energy supply efficiency is improved. The contradiction between the energy supply cost and the sudden energy demand is solved, and green energy management is realized. Specifically, for the expressway energy system, if the mobile energy storage unit of the scheme is adopted, stable operation of the expressway energy system can be well guaranteed on the basis of no need of arranging a plurality of electric point positions in the expressway traffic flow peak period, the energy utilization rate and the energy supply cost of the high-altitude road energy system are reduced, and the energy utilization rate of the expressway energy system is increased. Dynamic cooperative scheduling of traffic flow and energy supply is realized, the elasticity and reliability of energy scheduling of a highway energy system are improved, and the insufficiency of power grid energy scheduling is effectively made up.

The invention discloses an electric bus pre-disaster pre-deployment robust optimization method and system, and belongs to the technical field of disaster prevention and reduction of power systems. The method comprises the following steps: acquiring power grid, bus, load and disaster prediction data; adopting Monte Carlo simulation to generate a fault scene set; establishing a robust optimization model with minimization of system load shedding as a target, considering electric bus operation, dispatching and scheduling constraints and power distribution network system constraints, and describing line fault uncertainty by constructing an enhanced confidence set; camp is adopted; and solving the model by a CG decomposition algorithm to obtain an optimal pre-deployment scheme. According to the method, the problems of inflexible deployment and high cost of traditional fixed energy storage in post-disaster recovery are effectively solved, and the post-disaster recovery speed and the elasticity level of the power distribution network are remarkably improved and the power failure economic loss is reduced while the normal bus service is ensured by utilizing the mobile energy storage characteristic of the electric bus.

According to the method, complementary characteristics of virtual energy storage, fixed energy storage and new energy are fully utilized, the two-way dynamic wireless charging and discharging system of the electric vehicle is used as virtual energy storage to be applied to a power-traffic coupling network, and the optimal configuration of the two-way dynamic wireless charging and discharging system of the electric vehicle is achieved with the purpose of minimizing the comprehensive cost of energy storage facilities. Constructing an optimal configuration model of the power-traffic coupling network; and solving the optimal configuration model of the power-traffic coupling network to obtain an optimal configuration and operation scheme of the bidirectional dynamic wireless charging and discharging system and the fixed energy storage system. The two-way dynamic wireless charging and discharging system is applied to the electric power-traffic coupling network, dynamic wireless charging and discharging of the electric vehicle flow are controlled according to the load time sequence characteristics of the power grid in a three-party flexible interaction mode, the two-way dynamic wireless charging and discharging system is flexibly configured on the basis that normal driving and using of the electric vehicles are not affected, and the dynamic wireless charging and discharging efficiency is improved. The electrified road has a virtual energy storage effect, the new energy consumption capability of the energy storage system is improved, and stable operation of a power grid is maintained.

The application relates to the technical field of new energy optimization scheduling, and discloses a power distribution network source-load collaborative scheduling method considering multiple types of flexible resources. The method considers the diversity and space-time difference of flexible resources, introduces multiple types of flexible resources, enriches the resource types of source-load bilateral collaboration, and expands the feasibility and effectiveness of source-load collaboration in different scenarios. In addition to considering fixed energy storage resources, the method also introduces a demand response mechanism, integrates user-side flexible resources into the scheduling process, and at the same time, considers the space flexibility and time sequence adjustment capacity of mobile energy storage equipment, and builds a source-load collaborative scheduling model considering multiple types of flexible resources. Furthermore, aiming at the space-time characteristics that the mobile energy storage equipment needs to simultaneously decide the destination and charging and discharging power, the method introduces a PDQN algorithm based on a mixed action space. The application can effectively promote source-load collaboration, reduce network loss, promote new energy consumption, and improve the economic efficiency of power distribution network operation.

This application provides a method for coordinated scheduling of multiple home energy devices, including: comparing the expected dwell time with a preset duration threshold; if the dwell time is lower than the threshold, assessing the power supply gap risk level after the mobile energy storage leaves using a support vector machine algorithm; determining the adjusted lower limit of discharge depth based on the difference between the power supply gap risk level and the current state of charge, combined with the remaining power of the electric vehicle; using a linear regression algorithm to process the lower limit of discharge depth and the system's dispatchable capacity to determine the distribution of the number of charge and discharge cycles in each time period of the day; integrating the optimized discharge depth value and the supplementary adjustment scheme with the initial scheduling basic information to generate the final fixed energy storage discharge strategy and deploy and execute it, thereby completing the optimized scheduling of the fixed energy storage's daily charge and discharge cycles.

This invention discloses a method and system for decoupling and evaluating the combined capacity value of wind and energy storage, relating to the field of new power system planning and operational reliability assessment technology. The method includes: acquiring full-time-series basic data and defining the basic value of system adequacy; obtaining the optimal energy storage charging and discharging execution strategy through wind-energy storage joint operation simulation; executing dynamic reconstruction and joint output truncation of the real risk period set; obtaining the reconstructed real risk period set; and extracting the joint output time-series statistical characteristic parameters; finally, using an equivalent reliable capacity assessment model, solving for the overall equivalent capacity value of the wind-energy storage joint system to the power grid, thereby achieving nonlinear decoupling and confirmation assessment of the effective capacity of the wind power itself. This invention overcomes the limitations of traditional capacity assessment methods, such as fixed energy storage operation strategies, static extraction of risk periods, and difficulty in separating joint gains. It provides a quantitative basis for optimizing the long- and short-term energy storage capacity configuration of high-proportion wind power systems and designing power market capacity compensation mechanisms.

The invention discloses an urban and rural charging and storage combined scheduling method and system based on mobile energy storage, and belongs to the crossing field of energy internet and power markets, and the method comprises the steps: obtaining and preprocessing urban and rural power grid, traffic and market multi-source measurement data, and constructing a power-traffic double-flow weighted fusion graph model; establishing a day-ahead and intra-day double-layer prediction model of village and town new energy power generation and urban and rural node electricity price; a two-stage optimization scheduling model including day-ahead planning and intra-day scheduling is designed, a cooperative scheduling mechanism of fixed energy storage and mobile energy storage of villages and towns and an abnormal scene coping strategy are introduced, and a dynamic scheduling scheme is generated through alternate iteration solution by taking the maximum net benefit of operation of a mobile energy storage vehicle as a scheduling target. According to the method, a rural storage and urban use commercial operation mode is adopted, the economic benefits of mobile energy storage vehicle operators are guaranteed, the new energy consumption rate of villages and towns is improved, urban power grid congestion is relieved, and key technical support is provided for large-scale marketization application of mobile energy storage.

Systems and methods for advanced energy settlements in electric power grid are proposed. At least one energy customer, at least one retail electric provider and at least one distributed generator connect to an advanced energy settlement platform communicatively. The advanced energy settlement platform is operable to summate a customer balance from all the settlement blocks during a billing period and collect payments from the at least one energy customer automatically; aggregate and settle distributed energy charges with distributed generators and fixed energy charges with the energy retailer or retail energy provider for the at least one energy customer during the billing period. The advanced energy settlement platform also provides interactive graphical user interface for different participants in the advanced energy settlement and for advanced energy settlements application development kit (ADK) for access to functionality within the advanced energy settlement platform.

The invention relates to the technical field of mine electromechanical control, and provides a mine hoist emergency security power supply system and an emergency control method thereof. The system comprises a direct current collection bus; the AC end of the bidirectional converter is connected with the power grid, and the DC end is connected with the DC collection bus; the direct-current end of the four-quadrant frequency converter is connected with the direct-current collection bus, the alternating-current end of the motor side is connected with the mine hoist, and regenerative electric energy generated when the mine hoist is in a regenerative braking state is fed back to the direct-current collection bus; a fixed energy storage unit; the vehicle network interaction interface is connected with the direct current collection bus; and the energy management controller is used for controlling the fixed energy storage unit and / or the power battery to supply power to the mine hoist when the power grid fails. The bidirectional converter and a traditional frequency converter are deeply fused, the problems that a traditional emergency power supply is slow in response and complex in structure are fundamentally solved, and the safety requirement of emergency management is completely met.