30results about How to "Optimizing Load Profiles" patented technology

The invention relates to an electric automobile optimal peak-valley time-of-use pricing method giving consideration to the owner satisfaction degree. The electric automobile optimal peak-valley time-of-use pricing method specifically comprises the following steps of (1) establishing probability models of a last journey ending moment and a daily running mileage; (2) establishing demand response models for charging and discharging of electric automobiles, including (2a) a demand response model of an A-type electric automobile, (2b) a demand response model of a B-type electric automobile and (2c) a demand response model of a C-type electric automobile; (3) establishing an optimal peak-valley time-of-use electrovalence solving model. Charging and discharging power models of the electric automobiles are established according to two factors influencing the power demands of the electric automobiles, namely charging beginning moment and the daily running mileage, then an optimal peak-valley time-of-use electrovalence solving scheme applicable to the charging and discharging of the electric automobiles is established based on the electric automobile owner satisfaction degree and power grid benefits, and investment on peak-load units and lines is reduced to some extent.

The invention provides an intelligent control method and system for interactive home appliances on the basis of time-of-use electricity price response. The method is characterized by comprising the steps that the home appliances are automatically classified according to types of home appliance loads; use habits of the home appliances of users are determined according to historical home appliance running status data collected in 30 days; according to time-of-use electricity price policy information of a receiving power grid, basic load demand ranges corresponding to all time periods are predicted and determined for the users; according to obtained user home appliance use habit characteristics and load settings, controllable degree indexes of the home appliances are calculated, and running status models of the home appliances are determined; according to the controllable degree indexes of the home appliances, dynamic control priorities and a control algorithm of the home appliances are determined, and intelligent control over the home appliances is achieved. The method and system have the advantages that interactivity is good, the receiving degree of the users is high, the users can be guided to reasonably avoid the peak hours for electricity utilization, and electricity utilization cost is remarkably reduced.

The invention discloses a power grid safety optimization dispatching method considering demand response. The method comprises the following steps: establishing a dynamic excitation compensation mechanism, and carrying out modeling on demand response behaviors of a user according to load shedding and transfer features; establishing a calculation model of power grid reliability index loss-of-load probability and expected energy not supplied; converting a reliability index into an economic index and integrating the index into an objective function, and establishing a day-ahead economic dispatch model with the total operation cost minimum being as an objective; establishing constraint conditions to enable an electric power system to meet system constraints, unit constraints and security constraints; and carrying out solving through calculation software to obtain an optimal day-ahead economic dispatch result. The demand response and reliability index are integrated into day-ahead dispatching of the electric power system, and the optimal dispatching model considering dynamic excitation compensation and expected power failure loss is established, thereby coordinately solving the problem of unit commitment of a generation power side and the problem of supply-demand interaction of a demand side and realizing economy and security of operation of a power grid.

The invention discloses an intelligent electricity consumption oriented continuous task type load energy control method. The method comprises the following steps: constructing a continuous task type load model; constructing an energy control optimized decision model; solving the continuous task type load model and the energy control optimized decision model. According to the method, the use time of the load in the high electricity price time period is shortened, and the load is transferred to the time period when the distributed energy resource electricity generation is prominent, so that the total load curve can be improved; a part of distributed energy resource electricity generating capacity is transferred by a peak-clipping valley-filling manner of an energy storage device, on the one hand, the proportion of elimination on the spot of the distributed energy resource electricity generating capacity can be increased, the wasteful power grid access manner of the surplus electric quantity can be avoided, and the better economic efficiency can be obtained; on the other hand, the adverse effects of the distributed power supply on the power grid access can be reduced, and the method is favorable to the safe and stable operation of the power grid.

The invention relates to a dual-scale charging guidance method and system for electric vehicles taking into account user satisfaction. The method divides electric vehicles into immediate charging clusters and delayed charging clusters according to the user's requirements for charging periods, and establishes charging clusters at different scales. Satisfaction function; at the time scale layer, consider grid factors and user charging cost factors to establish a model, and adjust the load curve by guiding the start charging time of electric vehicles; at the spatial scale layer, consider charging station factors and user travel cost factors to establish a model, Plan the selection of charging stations for each vehicle to improve the operating efficiency of charging stations; guide the charging behavior of electric vehicle users on time and space scales according to the obtained optimal solution. Compared with the prior art, the present invention realizes the function of optimizing load curve, traffic condition, and utilization balance of charging station equipment while ensuring user satisfaction.

The invention relates to an ordered charging control method for accessing an electromobile into a residential area in scale. The method comprises the following steps: establishing an electromobile charging load model by comprehensively considering a travel behavior of a private car and a user charging behavior, and optimizing a grid load curve by proposing two charging control methods based on theoptimal parameter valid interval. By optimizing the electromobile charging control method at the residential area, the method is in favor of balancing the load of the grid, thereby enabling the power-supply grid to operate more economic and safe.

The invention relates to a processing method for optimizing connecting information of new consumers of a power distribution network. The processing method for the optimizing connecting information of the new consumers of the power distribution network comprises the following steps of (1) carrying out industry classification on the new power consumers , meanwhile, carrying out analysis on the connected power distribution network, (2) carrying out matching on the new consumers and the power distribution network according to a different consumer combination optimization algorithm, and (3) obtaining the optimizing connecting information of the new consumers. Compared with the prior art, the processing method for the optimizing connecting information of the new consumers of the power distribution network has the advantages of improving operating efficiency of power generation and supply devices, reducing operating cost of a power system, reducing consumption of resources, being beneficial to environmental protection and the like.

The invention discloses a distributed wind storage system optimization method that considers the multi-party interests of source-grid-load. The investor's maximum internal rate of return is his goal; the user's maximum benefit after implementing demand-side response is his goal; based on the multi-objective optimization planning model of the distribution network operator, the distributed power investor and the user's three-way stakeholder, using Distributed wind storage system scheduling strategy, and fully consider the wind storage system reactive power adjustment capacity, so as to optimize the interests of the above-mentioned grid operators, distributed power investors and users. In the distributed power planning process, the present invention considers the planning scheme of the source-network-load tripartite interests, which has more practical engineering significance, can improve the income of distributed power investors, and increase the utilization rate of renewable energy.