7 results about "Electricity demand forecasting" patented technology

This invention discloses a power dispatching method, system, equipment, and medium based on daily planning and simulated operation, belonging to the field of power dispatching technology. The specific steps are as follows: First, acquire real-time and historical power grid data to establish a power demand dataset. Second, establish a power demand forecasting model, perform time series analysis on historical and real-time power grid data, and forecast future power demand. Third, establish a multi-objective optimization function, and use an improved genetic algorithm to solve the multi-objective optimization function to obtain the optimal power dispatching scheme. Fourth, input the optimal power dispatching scheme into the simulation model for verification, and then issue the verified optimal power dispatching scheme for execution. This invention, through the closed-loop fusion of data-driven prediction, multi-objective intelligent optimization, and high-fidelity simulated operation, transforms the traditional static dispatching mode relying on human experience into a dynamic optimization and proactive defense intelligent decision-making mode. This improves the automated generation capability of dispatching plans and the level of safety pre-control.

The present invention comprises: a communication unit that communicates with a host system that creates a regional energy plan; a target setting unit that sets a target value for creating balancing power for a target consumer site; a prediction unit that predicts future electric power demand; a boundary-condition-setting unit that sets a boundary condition for demand control from load facility specifications; an operation plan creation unit that creates a demand control plan for the load facilities from the target value for balancing power, the future electric power demand prediction, and the boundary condition for demand control; and an input / output unit. The regional energy plan is created or corrected by the host system on the basis of whether the demand control plan can be executed.

This invention discloses a method and system for electricity demand forecasting based on big data analysis, belonging to the field of power big data analysis and load forecasting technology. It addresses the problems of multi-step rolling error accumulation and large peak-valley load forecasting deviations in traditional electricity demand forecasting. This invention collects and standardizes multi-source data on historical load, meteorological, date characteristics, and electricity consumption structure, jointly identifying and correcting abnormal data. Through error propagation characteristic analysis, a comprehensive error propagation index is constructed. Based on wavelet decomposition, hierarchical forecasting of trend, periodic, and fluctuation components is performed, and a dynamic weight allocation strategy is designed in conjunction with the error propagation index. An error compensation and confidence decay mechanism is introduced, and rolling updates and segmented verification corrections are performed, significantly improving the stability and accuracy of electricity load forecasting.

System and method ensure stability of power transmission system or power grid with mixed generation sources of renewable and non-renewable types while providing a best combination of stability services that minimizes both cost of generation and guaranteed reliability. An energy market management (EMM) module derives an energy market dispatch for a mix of generation sources including renewable and conventional types based on a steady state optimization of supplier cost and a power demand forecast. Dynamic Security Assessment (DSA) module performs a dynamic contingency assessment of stability for the power transmission system based on the energy market dispatch and sends feedback to the EMM module with results of the dynamic assessment of stability. EMM module clears the energy market dispatch on a condition that feedback indicates a stable dynamic assessment. For unstable assessment, data driven, model-based and / or rule-based algorithms provide recommendations on how EMM module can find stable market solutions.

To provide a hydrogen operation planning apparatus and method that can formulate an overall optimal hydrogen operation plan. [Solution] The method for formulating a plan for the production, conversion, and transportation of hydrogen and hydrogen carriers involves calculating the correlation between each parameter—predicted renewable energy generation amount, predicted electricity demand, predicted hydrogen demand, hydrogen and hydrogen carrier storage amount, hydrogen and hydrogen carrier conversion amount, and hydrogen and hydrogen carrier transportation amount—for each predetermined time period in the target area using past data. A mathematical model of the operating costs of hydrogen and hydrogen carriers is created using the calculation results. Using the created mathematical model and the aforementioned predicted renewable energy generation amount for each time period of the target day or period, the amount of hydrogen and hydrogen carrier storage, hydrogen and hydrogen carrier conversion amount, and hydrogen and hydrogen carrier transportation amount that reduce the operating costs of hydrogen and hydrogen carriers are determined for each time period.

A microgrid system using the power demand prediction model of the present invention includes: a load system that measures power consumption through an IoT-based sensor and generates power consumption data including the measured power consumption; a power generation system that generates power generation data including the amount of power produced by a power generation facility and status information of the power generation facility; an energy storage system that stores and releases power produced by the power generation facility to maintain the stability of the microgrid's power grid and generates ESS data; a control system that integrally manages the operation of components within the microgrid through a pre-trained power demand prediction model that uses the power consumption data, the power generation data, and the ESS data as input data; an external storage system that stores the power consumption data, the power generation data, and the ESS data; and an integrated operation center that collects data stored in the external storage system, retrains the power demand prediction model using the collected data, and provides the retrained power demand prediction model to the control system.

According to the present invention, a manufacturing, conversion, and transport plan for hydrogen and a hydrogen carrier is formulated by: using past data to respectively calculate, for each past prescribed time slot in a target region, the correlation among parameters constituted of a prediction value of a renewable energy power generation amount, a prediction value of a power demand amount, a prediction value of a hydrogen demand amount, storage amounts of the hydrogen and hydrogen carrier, reciprocal conversion amounts between the hydrogen and hydrogen carrier, and transport amounts of the hydrogen and hydrogen carrier; creating a mathematical model of an operation cost of the hydrogen and hydrogen carrier by utilizing the calculation results; and using the created mathematical model and the prediction value of the renewable energy power generation amount and the like for each time slot of a target date or time period to calculate, for each time slot, the storage amounts of the hydrogen and hydrogen carrier, the reciprocal conversion amounts between the hydrogen and hydrogen carrier, and the transport amounts of the hydrogen and hydrogen carrier that reduce the operation cost of the hydrogen and hydrogen carrier.