Thermoelectric optimization day-ahead scheduling method of residence integrated energy system considering multiple uncertainties

Abstract

The invention relates to a thermoelectric optimization day-ahead scheduling method for a residence integrated energy system considering multiple uncertainties. According to the scheme, a fuel cell, a storage battery, a photovoltaic power generation unit, a heat storage unit, a heat pump and other devices are included. The method comprises the following steps: firstly, carrying out random characteristic modeling on each uncertainty variable based on a time-varying Markov model; then, an operation model of the residence integrated energy system is established, and an optimal economic day-ahead scheduling problem taking the total fuel cost as a target and various operation and safety conditions as constraints is designed based on the model; and finally, solving the day-ahead scheduling problem by adopting a random dynamic programming algorithm to realize optimal scheduling of energy management under multiple uncertainties. According to the invention, thermoelectric cooperation of the residence integrated energy system can be realized, multiple uncertainties are effectively coped, thermoelectric supply and demand balance is realized, the energy utilization efficiency of the system is improved, the fuel cost is reduced, and the sustainability of operation of the residence energy system is promoted.

Description

technical field [0001] The invention relates to a scheduling method, in particular to the technical field of optimal scheduling of a sustainable cogeneration residential system containing a fuel cell, in particular to a thermal and electrical optimization day-ahead scheduling method for a residential integrated energy system that takes into account multiple uncertainties. Background technique [0002] In recent years, fuel cells have attracted more and more attention from academia and industry due to their high efficiency, flexibility, and low pollution, and have gradually become one of the effective solutions to achieve the goal of carbon neutrality. However, the main research and application of fuel cells are currently focused on hybrid vehicles, and their potential for thermoelectric optimization of residential systems remains to be further explored. At present, heating boilers are usually used for residential heating. This heating method has low efficiency and large carb...

AI Technical Summary

Problems solved by technology

Although many research models and methods centered on fuel cell / battery hybrid electric vehicles are very effective, usually with optimized control strategies to improve fuel cell efficiency, they cannot be directly applied to residential systems due to different operating requirements and load patterns

On the other hand, traditional deterministic algorithms, such as dynamic programming, can only perform energy management and efficiency optimization for systems under specific working conditions, and cannot deal with uncertain factors in system operation, such as electric and heat requirements related to user activities

Therefore, the residential system model and efficiency optimization problem for uncertain CHP application scenarios need to be studied

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