CN-115513941-B - Adjustable robust interval optimization method of electric-thermal comprehensive energy system considering hydrogen energy storage

Abstract

The invention discloses an adjustable robust interval optimization control method of an electric-thermal integrated energy system taking hydrogen energy storage into consideration, which comprises the steps of establishing a wind-hydrogen mixed system model taking wind power uncertainty into consideration in an intermittent working mode, establishing a robust interval optimization model containing wind power in an interval mode, meeting allowable constraint conditions in all wind power output allowable intervals, converting the robust interval optimization model into a single-layer model by adopting a dual theory, constructing an adjustable robust interval optimization model of the electric-thermal integrated energy system taking the wind power uncertainty into consideration based on the robust interval optimization model containing the wind power, adopting a binary unfolding method to convert the non-convex nonlinear model into a linear model, optimizing and analyzing an electric-thermal integrated energy system consisting of a PJM-5 node power system and a 6-node thermodynamic system, improving the wind power consumption and reducing the system operation cost.

Inventors

• SONG ZHUORAN
• CHEN YAN
• DOU WENLEI
• WANG ZHENG
• JIANG TAO
• LI JIANFENG
• WANG CHUNFENG
• TONG YONGJI
• ZHU HONGBO
• Lu Sichen

Assignees

• 国网辽宁省电力有限公司经济技术研究院
• 东北电力大学

Dates

Publication Date

20260512

Application Date

20221014

Claims (3)

1. 1. An adjustable robust interval optimization control method of an electric-thermal integrated energy system considering hydrogen energy storage is characterized by comprising the following steps: establishing a wind-hydrogen mixed system model under the intermittent working mode; Taking uncertainty of wind power into consideration in a section form, constructing a robust section optimization model containing wind power, and converting the robust section optimization model into a single-layer model by adopting a dual theory in all wind power output allowable sections which meet allowable constraint conditions; Based on a robust interval optimization model containing wind power, a time-varying participation factor is introduced, an adjustable robust interval optimization model of an electric-thermal integrated energy system considering wind power uncertainty is constructed, the model is a non-convex nonlinear model, and a binary expansion method is adopted to convert the non-convex nonlinear model into a linear model; The electricity-heat comprehensive energy system formed by the PJM-5 node power system and the 6 node thermodynamic system is optimally analyzed, so that the consumption of wind power is improved, and the running cost of the system is reduced; the linear model is as follows: ; Wherein T is time; the number of the thermal power generating units; Quoting the power generation cost of the conventional unit i; the output force of the conventional unit at the moment t; The number of wind farms; Quoting the wind power generation cost; the wind power can be scheduled; is the number of hydrogen energy storage systems; The hydrogen is c h 、c fc is the unit operation cost of the electrolyzer and the fuel cell, and P h,t 、P fc,t respectively represents the power consumption of the electrolyzer and the power generation of the fuel cell; investment cost for unit capacity of the hydrogen storage tank; The capacity of the hydrogen storage tank at the moment t; The number of CHP units; Quoting the power generation cost of the CHP unit; the power of the adjustable unit is downwards adjusted for the time t; the downward power of the adjustable unit at the moment t is adjusted, s is a participation factor; The power output of the CHP unit is at the time t; wherein, two variables WPu i, t and WPd i are introduced, t replaces the wind power imbalance power: ; wherein Puw, j, t and Pd w, j, t represent the upper and lower limits of the predicted wind power; And Representing upper and lower limits of allowable output wind power; Let z ki = x ki s i,t , w ki = y ki s i,t : Converting bilinear terms into linear terms: ; ; ; ; Wherein, the Is a time-varying participation factor.
2. 2. The method for optimizing and controlling an adjustable robust interval of an electric-thermal integrated energy system taking hydrogen energy into consideration according to claim 1, wherein the wind-hydrogen hybrid system model is as follows: ; ; ; ; Wherein P h,t 、P fc,t represents the power consumption of the electrolytic tank and the power generation of the fuel cell respectively, Q h,t 、Q fc,t represents the power generation of the electrolytic tank and the fuel cell respectively, H H2 represents the high heat value of hydrogen, n t represents the hydrogen generation rate of the electrolytic tank at the time t, m t represents the hydrogen consumption rate of the fuel cell at the time t, eta h 、η fc represents the efficiency of the electrolytic tank and the fuel cell respectively, E t represents the capacity of a hydrogen storage tank at the time t, lambda h,t and lambda fc,t are binary variables, the hydrogen storage system cannot be charged and discharged at the time t simultaneously, Q H2,t represents the heat energy stored by the heat storage tank at the time t, eta ch represents the heat exchanger efficiency, and Q con,t 、Q thermal,t represents the heat power consumed by the hydrogen storage system at the time t and the heat power provided for the regional heat grid system respectively.
3. 3. The method for optimizing and controlling the adjustable robust interval of the electric-thermal integrated energy system by considering hydrogen energy storage according to claim 1, wherein the uncertainty of wind power is considered in an interval form, a robust interval optimizing model containing wind power is constructed, the allowable constraint condition is met in all wind power output allowable intervals, and the robust interval optimizing model is converted into a single-layer model by adopting a dual theory: 1) Taking uncertainty of wind power into consideration in a section form, constructing a robust section optimization model containing wind power, and obtaining a corresponding optimal target when wind power output is within any given section range, so that wind power plant output is established on a section basis: ; wherein x represents the output power of a conventional unit, y represents the output power of a wind farm; The wind power output-allowed interval is represented, the wind power prediction interval is represented by [ y d , y u ], and the constant coefficient matrix is A, B, D, V; The upper output limit of the conventional unit is indicated, The method comprises the steps of representing the lower output limit of a conventional unit, wherein d represents the lower limit index of a wind power prediction interval, and u represents the upper limit index of the wind power prediction interval; 2) Based on the dual theory, the method is converted into a single-layer linear programming model by introducing a variable lambda, and the method is concretely as follows: ; by introducing auxiliary variables, the conversion is as follows: ; wherein, A i 、B i 、D i is a constant coefficient matrix; by the dual theory, the method is converted into: 。

Description

Adjustable robust interval optimization method of electric-thermal comprehensive energy system considering hydrogen energy storage Technical Field The invention relates to the field of power systems, in particular to an adjustable robust interval optimization control method of an electric-thermal integrated energy system considering hydrogen energy storage. Background In recent years, in the background of deterioration of ecological environment and shortage of fossil energy, the proportion of renewable energy sources such as wind power and photovoltaic has been rapidly increased, and comprehensive energy systems have been attracting attention. However, due to the high proportion of wind power incorporated into the grid, the volatility and uncertainty of wind power pose a great threat to the safe operation of the power system, especially in areas where there is a need for heating. As one of important components of the integrated energy system, the electric-thermal integrated energy system can improve the flexibility of system operation and the capacity of the system for absorbing wind power. Therefore, the coordination optimization between the electric power system and the regional heating system is carried out, and the improvement of the energy utilization efficiency and the wind power consumption capability has important significance. In addition, the increase of the new energy power generation proportion reduces the flexibility of the power system under the constraint of the existing power supply structure. In order to improve the flexibility of the power system in the high-permeability renewable energy power generation system, a strategy of combining the renewable energy power generation system with an energy storage system to form a hybrid system is greatly developed. However, conventional energy storage has a limited effect on reducing the use of fossil energy and reducing carbon emission due to a single energy conversion form. In comparison, the hydrogen energy storage is taken as a novel energy storage means with zero carbon emission and multi-energy combined storage capacity, has a certain substitution effect on traditional energy sources such as fire coal, fuel gas and the like, and is considered as secondary energy perfectly complementary with electric power. When the wind power uncertainty problem is processed in actual operation, the solution by adopting a deterministic model may not be feasible. In order to cope with uncertainty of wind power, common methods include a stochastic programming method and a robust optimization method. The probability in the random programming needs to obtain a probability distribution function of an uncertain quantity and has large calculated quantity, and the robust optimization does not need to obtain probability distribution of the uncertain quantity, but only needs to obtain a variation range of the uncertain quantity. However, for traditional robust optimization, the generated energy and wind power output power of a conventional unit are regarded as fixed values, when an uncertainty set is given and cannot be adjusted, the obtained result has larger prediction error, unnecessary wind power reduction can be caused, and the output power of a wind power plant is difficult to accurately track. The robust interval optimization is an effective method for processing wind power uncertainty, so that the electric-thermal comprehensive energy system needs to be controlled from the angle of the robust interval optimization. Disclosure of Invention The invention provides an adjustable robust interval optimization control method of an electric-thermal comprehensive energy system taking hydrogen energy storage into consideration, which fully exerts the adjustment capability of a conventional unit on the premise of ensuring the safety and economic operation of the electric-thermal comprehensive energy system, maximally dissipates wind power, can effectively solve the problem that the output power of a wind power plant is difficult to accurately track due to the wind power output prediction data error, and has stronger robustness in the prediction uncertainty environment, and is described in detail below: An adjustable robust interval optimization control method of an electric-thermal integrated energy system considering hydrogen energy storage, the method comprising: establishing a wind-hydrogen mixed system model under the intermittent working mode; Taking uncertainty of wind power into consideration in a section form, constructing a robust section optimization model containing wind power, and converting the robust section optimization model into a single-layer model by adopting a dual theory in all wind power output allowable sections which meet allowable constraint conditions; Based on a robust interval optimization model containing wind power, a time-varying participation factor is introduced, an adjustable robust interval optimization model of an electric-thermal compreh