摘要
在多能源耦合的综合能源系统(IES)中,随着高比例可再生能源的高度渗透,给IES的灵活运行提出了新的挑战。考虑到天然气网的慢动态所带来的惯性特性,可利用差分法将天然气网高度非线性偏微分方程转化为线性代数方程组,同时,现有的IES大多只考虑单一机组或者耦合设备的运行状况,严重影响系统的联合优化运行。为此,本文以系统经济性和最低碳排放为目标,考虑天然气网惯性特征,构建结合燃气轮机、燃气内燃机、燃气锅炉等多种耦合设备运行约束的IES日前优化调度模型,并运用PSO算法对建立的IES优化调度模型进行求解,并借助MATLAB仿真软件编写程序进行仿真分析,最后得到使IES具有最小运行成本的调度策略。所得结果表明,在通过日前优化调度,更准确的体现了IES在协调各惯性网络及耦合设备的出力中系统的变化过程,验证了各能源网及耦合设备可在一定范围内为系统提供功率支撑,在考虑碳排放最低的前提下以实现经济最优。
In the multi-energy coupling integrated energy system (IES), with the high penetration of high proportion of renewable energy, the flexible operation of IES has posed new challenges. Considering the inertia characteristics brought by the slow dynamics of the natural gas network, the highly non-linear partial differential equations of the natural gas network can be converted into linear alge-braic equations using the difference method. At the same time, most of the existing IES only con-sider the operation of a single unit or coupling equipment, which seriously affects the joint optimi-zation operation of the system. Therefore, taking the system economy and the lowest carbon emis-sions as the objectives, taking into account the inertia characteristics of the natural gas network, this paper constructs an IES day-ahead optimal scheduling model that combines the operation con-straints of gas turbines, gas internal combustion engines, gas boilers and other coupling equipment, and uses PSO algorithm to solve the established IES optimal scheduling model, and uses MATLAB simulation software to write programs for simulation analysis. Finally, the scheduling strategy that makes IES have the minimum running cost is obtained. The results show that through the day-ahead optimization scheduling, the system change process of IES in coordinating the output of various inertial networks and coupling equipment is more accurately reflected, and the energy networks and coupling equipment can provide power support for the system within a certain range, so as to achieve economic optimization under the premise of considering the lowest carbon emis-sions.
出处
《建模与仿真》
2023年第2期1284-1294,共11页
Modeling and Simulation
