Modern central heating systems with logwood boilers are comprised of the boiler, a buffer storage and solar thermal collectors. Conventional control strategies for these heating systems do not coordinate the utilization of all components. This can lead to a sub-optimal operation of the entire heating system resulting in a loss of efficiency and increased pollutant emissions. This contribution presents a control strategy which considers all components of the heating system including the user and forecasts for the solar yield and heat demand. It determines and carries out an optimal operating strategy that improves the user utility and maximizes the heating system efficiency while also ensuring a clean and efficient combustion. The control strategy continuously learns the user behavior and instructs the user when to refill the logwood boiler and how much fuel to use. The new control strategy was verified through test runs performed at an experimental setup consisting of a commercially available logwood boiler with a nominal capacity of $28\text{kW}$, two buffer storages with a capacity of $1.5{\text{m}}^3$ each and a heating device with a thermal output of up to $12\text{kW}$ simulating a solar thermal collector. During these test runs, the CO emissions were reduced by $93.6\text{\%}$ in the main combustion phase, $7.1\text{\%}$ more solar yield was utilized, the buffer losses were reduced by $-16.9\text{\%}$ and the overall efficiency was increased by $3.1\text{\%}$. Thus, the application of this control strategy resulted in a significantly improved user utility and heating system efficiency.

配备木柴锅炉的现代中央供暖系统由锅炉，缓冲存储器和太阳能集热器组成。这些加热系统的常规控制策略无法协调所有组件的利用。这会导致整个加热系统的运行欠佳，从而导致效率降低和污染物排放增加。该贡献提出了一种控制策略，该策略考虑了供暖系统的所有组件，包括用户，并预测了太阳能产量和热量需求。它确定并执行了最佳的操作策略，可改善用户效用并最大化加热系统的效率，同时确保清洁高效的燃烧。控制策略不断学习用户的行为，并指导用户何时加注原木锅炉以及使用多少燃料。通过在实验装置上进行的试验运行对新的控制策略进行了验证，该试验装置由标称容量为1的市售木柴锅炉组成$28\text{千瓦}$，两个容量为 $1.5{\text{米}}^3$ 每个加热装置的热输出高达 $12\text{千瓦}$模拟太阳能集热器。在这些测试运行中，CO排放量减少了$93.6\text{％}$ 在主要燃烧阶段 $7.1\text{％}$ 利用了更多的太阳能产量，缓冲损失减少了 $-16.9\text{％}$ 整体效率提高了 $3.1\text{％}$。因此，这种控制策略的应用大大提高了用户的使用率和加热系统的效率。