多目标约束下给水管网水质传感器选址优化算法的研究

利用EPANET2模拟扩展周期非稳态水力水质条件下管网节点污染物浓度变化,根据各个节点被注入污染物后,在管网模拟结束时得到的选址目标值的大小来确定节点有可能作为污染物注入的节点,目标值越大,该节点被选择的可能性越大.另外,本文提出了基本粒子群算法与遗传算法交叉、变异算子相结合的整数编码的优化算法来求解水质传感器选址问题,并编制了相应的计算程序.文中结合算例,以经过归一化后的节点平均坐标作为衡量选址结果的指标,得到了不同污染物注入开始时刻、注入持续时问和质量注入速率条件下传感器选址节点平均坐标的累计分布函数图,为传感器的选址提供参考.

Optimal algorithm for determining locations of water quality sensors in water supply networks under multi objective constraints

The time series of contaminant concentration at nodes of water supply networks in extended period under the condition of unsteady hydraulic and water quality are simulated by using software EPANET2. The most dangerous nodes for injecting the contaminant into the networks to pollute the water supply system can be determine according to the location objective value obtained from simulation. Nodes with high objective value will be the most dangerous nodes. An integer coded optimal algorithm is proposed to optimize the location of sensors for detecting the contaminant, it incorporates the crossover and mutation operators of genetic algorithm in the basic particle swarm optimization algorithm and the corresponding computational program is developed. An example of application is presented. The normalized indexes of average coordinates of optimized nodes for sensor are given, and the indexes are used to measure the correctness of the location for installing sensors. The cumulative distribution functions of possible sensor locations under different contaminant injection scenarios with various injection starting moments, injection durations and contaminant mass injection rates are calculated to help determine the locations of sensors.