In the optimization of mass exchange networks with mass transfer load as the optimization variable, using the penalty function method to deal with infeasible solutions that violate the feasible constraints on mass transfer will limit the generation of mass transfer units, and at the same time bring negative effects on the optimization algorithm's optimization path. In view of this, the negative impact of the penalty function method to deal with mass transfer constraints on optimization is analyzed, based on which a dynamic regulation strategy of mass transfer load is proposed to deal with the units mass transfer constraints by using different regulation methods, attenuating the mass transfer load of the units that violate the mass transfer constraints or eliminating the unit to ensure that the mass transfer units in the structure not violate the constraints. The validation is carried out by two mass exchange network arithmetic examples, and the obtained results demonstrate the effectiveness of the strategy by decreasing 2 943 ＄·a^-1 and 1 697 ＄·a^-1, respectively, compared with the optimal results in the literature, and increasing the number of mass transfer units in the structure.

In order to solve the configuration optimization problem of isolated micro-grid, wind driven generator, photovoltaic, diesel generator and energy storage battery optimization model described in the form of energy flow matching is established, which can flexibly form the node connection relation representing the output of equipment at each time. At the same time, in view of the precocious convergence of swarm intelligence algorithm applied to optimal configuration of micro-grid, a random walk optimization algorithm suitable for optimal configuration of micro-grid is proposed. Guided by reducing the annual comprehensive cost of the system, the algorithm realizes synchronous optimization of continuous variable (equipment output) and integer variable (equipment quantity) by randomly increasing or decreasing the hourly output of equipment. By accepting the differential solution mechanism, the algorithm has the ability to jump out of the local optimal solution and better take into account the global search and local search in the capacity optimization process of micro-grid. Applying the random walk algorithm to the simulation example, the annual comprehensive cost is 552 826.39 yuan. Compared with particle swarm optimization algorithm, a better result is obtained. The superiority of the algorithm in optimization accuracy is verified.

A chessboard model of mass exchange networks (CBM-MEN) is proposed. The CBM-MEN has characteristics of compact structure, simple expression, and flexible stream arrangement. A phase of eliminating mass exchanger is added to a random walk algorithm with compulsive evolution. The algorithm is combined with the chessboard model. During optimization process, the mass exchange load is used as an optimization variable. Finally, the simultaneous optimization method is applied to two cases, recovery of copper from liquid effluents of an etching plant and dephenolization of aqueous wastes. The total annual cost of optimized structures is decreased by 5.8‰ and 1.6‰, respectively. It shows that the method has good search domain and search capability.