A run-off algorithm based approach for optimal operation of a DCCHP system

A new optimization algorithm, named run-off algorithm, is proposed in this paper to solve the nonlinear, nonconvex and often discontinuous optimization problems. The algorithm a kind of modern heuristic algorithm and has advantages of low randomness and high accuracy. Comparing with standard optimization algorithms such as gradient descent, its main characteristic is no need of functions and variables to be continuous and differentiable, so it is suitable for solving discrete and multidimensional problem. In order to get more convincing results, it should compare with other heuristic algorithms. It has similar shortage with current heuristic algorithms but has better performance. Therefore, it is applied to solving optimal dispatching problem of distributed combined cool, heat and power (DCCHP) system. The carbon equivalent conversion coefficient is proposed for actualizing the conversion between different pollution emissions, and the environmental cost model is further simplified by equivalent transformation between the SO2, NOx and CO2 emissions. The simulation result shows that compared with genetic algorithm and standard particle swarm algorithm, run-off algorithm can get optimization solution better, faster and more stable than others. Meanwhile, optimization result proves the feasibility and superiority of this algorithm in solving such problems.