Research On The Equipment Room Intelligent PID Temperature Control For Base Stations Energy-saving

Communications industry not only has great potential on energy-saving and reducing consumption, but also is a powerful pushing hand for highly effective energy-saving in the whole society. Communication base station with characteristics of many sites, long line and wide coverage is the key to save energy in the communications network, which takes up about70%of the total energy consumption in communications industry; Base stations room is an enclosed space which assembled the wireless communication equipments and auxiliary equipments. At present, the room’s temperature is kept between24-26℃mainly by high-power industrial air-conditioner constantly running24hours, which consumed more than40%of the total power consumption of the room. Therefore, accomplishing the precise control of temperature of base stations room can not noly ensure normal operation of communication equipments and extend battery lifecycles, but also reduce frequent start-stop and running time of air-conditioner to save basic consumption in base stations. It can provide technical guarantee to energy-saving and sustainable development of communications enterprises.Currently, the room temperature control system adopts dynamic extensive regulation of simple control strategy. Controlled object has complex system characteristics such as large inertia, pure time-delay and uncertainty disturbance, and classic PID temperature control system exists difficulties in tuning parameters. Therefore, a thought of carrying out energy-saving through controlling base stations room temperature accurately and intelligently was proposed based on summarizing communications industry energy consumption status and energy-saving technical measures systematically. After described the basic theory and general improved principles of Particle Swarm Optimization (PSO) algorithm, an improved Particle Swarm Optimization algorithm based on Two-subpopulation (TS-IPSO) is proposed. Without increasing the size of particle swarm, this algorithm introduces the two-subpopulation (main subpopulation particle swarm and assistant subpopulation particle swarm, which search direction are inversed completely) to cooperative search, extending the search range, also adopts the crossbreeding mechanism in genetic algorithm, and uses non-linear inertia weight reduction strategy. Finally, the improved PSO (TS-IPSO) is applied in tuning process of PID controller parameters. And the specific algorithm for optimization of the controller parameter tuning is designed.The simulation results using simplified room temperature control model show that TS-IPSO PID control algorithm can meet the requirement of controlling the temperature accurately of base room; The TS-IPSO PID control algorithm is superior to SPSO and fuzzy PID control algorithm on the performances such as speed response, steady precision and anti-interference, which has strong robustness and can achieve a certain degree of base stations room energy-saving.