Optimization Of Building Distributed Energy System With Ice-storage Air-conditioning

With the rapid development of the global economy and the shortage of fossil energy,improvingenergy efficiency and protectingthe global environment problems have becomeincreasingly prominent.Under this background, attention has been widely paid to distributedenergy systems. But the investment of distributed energy system is high, and each equipmentof the system must be reasonable configured in order to play to their strengths.In addition,many areas have obvious difference between peak and valley,there is severe power shortageat the peak, while a large capacitycould not be made full use at the valley which seriouslyaffects the economicefficiency of grid.Ice-storage air-conditioning can take full advantage ofcheap electricity for icing at night,on the other hand, these ice will be used as a cold source torelease coldduring the day.Therefore, the establishment of building distributed power supplysystem with ice-storage air-conditioning, can reduce the electricity cost, which has importantpractical significance.In this paper, building energy consumption of large buildings as well as their coolingpower load in a city in Guangdong province were investigated.According to theirpower loadcharacteristics, the buildingswere divided into two groups: continuous load constructions andintermittent load constructions.And according to the importance of the load, the intermittentload constructionscould be subdivided into important load and unimportant load.Buildingenergy consumption per unit area，terminal power consumption and the typical days’ coolingload of each seasonof these three kinds of constructions were analyzed.In order to realize the economical operation of building distributed energy system, thebi-leveloptimization model of building distributed energy system with ice-storageair-conditioning was set up. Lower layer is the dispatching operation model based on mixedinteger programming algorithm while the upper layer using the particle swarm algorithm tofind optimal equipment configuration capacity, with the optimization target of shortestincremental payback period.Upper layer passedequipment type and capacity to the lower layer,lower layer used the minimum daily operation cost as the optimizationtarget, and thenrelatedtarget was used as the fitness of a particle swarm optimization (PSO) to return toupperlayer. The optimal investment payback period and equipment capacity and operating strategy weregained after layer upon layer evolution finally.Using the above model, under the condition of current market electricity price andnatural gas price, distributed energy system of three kinds of buildingswere optimizedrespectively, the capacity and operation solutionof all the typical architecture of buildingdistributed energy system with ice-storage air-conditioning were gained. Aiming at eachtypical buildings,contrastive analysis on economic efficiency between the distributed energysystem optimization configuration solution and traditional distributed sub-system ofdistributed energy system without ice-storage air-conditioning was put forward. Effect onincremental investment payback period and distributed energy system configuration capacitydue to the change of construction area, cold power ratio and important load coefficient hadbeen researched.Research shows that: the reasonable and efficient configuration of buildingdistributed energy system with ice-storage air-conditioning will make a big contribution tobringing economic benefit, avoiding the peak time, improving the environment protection.