基于能源多类型网络构建低碳能源社区

Constructing Low Carbon Energy Community Group Based on Multi-Energy Network System

低碳社区的设计与规划必须考虑到所有可用能源网络之间的协同作用。“本地能源共同体”概念即采用单一实体同时代表能源资产的需求与管理。提出了一种创新模型,社区模型被设计为一个空间错置的能源枢纽网络,每个枢纽均有自己的电力,供热和制冷的能源需求,上述模型验证了满足区域用户能源需求最佳组合的方法,同时降低其碳排放,包括能源系统,热能和电能存储以及能源网络基础设施。采用某区域的能源需求数据为基础,以经济目标为优化目的和施加额外约束条件减少区域的碳排放两种方案以验证模型有效性。第一种方案以经济目标为唯一优化目的,主要为了最大程度地降低区域运营总成本;第二种方案主要通过施加额外约束以减少区域碳排放,从而整体上限制一次能源消耗。经测试验证,方案1可将峰值冷功率容量降低33%,方案2与方案1的成本仅相差1%,但是实现了满足经济性前提下又达到一次能源消费总量减少10%的目的。最终结果表明通过广泛使用可再生能源、能源储存,通过利用不同能源网络之间的协同作用,可以实现“低碳能源社区”。

Design and planning of low carbon cities and regions must take into account synergies among all available energy networks. The concept of "local energy community" means adopting single entities simultaneously representing energy assets requirements and management. This paper presented an innovative model which was designed as a spatially staggered energy hub network;Each hub has its own energy demand for electricity, heating and cooling;The above model verified the method to meet the best combination of energy demand of regional users, while reducing its carbon emissions, including energy systems, thermal and electric energy storage, and energy network infrastructure. Based on energy demand data of a region, two schemes was proposed to verify model validity by optimizing objectives and imposing additional constraints on regional carbon emissions based on energy demand data of regions. The first scheme takes the economic goal as the only optimization purpose, mainly to minimize the total regional operation cost;The second scheme is mainly to reduce regional carbon emissions by imposing additional constraints, so as to limit primary energy consumption as a whole. Test results show that scheme 1 reduces peak cooling power capacity by 33%,while the cost of scheme 2 and scheme 1 is only 1%,but achieves reducing 10% per cent energy consumption under economical premise. The final results indicate that "low carbon energy communities" can be achieved through extensive use of renewable energy sources, energy storage and leveraging synergies among different energy networks.