Short-Term Load Forecasting of Distributed Energy System Based on Kernel Principal Component Analysis and KELM Optimized by Fireworks Algorithm

Accurate and stable load forecasting has great significance to ensure the safe operation of distributed energy system. For the purpose of improving the accuracy and stability of distributed energy system load forecasting, a forecasting model in view of kernel principal component analysis (KPCA), kernel extreme learning machine (KELM) and fireworks algorithm (FWA) is proposed. First, KPCA modal is used to reduce the dimension of the feature, thus redundant input samples are merged. Next, FWA is employed to optimize the parameters C and σ of KELM. Lastly, the load forecasting modal of KPCA-FWA-KELM is established. The relevant data of a distributed energy system in Beijing, China, is selected for training test to verify the effectiveness of the proposed method. The results show that the new hybrid KPCA-FWA-KELM method has superior performance, robustness and versatility in load prediction of distributed energy systems.

An expansion planning method for extending distributed energy system lifespan with energy storage systems

The recent advances in the modern power grids, such as growing energy demand and penetration of higher amounts of distributed energy generators like renewable energy resources, caused additional grid integration challenges for the distributed energy system operators. Besides, deep electrification impacts triggered by a growing share of electric vehicles as additional electric loads made it essential for the distributed energy system operators to re-investigate their upgrade plans in terms of distributed energy system lines and corresponding infrastructure investments. An energy storage system offers the opportunity to use energy flexibly, resulting in deferring the inevitable upgrade costs of the distribution grid elements and increasing the power quality. In this study, a new method is proposed to extend the lifespan of distributed energy systems with an energy storage system and reduce line upgrade costs. The proposed method is tested on the IEEE-33 with different case studies. The findings of this study indicated that the investigated energy storage option has a positive impact on the distributed energy system components and assets in terms of extending their lifespan and helping to mitigate growing demand peaks because of the load increase. According to the results, the proposed method reduces the total cost by up to 66%. Furthermore, the power losses are reduced by an average of 34.8%, and the voltage profiles are improved with the energy storage system.