Joint configuration optimization strategy of unstable power supply and energy storage for offshore oil and gas platforms
Aiming at the joint configuration of offshore oil and gas platform cluster access to unstable power supply and energy storage,combined with the characteristics of offshore wind power and photovoltaic and existing topology,this paper proposes a staged joint configuration strategy of wind turbine/photovoltaic/energy storage and introduces the staged particle swarm optimization embedded in power flow calculation.In the first stage,the prediction model of LightGBM is applied to obtain the time series prediction power generation of wind turbine/photovoltaic,and then the wind turbine/photovoltaic capacity of each node is optimized with the goal of investment and construction economy and power flow stability.In the second stage,a cluster division method based on voltage and loss sensitivity is proposed for the distribution network with an unstable power supply configuration.The distribution network cluster is divided into several sub-clusters.In the third stage,according to the divided sub-clusters,energy storage capacity,distribution network loss,and node voltage fluctuation are configured for each subcluster in terms of energy storage.Taking a real 10 kV distribution network of oil and gas platform in Bohai sea as an example,two schemes of customized gas turbine output and customized economy are set up to verify the rationality of the joint configuration optimization strategies.The results indicate that both configuration strategies can effectively improve the flow stability of offshore oil and gas platform distribution networks and increase the penetration rate of new energy.This study verifies the feasibility of offshore decentralized wind turbine/photovoltaic power generation projects,which is beneficial for achieving zero carbon construction of offshore oil and gas platforms in the future.
offshore oil and gas platformswind powerphotovoltaicenergy storageoptimization strategysubcluster divisionsensitivity indexzero carbon
万方数据
维普
