基于非参数核密度估计的风光水火储系统灵活性评估方法研究OA

With the rising penetration of new energy,uncertainties on both generation and load sides pose significant risks to power system stability.To scientifically assess the flexibility of a novel multi-source coupled power system(integrating wind,solar,thermal,hydro and energy storage),a collaborative analysis framework is proposed,combining interval estimation of bilateral generation-load uncertainties with stochastic production simulation.First,non-parametric kernel density estimation generates confidence intervals for new energy output and load,and extreme supply-demand scenarios are constructed to quantify such uncertainties.Second,via a hierarchical dispatching strategy,wind,photovoltaic and run-of-river hydropower are prioritized as equivalent negative loads.Considering system ramping constraints,an improved stochastic production simulation algorithm schedules thermal power unit output.Finally,reservoir-type hydropower under-takes remaining system load.In case of load shedding or new energy curtailment,energy storage devices regulate the system through charging and discharging.Case studies show non-parametric estimation effectively characterizes bilateral generation-load uncertainties.The proportions of load shedding and new energy curtailment due to insufficient system ramping capacity are 14.8%and 91.5%,respectively,indicating ramping constraints are critical to system stability.Energy storage configuration significantly enhances regulation capacity,reducing the loss of load probability(LOLP)and new energy curtailment probability by 8.6%and 34.1%,respectively.