Research On Optimal Dispatching Of Wind-photovoltaic-thermal And Energy Storage Considering Deep Peaking And Wind And Photovoltaic Power Uncertainty

The transformation of energy structure has led to the rapid development of renewable energy,but the large-scale grid connection of wind power and photovoltaic power generation has also put forward higher requirements for the power system.The increasing scale of wind and photovoltaic grid connection has posed a serious challenge to system peaking,while thermal power peaking as China’s traditional peaking method has been unable to meet the needs of new energy consumption.The volatility and uncertainty of wind power and photovoltaic power output not only increases the difficulty of new energy consumption,but also poses a hidden danger to the safety of the system.Therefore,improving the peak regulation capacity of power system and reducing the forecast error of wind power and photovoltaic power output is the key to solve the above problems,and it has important research significance to promote the grid consumption of high percentage of new energy and improve the reliability of power system.In this thesis,we address the above issues from two aspects of joint peaking and optimal scheduling of multi-energy complementary.First,the system structure and operation principle of wind power and photovoltaic power generation are introduced,mathematical models are established respectively,and their output characteristics are briefly analyzed.Based on the response characteristics of different energy storage systems and combined with the demand for energy storage power plants in this thesis,The Li Fe PO4 battery is chosen as the energy storage unit and the energy storage charging and discharging model is established.The classification and characteristics of demand response are introduced,and it is divided into PDR and IDR according to different driving methods,and different mathematical models are established.The above-mentioned content lays the theoretical foundation for the subsequent research.Secondly,a peaking cost model is established,and a joint peaking model of windphotovoltaic-thermal and energy storage is constructed by combining the source,load and storage mathematical models.Considering the initiative of thermal power peaking,peaking initiative modeling is added to fully motivate each power generation entity to participate in deep peaking on the basis of ensuring that they receive peaking benefits.Using time-of-use tariffs to reduce the peak-to-valley load difference,and considering the limited ability of timeof-use tariffs to regulate short-term loads,adding interruptible loads to speed up customer response,further flatten the load curve,and relieve the system’s peak regulation pressure.To enhance the peaking depth of thermal power units,the wind and light abandonment rate is added as the objective function based on the total operating cost and solved using NSGAII algorithm.The calculation results show that the peaking capacity of the power system is improved from source,load and storage,which improves the flexibility of system peaking,promotes the gridconnected consumption of wind and photovoltaic and improves the stability of the system.Finally,considering the influence of wind and photovoltaic power uncertainty,a scenario analysis method considering temporal correlation is proposed.In the scene generation stage,the original wind and photovoltaic scenes with temporal correlation are generated using inverse transform sampling and multivariate normal distribution.In the scene reduction stage,the computation time is too long because the k-means clustering algorithm weakens the representation of wind and photovoltaic joint scenes,and the SBR method requires continuous traversal of the original scene set.A small number of wind and photovoltaic independent scenes are obtained after the initial reduction of the original scenes using the k-means clustering algorithm,and the wind and photovoltaic joint scenes are finally obtained by the secondary reduction using SBR method.The results show that the scenario analysis method can better characterize the wind and photovoltaic power generation actual output and reduce the impact of prediction errors on the scheduling results.Since the scenario analysis method ignores the influence of small probability scenarios on the error,the scenario analysis method is based on the introduction of boundary scenarios containing wind and photovoltaic power prediction errors,and considering the load cutting phenomenon of the boundary scenarios,a windphotovoltaic-thermal and energy storage optimal scheduling model considering the reserve capacity constraint of the boundary scenarios is established.The results of the algorithm show that the model reduces the risk of load shedding,improves the operational reliability of the system,and enhances the wind and photovoltaic utilization by increasing the sensitivity of the total open capacity.