风光储联合发电系统储能优化控制研究
发布时间：2018-08-01 19:06
【摘要】：近些年来，随着化石能源的枯竭，以风能和太阳能为主的新能源得到大力的发展。风能和太阳能不仅资源丰富用之不竭，而且对无污染。但是，风能和太阳能具有随机性、间歇性和不确定性，导致风光出力具有波动性。随着风电和光伏发电在电网中所占的比例逐渐增加，并网之后，势必会严重影响电网的发展。为了解决新能源接入带来的问题，把储能装置加入风电场和光伏电站形成风光储联合发电系统是解决可再生能源发展的重要途径。为了实现新能源的友好接入，风光储联合发电系统必须具有可调度性，所以，本文提前一天对以蓄电池为主的储能装置进行了优化控制研究。具体研究内容如下： 1、首先，对风光储联合发电系统的基本结构和工作原理进行了介绍，了解了整个系统工作原理和过程。重点研究了以蓄电池为代表的储能系统的工作特性，包括荷电状态、放电深度以及每个时段电量的推导公式，这些对储能的控制和寿命有重要的影响。其次，介绍了风力发电和光伏发电的预测方法，并分析了风光预测存在误差，以及现有文献中对预测误差的处理。 2、针对风光预测出力的误差具有随机性，本文采用机会约束规划对储能进行优化控制。该方法以储能装置的功率和电量为约束条件，，以风光储总出力曲线与给定的计划出力曲线的余弦相似度为目标函数，使用基于随机模拟的粒子群算法求解，得到两条曲线最接近时对应的储能充放电功率。算例分析表明，所提出的储能优化控制策略能够使风光储发电系统的总出力跟踪计划出力曲线。 3、针对风光预测出力的误差具有模糊性，本文采用模糊相关机会规划对储能进行优化控制。该方法以储能装置的功率和电量为约束条件，每个时段的匹配程度用可信度表示，以一天内96个时段总的可信度均值最大为目标，使用基于模糊模拟的遗传算法求解，得到可信度均值最大时不同时段对应的储能充放电功率。最后，算例表明，所提出的储能优化控制策略能够使风光储联合发电系统总出力最大程度的跟踪计划出力曲线。
[Abstract]:In recent years, with the depletion of fossil energy, new energy, mainly wind energy and solar energy, has been greatly developed. Wind and solar energy are not only rich in resources, but also non-polluting. However, wind and solar are random, intermittent and uncertain, resulting in volatility of wind power. With the increasing proportion of wind power and photovoltaic power generation in power grid, the development of power grid will be seriously affected after grid connection. In order to solve the problem caused by new energy access, it is an important way to solve the problem of renewable energy development by adding energy storage equipment to wind farm and photovoltaic power station to form wind energy storage combined generation system. In order to realize the friendly connection of new energy, the combined generation system of solar energy storage and storage must be schedulable. Therefore, the optimal control of the energy storage device based on storage battery is studied one day in advance in this paper. The main contents of this paper are as follows: 1. Firstly, the basic structure and working principle of the wind energy storage combined generation system are introduced, and the working principle and process of the whole system are understood. The working characteristics of the energy storage system represented by the storage battery are mainly studied, including the charge state, discharge depth and the formula of the electric quantity in each period, which have an important influence on the control and life of the storage energy. Secondly, the forecasting methods of wind power generation and photovoltaic power generation are introduced. In this paper, the opportunity-constrained programming is used to optimize the control of energy storage. In this method, the power and electricity of the energy storage device are taken as the constraint conditions, and the cosine similarity between the total wind force curve and the given planned force curve is taken as the objective function, and the particle swarm optimization algorithm based on stochastic simulation is used to solve the problem. The charge and discharge power of energy storage is obtained when the two curves are closest to each other. The analysis of an example shows that the proposed optimal control strategy of energy storage can make the total output of the wind energy storage power generation system track the planned output curve. 3. The error of forecasting the wind energy is fuzzy. In this paper, fuzzy correlation opportunity programming is used to optimize the control of energy storage. In this method, the power and electricity of the energy storage device are taken as the constraint conditions, the matching degree of each time period is expressed by the confidence level, and the maximum mean of the total reliability of the 96 periods of the day is taken as the goal, and the genetic algorithm based on fuzzy simulation is used to solve the problem. The energy storage charge and discharge power corresponding to different periods of time is obtained when the confidence average is maximum. Finally, an example shows that the proposed optimal control strategy of energy storage can make the maximum total output of the wind energy storage combined generation system to track the planned output curve.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM61
本文编号：2158543
[Abstract]:In recent years, with the depletion of fossil energy, new energy, mainly wind energy and solar energy, has been greatly developed. Wind and solar energy are not only rich in resources, but also non-polluting. However, wind and solar are random, intermittent and uncertain, resulting in volatility of wind power. With the increasing proportion of wind power and photovoltaic power generation in power grid, the development of power grid will be seriously affected after grid connection. In order to solve the problem caused by new energy access, it is an important way to solve the problem of renewable energy development by adding energy storage equipment to wind farm and photovoltaic power station to form wind energy storage combined generation system. In order to realize the friendly connection of new energy, the combined generation system of solar energy storage and storage must be schedulable. Therefore, the optimal control of the energy storage device based on storage battery is studied one day in advance in this paper. The main contents of this paper are as follows: 1. Firstly, the basic structure and working principle of the wind energy storage combined generation system are introduced, and the working principle and process of the whole system are understood. The working characteristics of the energy storage system represented by the storage battery are mainly studied, including the charge state, discharge depth and the formula of the electric quantity in each period, which have an important influence on the control and life of the storage energy. Secondly, the forecasting methods of wind power generation and photovoltaic power generation are introduced. In this paper, the opportunity-constrained programming is used to optimize the control of energy storage. In this method, the power and electricity of the energy storage device are taken as the constraint conditions, and the cosine similarity between the total wind force curve and the given planned force curve is taken as the objective function, and the particle swarm optimization algorithm based on stochastic simulation is used to solve the problem. The charge and discharge power of energy storage is obtained when the two curves are closest to each other. The analysis of an example shows that the proposed optimal control strategy of energy storage can make the total output of the wind energy storage power generation system track the planned output curve. 3. The error of forecasting the wind energy is fuzzy. In this paper, fuzzy correlation opportunity programming is used to optimize the control of energy storage. In this method, the power and electricity of the energy storage device are taken as the constraint conditions, the matching degree of each time period is expressed by the confidence level, and the maximum mean of the total reliability of the 96 periods of the day is taken as the goal, and the genetic algorithm based on fuzzy simulation is used to solve the problem. The energy storage charge and discharge power corresponding to different periods of time is obtained when the confidence average is maximum. Finally, an example shows that the proposed optimal control strategy of energy storage can make the maximum total output of the wind energy storage combined generation system to track the planned output curve.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM61
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