Dalian University of Technology

Jianjian Shen

Chuntian Cheng

Congtong Zhang

Yue Wang

Wenjing Niu

Shanzong Li

Nannan Zhang

Sen Wang

Qianqian Shen

Lifei Sun

Chengguo Su

Rui Cao

Binbin Zhou

Guangze Chen

Juntao Zhang

Lin Hu

The present invention belongs to the field of power system operations and provides a method for quantifying the flexibility demand and coordinating optimization of a hydro-wind-solar multi-energy complementary system. Firstly, the flexibility demand quantification method considering the uncertainty of wind and solar power output is constructed, and the wind and solar power output interval is divided by using quantile points to generate a set of output scenarios, and then the flexibility demand under each scenario is calculated. Based on the quantitative index of flexibility demand, an optimal operation model of hydro-wind-solar complementary system considering the minimum expectation of system flexibility deficiency is constructed to realize the optimal calculation of hydro-wind-solar complementary. By utilizing an actual wind-hydro complementary system of the Yunnan Power Grid, the model is validated for different new energy access ratios. The results show that the method of the present invention can give a complementary operation and scheduling scheme for multiple types of power sources under different conditions, effectively meet the flexibility demand of the system, reduce the abandoned power and improve the level of clean energy integration.

Method for quantification of flexibility requirements and coordinated optimization of a hydro-wind-solar multi-energy complementary systems

A practical method for short-term operations of large-scale hydropower plants divides all hydropower plants into three categories using operation characteristics such as system hierarchy, space attributes, task requirements, and schedule particularity. A strategy for adjusting spillage based on peak-shaving response and a strategy for equal load reduction in off-peak hours check and adjust power generation of hydropower plants with specified dispatching modes. For medium- and small-sized cascaded hydropower plants, the load distribution among plants is optimized with an objective of minimizing total power release subject to control condition of total generation profile. For large-size cascaded hydropower plants, an optimization model for peak-shaving operations and a method for balancing power plants with equal load rate are combined to respond to system peak demands and guarantee power balance in all periods.

Practical method for short-term operations of super large-scale hydropower plants

The invention relates to a multi-objective optimization method for power system peak-shaving based on index linkage analysis. The invention comprehensively considers five peak shaving indexes, and introduces a linkage analysis theory in economics to test stationarity and causality of data series of peak-shaving indexes. The purpose is to effectively clarify linkage relationship between indexes. A regression analysis method is used to quantify the mutual influence relationship. A multi-index coupling peak shaving optimization model for generation scheduling is developed and finally solved by using genetic algorithm. The invention can objectively describe comprehensive peak shaving requirements of a provincial power grid, and is helpful for generation dispatcher to reduce subjective assumptions in the decision-making. Compared with a conventional single-index peak-shaving model, peak-shaving effect of our method is obviously improved, which provides a novel technical way for peak-shaving generation scheduling and decision-making in short-term operations of power systems.

Multi-objective optimization method for power system peak-shaving based on index linkage analysis

The invention relates to the field of hydropower scheduling, and relates to a method for multi-objective optimal operations of cascade hydropower plants based on relative target proximity and marginal analysis principle. The invention constructs an optimization model with relative target proximity by introducing positive and negative ideal points of objectives so that a multi-objective optimization is efficiently handled. A strategy for processing complex operation constraints is proposed and coupled with genetic algorithm to solve the model. Thus, optimal solution sets under different weight coefficients of objectives can be determined. Following this, marginal benefit and marginal cost are introduced to represent a relationship between multiple objective values and corresponding weight coefficients. According to principle of profit maximization in economics, a marginal analysis of objective weight coefficient is finally made to determine benefit-dominant area, cost-dominant area and equilibrium area, and there by obtaining a basis of multi-objective decision-making.

Method for multi-objective optimal operations of cascade hydropower plants based on relative target proximity and marginal analysis principle

The invention relates to the field of hydropower scheduling, and relates to a method for short-term generation scheduling of cascade hydropower plants coupling cluster analysis and decision tree. Linear regression technique is adopted to determine a matching relationship of energy production between upstream and downstream hydropower plants. With the relationship, typical generation curves of each hydropower plant can be clustered from lots of historical data. These typical generation curves and impact factors of generation scheduling such as planned daily electricity, reservoir level, and power grid characteristics, are together trained to obtain decision-making library for generation scheduling of cascaded hydropower plants. Thus, the decision tree method can be used to rapidly determine an operational scheme for generation scheduling of cascaded hydropower plants. Finally, a correction strategy for operation constraints is introduced to ensure feasibility of the operation scheme. The invention can quickly obtain generation schedules of cascade hydropower plants.

Method for short-term generation scheduling of cascade hydropower plants coupling cluster analysis and decision tree

The invention that relates to the field of hydropower scheduling presents a method for long-tens optimal operations of interprovincial hydropower system considering peak-shaving demands. It can take full advantage of the differences of hydrological characteristics among hydropower plants on different rivers to implement compensation operations of interprovincial hydropower system. In this operation, typical daily load demands during dry season are considered to optimize the allocation of hydropower production over one year. The purpose is to increase the dispatchable generation capacity for peak demands of power grids. The technology scheme of the invention can be summarized as follows. A multi-objective model of hydropower system operations is established with maximizing generation production and minimizing the difference rate between peak and valley load during dry period. The difference of hydrological characteristics and regulation performance between rivers and plants are utilized to divide all power plants into several groups and their calculation order. A hybrid algorithm that integrating progressive optimality algorithm and discrete differential dynamic programming is presented to optimize monthly reservoir levels of hydropower plants. During optimization, a load reconstruction-based strategy is used to handle time-coupled network security constraints so that feasible hourly generation schedules far peak-shaving are easily obtained. An iterative procedure is executed to obtain the optimal monthly generation schedules and hourly power curves at the typical day of each month. The invention can make full use of the compensation operation characteristics of hydropower plants to meet the demands of coordinating monthly generation production and daily peak power. It is capable of providing the support for interprovincial power transmission and joint operations of China's huge hydropower plants such as Xiluodu and Jinping.

Growing community of inventors

Dalian, China

Jianjian Shen