Non-dominated sorting culture differential evolution algorithm for multi-objective optimal operation of Wind-Solar-Hydro complementary power generation system

Due to the intermittency and instability of Wind-Solar energy and easy compensation of hydropower, this study proposes a Wind-Solar-Hydro power optimal scheduling model. This model is aimed at maximizing the total system power generation and the minimum ten-day joint output. To effectively optimize the multi-objective model, a new algorithm named non-dominated sorting culture differential evolution algorithm(NSCDE) is proposed. The feasibility of NSCDE was verified through several well-known benchmark problems. It was then applied to the Jinping Wind-Solar-Hydro complementary power generation system. The results demonstrate that NSCDE can provide decision makers a series of optimized scheduling schemes.

PSO-BP-Based Optimal Allocation Model for Complementary Generation Capacity of the Photovoltaic Power Station

To improve the operation efficiency of the photovoltaic power station complementary power generation system,an optimal allocation model of the photovoltaic power station complementary power generation capacity based on PSO-BP is proposed.Particle Swarm Optimization and BP neural network are used to establish the forecasting model,the Markov chain model is used to correct the forecasting error of the model,and the weighted fitting method is used to forecast the annual load curve,to complete the optimal allocation of complementary generating capacity of photovoltaic power stations.The experimental results show that thismethod reduces the average loss of photovoltaic output prediction,improves the prediction accuracy and recall rate of photovoltaic output prediction,and ensures the effective operation of the power system.

CVaR-based Reserve Optimization for Isolated Multi-energy Complementary Generation Systems in Mixed Time Scale

With the rapid growth of photovoltaic integration,the volatility and uncertainty of intermittent photovoltaic injection will dramatically reduce system operation reliability from the generation side.The system operator may face certain financial risks brought by unexpected power failure under low operation reliability.Therefore,maintaining sufficient power reserve to meet system operation reliability and reduce risk,especially in an isolated system,is essential.However,the traditional reserve preparation strategy fails to consider the uncertainties of the power generation under the high penetration levels of emerging renewable energy resources.A novel reserve preparation strategy for an isolated system is developed in this paper using a twostage model.In the first stage,the optimal hourly scheduling of an isolated system is determined.In the second stage,a minute level conditional value-at-risk(CVaR)based model is established where the uncertainty of the reserve requirement is introduced with the chance constraint.The proposed discretized step transformation(DST)and subtraction type convolution(STC)methods are utilized to convert the model into mixedinteger linear programming,and finally solved by applying the CPLEX solver.The IEEE 39-bus system is used as the test case to validate the feasibility and effectiveness of the proposed two-stage model.

Coordinative Optimization of Hydro-photovoltaic-wind-battery Complementary Power Stations

The depletion of fossil energy and the deterioration of the ecological environment have severely restricted the development of the power industry.Therefore,it is extremely urgent to transform energy production methods and vigorously develop renewable energy sources.It is therefore important to ensure the stability and operation of a large multi-energy complementary system,and provide theoretical support for the world’s largest single complementary demonstration project with hydro-wind-PV power-battery storage in Qinghai Province.Considering all the multiple power supply constraints,an optimization scheduling model is established with the objective of minimizing the volatility of output power.As particle swarm optimization(PSO)has a problem of premature convergence and slow convergence in the latter half,combined with niche technology in evolution,a niche particle swarm optimization(NPSO)is proposed to determine the optimal solution of the model.Finally,the multiple stations’coordinated operation is analyzed taking the example of 10 million kilowatt complementary power stations with hydropower,wind power,PV power,and battery storage in the Yellow River Company Hainan prefecture.The case verifies the rationality and feasibility of the model.It shows that complementary operations can improve the utilization rate of renewable energy and reduce the impact of wind and PV power’s volatility on the power grid.

Power Source Flexibility Margin Quantification Method for Multi-energy Power Systems Based on Blind Number Theory

The grid connection of a high proportion of re-newable energy generation increases the uncertainty in power systems.Therefore,the flexibility margin of different energy sources needs to be quantified to cope with the uncertainty change and maintain the dynamic balance of power system flexibility.In this paper,first,the flexibility characteristics of source,net,load and power and load community(PLC)are analyzed.The dynamic equilibrium relationship among them is briefly introduced.Secondly,taking into full consideration the complex output characteristics of different energy sources and combining their respective flexibility characteristics,a quantitative model of the power source flexibility margin for thermal power,hydro-power,gas power and concentrating solar power is established.A quantitative model for a power source flexibility margin in PV and wind power based on blind number theory is estab-lished.Furthermore,the calculation method of theoretical power generation capacity,which can reflect different characteristics of output power of various energy sources,is presented.The actual output power of each power source in each period is predicted.Finally,a case study shows that the model and method can consider the operating characteristics of different types of power sources,and quickly and accurately quantify the adjustable range of flexibility margins of each power source at different periods of time,which can provide an important basis for evaluating the capacity of renewable energy consumption and the optimal operation of multi-energy power systems(MEPSs).