Environmental Economic Dispatch Of Power System With Wind Power Based On Multi-Objective Optimization Algorithm

Power system is one of the most complex engineering systems in the world,and its dispatching problem has been the focus of many scholars’ research.Scientific and reasonable scheduling methods can effectively reduce the operating costs of power system.In the traditional power dispatching methods,the economic cost is usually taken as the dispatching objective.However,with the increasing shortage of energy and the increasingly serious environmental problems,this method is difficult to meet the current requirements of lowcarbon environmental protection.The environmental economic dispatching(EED)of power system,at present,has been a research hotspot of this field,this method takes the pollution emission and the economic cost as the dispatching objective simultaneously,which not only saves the cost,but also can protect the environment effectively.Most of the power plants in the world today still use coal and other fossil fuels to generate electricity,the use of such fuels will produce a large amount of harmful gases and have great harm to the environment.Therefore,many scholars have turned their eyes to wind energy and other green energy.The biggest advantage of wind power is energy saving and environmental protection,without any pollutant emissions,which is very consistent with the current "green and low carbon" concept.Based on this,this thesis carried out related research on static and dynamic dispatching of power system with wind power,and the specific work is as follows:(1)Aiming at static and dynamic dispatching problems of power system with wind power,the original optimal dispatching model was improved.The valve point effect is added to the original economic cost and the rotation reserve constraint is taken into account.In case of system failure or system power shortage due to the randomness and volatility of wind power,the rotating reserve capacity is utilized to ensure that the power system can supply power to users normally.At the same time,the scheduling model in this thesis also takes into account the network loss,climbing constraints,etc.,which makes the problem model more consistent with the actual situation.(2)An improved multi-objective evolutionary algorithm based on decomposition is proposed for static environmental economic dispatching(SEED)of power system with wind power.The algorithm combines a better constraint processing technique to ensure that the population can fully explore the target space.In this thesis,SEED is used to reasonably distribute the output of each thermal power unit according to the load demand of the system at a certain time point.Here,all wind power would be integrated into the grid and takes into account constraints such as power balance and other aspects.The constraint handling technique of the proposed algorithm is improved,in the process of algorithm optimization,not only some quality individuals which satisfy the constraint conditions,but also some individuals with low degree constraint violation and better objective function values are selected,these individuals can affect the search direction of entire population and make the population fly in a better direction.Through the simulation experiment,the feasibility of the proposed algorithm is verified,and compared with the other algorithms,the proposed algorithm can provide a better dispatching scheme for SEED of power system with wind power.(3)In this thesis,two improved differential evolution algorithms are proposed for dynamic environmental economic dispatch(DEED)of power systems with wind power.Compared with SEED,DEED is a more complex multi-objective optimization problem with more complex constraints to be considered,such as power balance constraint,climbing constraint and so on.The first proposed algorithm combines two selection strategies on the basis of the differential evolution algorithm.Due to the differences in the proportion of the feasible region to the whole search space,the search process and the problem itself,different selection strategies have different effects.Using two selection strategies can make the final result have better diversity.The second algorithm adopts the elite selection strategy to ensure the quality of the population,and incorporates the close neighbor mobility strategy to compensate for the weak local search ability of the differential evolution strategy.Through the simulation experiment,the results show that the two algorithms have strong ability to solve the problem of DEED.By comparing with other algorithms,we can see that the proposed algorithm has certain advantages in both economic cost and pollution discharge.At the same time,the experimental results show that the addition of wind power can save the operating cost of the power system,and can better alleviate the environmental pressure effectively.