Study On The In-island And Island-island Integrated Scheduling Strategy Of Energy Supply System Of Pelagic Island Group

As the fulcrum and platform for the development of ocean,pelagic islands,which play important roles in the overall ocean strategy of our country,contain a large number of exploitable resources.However,because of far away from the mainland,the supply of resources on the mainland alone can not fully meet all kinds of energy needs of pelagic islands.On the other hand,because of the limited area of pelagic islands,it is difficult to be equipped with large-scale power generation equipment for renewable energy,resulting in a certain inconsistency and difference between the enewable energy and load demand of each island.Considering that there is much demand for multiple energy production and use of the tourism oriented load center island,it will bring a lot of pressure to the supply to all kinds of energies.If the pelagic island group can be divided into the rich-resource islands with high renewable energy generation and the load center islands with large load integration,by coupling and storage of multiple energies,the local consumption of wind power and photovoltaic can be promoted.Besides,the supply of all kinds of energies raise and the pressure is released.In many cases,pelagic islands are scattered and far away from each other,so the traditional power transmission mode such as submarine or overhead cable may not be feasible and economic.As a result,there is a new energy transfer mode for pelagic islands to transfer and collect energy between islands by storage and exchange vessels.However,if the number of exclusive storage and exchange vessels is not enough,there will be surplus electricity on rich-resource islands and inadequate electricity on load-center islands,which not only goes against the full utilization of clean energy power,but also increases the cost of power supply.On this condition,the sharing transitting electric vessels which are used to meet the demand of passenger and freight transportation between the islands every day can play an important role in improving the energy supply economy of pelagic islands.In response to above challenge and requirement,firstly,this thesis proposes the model of six-energy(electricity,water,hydrogen,gas,cold and hot)load center island self-consistent system with supply and demand and divide it into supplement side,conversion side,and load side based on the conception of energy hub.Also,for the supply side,the models of wind and photovoltaic power generation devices and generation energy conversion devices for water and hydrogen are built,which lays an important theoretical foundation for day-ahead scheduling of the system later.Moreover,based on the polymorphic energy self-consistent system with supply and demand for load center islands,the day-ahead optimization scheduling model is established by considering the total cost of purchasing energy from the external network in a whole day as the objective function and the constraint conditions of each part.Then,comparing with coupling reduced and electric storage alone case in the simulation,the necessity of polymorphic energy coupling and storage medium are validated;In the meantime,the impact of the price of each kind of energy on energy coupling is analyzed.It is proved that the proposed model can increase the consumption of renewable energy and decrease the total cost of purchasing energies.Finally,based on the idea of shared economy,this thesis proposes the concept of Sharing Transit Electric Vessel(STEV)with both transportation and energy transport functions,and designs surplus energy collection strategy based on STEV: aiming at collecting maximum net total power of STEV,and taking into account the constraints of returning time,capacity of storage battery and charging power,the optimal scheduling strategy is solved by using particle swarm optimization algorithm twice.And then,the model and simulation is made based on the actual geographic location and the wind and photovoltaic output data of pelagic islands,validating the rationality of the proposed strategy and the effectiveness and superiority of using particle swarm optimization algorithm twice.