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Research On Planning Method Of Bulk Power Network Integrated With Large-scale New Energy Power Bases

Posted on:2018-07-11Degree:DoctorType:Dissertation
Country:ChinaCandidate:L GanFull Text:PDF
GTID:1312330518955393Subject:Power system and its automation
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Recently,technologies of intermittent renewable new energy generation are developing rapidly worldwide,mainly incuding wind generation and photovoltaic generation.In China,the wind generation and photovoltaic generation are developed in the mode of lage-scale exploiting and centralized grid connection.More and more large-scale new energy power bases(LNEPBs)are planned to construct in future.Many LNEPBs located remote from load centers inversely,at the weak end of the interconnected bulk power network.The planning of the matched intergration systems and sending backbone networks lags behind the development of LNEPBs.According to the demand of bulk power network development integrated with polymorphous large-scale new energy power,the methodology of transmission network planning is studied here,to deal with the unbalanced development of LNEPBs and sending networks.The study aims at developing scientific and reasonable planning methods to integrate the output of LNEPBs securely and economically,as well as to strengthen the sending network to meet the local,cross-provincial and cross-regional consumption target of LNEPBs’ output.The main research work is summarized as follows.Based on analyzing the characteristics of large-scale new energy power,systemic economic evaluation of LNEPBs integration system planning is modeled,considering the construction cost of transmission projects,compensation cost of new energy power curtailment and the benefit of transmitting new energy power.To realize the optimal economy of integration system,an integration system planning model of LNEPBs is proposed,subject to the constraints of actual grid-connected transmission projects.To solve the model efficiently,linearization methods are applied to linearize the model,including equivalent disjunctive inequalities,siting of collecting stations based on raster map,and piece-wise approximation of annual new energy power curtailment.The primal integration system planning model of LNEPBs is reformulated as a mixed integer linear programming(MILP)model,which can be solved by commercial MILP optimizers.The obtained optimial planning scheme is the global optimal solution of the MILP model.Numerical simulation shows the high performance of linearization methods and proves the feasibility andpracticability of the proposed integration system planning method of LNEPBs.Based on the above research result,a bi-level programming model is proposed to coordinating integration system planning of LNEPBs and regional transmission network planning(RTNP)within the grid-connected zone of LNEPBs.The upper level model deals with the integration system planning of LNEPBs,with the objective to minimize the overall cost of the two planning processes.The lower-level model deals with the scenario-based RTNP considering uncertain output of LNEPBs and load fluctuation,with the objective to minimizing the investment of RTNP.To add the KKT conditions of the lower-level model into the upper one,the primal bi-level model is reformulated as a single-level mathematical programming with equilibrium constraints(MPEC).To linearize the complementary constraints of the MPEC model equivalently,the primal bi-level model is remodeled as a MILP model.Numerical simulation shows the rationality and the feasibility of the proposed coordinated planning method of integration system planning of LNEPBs and RTNP.By analyzing the sensitivity index and its criterion of static voltage stability(SVS)of LNEPB grid-connected point,extreme power constraints can be obtained to transmit the collected new energy power.In the meanwhile,due to the close relation between nodal impedence and SVS constraints,a RTNP model is proposed considering the change of nodal impedence.A bi-level coordinated planning model of LNEPBs integration system and RTNP is proposed considering SVS constraints.The upper integration system planning model takes the extreme transmitting power constraints into account considering SVS constraints,and the lower RTNP model takes the change of nodal impedence into account.Similar to the solving method of bi-level model in the previous research,the bi-level coordinated planning model considering SVS constraints is reformulated as a single-level MILP model.Numerical simulation shows the rationality of considering SVS in coordinating integration system planning of LNEPBs and RTNP.On the premise that integration system planning schemes of LNEPBs and RTNP schemes have been obtained with the above proposed coordinated planning method,the bulk power network planning focuses on the multi-provincial ultra-high-voltage(UHV)backbone network integrated with polymorphous LNEPBs.A bi-level stochastic transmission planning model is proposed in the final section.The upper-level model deals with the adequacy planning to minimize the life cycle cost of the transmission planning scheme.Considering the uncertain factors and N-1 criterion of transmission lines,the lower-level model evaluates the static security of the generated planning scheme based on 2m+1 point estimate method,with the objective of minimizing load shedding.Then reformulate the proposed bi-level stochastic transmission planning model as a single-level MILP model and solve it with MILP optimizers.Numerical simulation shows that the obtained optimal UHV transmission planning scheme can basicly accommodate the output of polymorphous LNEPBs,and provide strong and firm sending backbone network support to power transmission via extra-high-voltage ac/dc transmission access.The analysis of numerical simulation proves scientificity,validity and practicability of the proposed multi-provincial transmission network stochastic planning method.
Keywords/Search Tags:intermittent renewable new energy generation, transmission planning, integration system planning, coordinated planning, point estimate method, static voltage stability, bi-level planning, mathematical programming with equilibrium constraints
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