Investigations On Impacts Of Distributed Generators And Electric Vehicles On Distribution System Planning And Operation

With the limitation of available transmission corridors and the gradual increase in theglobal temperature, rapid development of Distributed Generators (DGs) has been observedaround the world. DGs combined with distributed energy resource (DER), not only can reduceenergy loss, lessen emission and decrease investment risk, but also can enhance the stabilityand security of power system, improve the power quality and increase energy utilization.However, the extensive penetrations of DGs could lead to some risks to the secure andeconomic operation of power systemsOtherwise, with the progressive exhaustion of fossil energy and the enhanced awarenessof environmental protection, electric vehicles (EVs) have been paid more and more attention.Inappropriate siting and sizing of EV charging stations could affect the development of EVs,the layout of the city traffic network and the convenience of the EV drivers, as well as lead toan increase in network losses and a drop of voltage quality at some buses.Given these backgrounds, many systematic and in-depth investigations on impacts ofdistributed generators and electric vehicles on distribution system planning and operationhave been done in this dissertation for the reasonable and stable penetrations of them intopower system. Meanwhile, the huge potentials can be explored and a lot of auxiliary services,such as the improvement of power quality, the enhancement of power supply reliability andthe increasement of operation flexibility can be achieved.Specifically, the contents of this dissertation are as follows:(1) A sensitivity based approach is presented to identify the optimal siting of DGs. Onthe other hand, the optimal sizing of DGs is determined by the Modified Primal-Dual InteriorPoint Algorithm with an objective of maintaining the voltage profile at the optimal level.IEEE123-node test feeder is employed to verify the effectiveness of the proposed method.The results demonstrate that the proposed approach is able to search for the optimal solutionsquickly. At the same time, the voltage profiles are obviously improved and the network loss isdecreased dramatically(2) Under the chance constrained programming (CCP) framework, a new method ispresented to handle these uncertainties in the optimal siting and sizing of DGs. First, amathematical model of CCP is developed with the minimization of the DGs’ investment cost,operating cost, maintenance cost, network loss cost as well as the capacity adequacy cost asthe objective, security limitations as constraints, the siting and sizing of DGs as optimization variables. Then, a Monte Carlo simulation embedded genetic algorithm based approach isemployed to solve the developed CCP model. Finally, the IEEE37-node test feeder is used toverify the feasibility and effectiveness of the developed model and method, and the test resultshave demonstrated that the voltage profile and power supply reliability for customers can besignificantly improved and the network loss substantially reduced.(3) A two-step screening method with the environment factors and the service radius ofEV charging stations considered is first presented to identify the candidate sites of EVcharging stations. The charging service area of each EV charging station is divided in terms ofthe Voronoi diagram (also called Thiessen polygons), which has been extensively applied togeographic information system (GIS). The EVs’ owners can choose the proper EV chargingstations for charging on basis of the SOC in battery packs.Then, a mathematical model for optimizing the siting and sizing of EV charging stationsis developed and solved by a Modified Primal-Dual Interior Point Algorithm with theminimization of the sum of the EV charging stations’ investment costs, operation costs andmaintenance costs, as well as the network loss costs as the objective function, and someoperating limitations as constraints to be respected. Finally, the IEEE123-node test feeder isemployed to illustrate the essential features of the developed model and method. The testresults demonstrate that the proposed model and method not only can obtain the reasonableplanning schemes of EV charging stations, but also optimize the load curve and voltagequality, as well as enhance the security and reliability of power systems.(4) An optimal under-frequency load shedding strategy for a distribution system withDGs and load static characteristics taken into consideration is developed. Based on thefrequency and the rate of change of frequency (ROCOF), the presented strategy consists ofseveral basic rounds and a special round. In the basic round, the frequency emergency can bealleviated by quickly shedding some loads in a certain orders.In the special round, a mathematical model is developed with the minimization of threeindexes including the load shedding cost, the total sum of the squared voltage deviations at allnodes, and the total sum of the squared frequency deviations as the multi-objective function,and some constraints considered. As a result, the frequency security can be maintained andthe operating parameters of the distribution system can be optimized by adjusting the outputpowers of DGs and some loads. The modified IEEE37-node test feeder is employed todemonstrate the essential features of the developed optimal UFLS strategy in theMATLAB/SIMULINK environment.