In order to have a reliable microgrid (MG) system, we need to keep the frequencywithin an acceptable range. However, due to disturbances in a MG system (suchas a sudden load change), it can experience major or minor deviations in frequency,which needs to be reduced within seconds to provide the system stability. In order tomaintain the balance between energy supply and demand, traditionally, generationside controllers are utilized to stabilize the power system frequency. These systemsadd high operational cost, which is not desired for power system operators. Withthe introduction of smart grid, more and more renewable energy sources are to beused in the power system. The intermittent behavior of these energy resources, aswell as high operation cost of conventional controllers, has led to research for newalternatives. In a smart grid environment, demand response (DR) programs can beconsidered as a promising alternative to the conventional controllers, to e cientlycontribute to the frequency regulation by switching responsive loads on or o . DRprograms can reduce the amount of energy reserve required and, hence, are morecost efficient. Moreover, they can act very fast and can provide a wide range ofoperation time from a few seconds to several minutes. Thermostatically controlledloads (TCLs) are proper candidates to participate in frequency regulation programs.However, individual TCLs do not have a noticeable impact on frequency due to smallsize. They should be aggregated in order to have a considerable effect on frequency.Nevertheless, there are still many challenges which should be addressed in orderto make use of TCLs for frequency control in smart grid. In this regard, properaggregated load models and control algorithms for TCLs contributing to this serviceneed to be investigated.In this thesis, we present an aggregation model for TCLs and a control strategyto coordinate power provided from DR participants with that of generation side ofthe MG to keep system frequency within its desired range. For the aggregationmodel considered in this study, a state space model is used to take into account theinterdependency of TCLs' temperature participating in DR programs. The modelgroups TCLs into clusters, each controlled by an aggregator. A minimum off/onperiod is considered for individual TCLs to avoid frequent switching of these devices.A control strategy is presented to control frequency by coordinating the generationand demand side regulation service providers. Computer simulation results showthat the proposed aggregation model and control strategy can effectively controlfrequency under various case studies.
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Frequency control via demand response in smart grid