Abstract:
Several catastrophic global blackouts have occurred, including Bangladesh, in the last few years. Inefficient design of existing load shed schemes is one of the critical reasons to prevent larger blackout footprint. However, the analysis of recent blackouts suggests that voltage collapse and voltage-related problems are also important concerns in maintaining system stability. For this reason, both frequency and voltage need to be taken into account in blackout preventive load shedding schemes. In this context emergency controls that are used to prevent blackouts need to be revisited. It is difficult to prevent system blackouts entirely. However, protection and control procedures can be improved by using the emerging technologies to help reduce the geographical span of blackouts.
Conventional decentralized adaptive load shed schemes might be failed in some credible scenario because of change of demand pattern or network topology. The existing decentralized adaptive load shed scheme tries to estimate the disturbance severity and tries to shed the load accordingly but it goes without saying that the feeders under scheme are fixed and the scheme has no information about feeder load of a system. Due to the lack of enough adaptability to the operation state of the system, the successive estimation and approximation under frequency load shedding scheme will cause excessive cut or undercut problems inevitably.
A new dynamic adaptive load shedding methodology is introduced which helps to improve overall blackout protection including the tie lines security among zones with the help of phasor measurement unit (PMU). The methodology takes care of frequency and voltage stability in response of combinational disturbances of electric power system. The methodology involves measuring the power mismatch and relative disturbance magnitude with taking advantage from load damping factor as well as it decides the amount of load to be shed from each bus using the voltage sensitivities. The proposed methodology dynamically selects the feeders to shed the calculated loads from every PQ bus and any mismatch of calculated loads for a particular bus, the scheme corrects the calculated loads to the next adjacent bus in a more adaptive way, so that the total actual load shed size becomes very close to the calculated required load shed size and make the methodology based scheme more adaptive. Unlike other adaptive techniques it ensures the exact amount of load shed by selecting feeders in a dynamic manner to avoid over or under cut. The proposed methodology incorporates important real time power system stability parameters especially voltage, frequency, frequency decline rate, bus MW and Mvar during a situation where the power system would otherwise have become unstable. In the context of emerging technologies and sub-station communication standard based framework, the proposed methodology is not only limited to it but also monitor and affirm the security of tie lines or interconnections among zones and the aim is to realize this methodology in practice.
To validate the proposed blackout mitigation methodology, it is scripted in python language and implemented on New England test system (IEEE 39 Bus) to execute in ‘Digsilent PowerFactory’ environment for all illustrative case studies. Comparisons of the adaptivity performance of proposed load shedding methodology based scheme with those of other decentralized adaptive schemes are also presented.
