The continued growth in load demand and the gradual change of generation sources to smaller distributed plants utilizing renewable energy sources (RESs), which supply power intermittently, is likely to strain existing power systems and cause congestion. Congestion management still remains a challenging issue in open access transmission and distribution systems. Conventionally, this is achieved by load shedding and generator rescheduling. In this study, the control of the system congestion on an islanded micro grid (MG) supplied by RESs is analyzed using artificial bee colony (ABC) algorithm. Different buses are assigned priority indices which forms the basis of the determination of which loads and what amount of load to shed at any particular time during islanding mode operation. This is to ensure as minimal load as possible is shed during a contingency that leads to loss of mains and ensure a congestion free microgrid operation. This is tested and verified on a modified IEEE 30-bus distribution systems on MATLAB platform. The results are compared with other algorithms to prove the applicability of this approach.
The main aim of a power utility company is to supply quality and uninterrupted power to customers. This becomes a growing challenge as the continued increase in population calls for proportional increase in power supply to additional loads. If not well planned, this steady increase in power demand can lead to voltage collapse and eventual power blackouts. In instances where power demand exceeds generation within islanded microgrid or due to an occurrence of a contingency, optimum load shedding should be put in place so as to enhance system security and stability of the power system. Load shedding is traditionally done based on undervoltage measurements or underfrequency measurements of a given section of the grid. However, when compared with conventional methods, metaheuristic algorithms perform better in accurate determination of optimal amount of load to be shed during a contingency or undersupply situations. In this study, an islanded microgrid with high penetration of Renewable Energy Sources (RESs) is analyzed, and then Artificial Bee Colony (ABC) algorithm is applied for optimal load shedding. The results are then compared with those of Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and GA-PSO hybrid. Both generation and overload contingencies are considered on a standard IEEE 30-bus system on a MATLAB platform. Different buses are assigned priority indices which forms the basis of the determination of which loads and what amount of load to shed at any particular time.
Abstract:Currently the greatest threat to the power systems reliability and security is the cascading of electric system failures thus causing power blackouts. For quite some time now, the world has been encountering many power blackouts as a result of these cascading failures. The cascading power failure instances pose great risks towards the integrity of power system network. This may finally lead to the splitting of the power system into various small unintentional islands. Hence, intentional or controlled islanding is then utilized as a preventive measure to mitigate the losses caused by unintentional islanding of the power system. Thus, by doing this, the entire power system is split into controlled island regions for the purposes of easy handling and control. In such situation, each islanded region should have sufficient generation to supply its connected loads in order to remain operative and stable. It should also be pointed out that intentional islanding is very important as it can prevent the entire power system from collapsing. The distributed generators supplying the loads in these islands may not be able to maintain the voltage and frequency within desired limits in the distribution system when it is islanded within the micro grid. There may be a power deficit within the island. This eventually leads to shedding of some loads within the island for the sake of stability of the system. Hence the main challenge here is to determine the appropriate and reliable method to optimize the power supply and the load demand in the island and thus maintain the voltage and frequency within the desired limit. In this study we focused on the determination of the minimum load amount for shedding within the islanded region and the prioritization of the buses for shedding so that electricity supply to customers could be maximized using ABC algorithm. From the results obtained, the ABC algorithm can be successfully applied for solving the optimization and prioritization problems within the island being supplied by a DG. The ABC algorithm has several merits over other algorithms which makes it suitable in this application. These advantages include; it is easily implemented, flexible, has few control parameters, easily hybridized with other optimization algorithms and can be modified very easily to suit any application. This system was simulated in MATLAB and SIMULINK using IEEE fourteen bus systems.
The increased use of distributed generation in the power system due to increased load demand has brought about many benefits to the power grids. This is due to the concerns about whether the technology in use currently in power generation and distribution, is sufficient to cover the future increasing demand with the limited supply. In response to this problem of increased load demand, efforts have been made to decentralize this infrastructure through the use of distributed generators. The benefits of using distributed generation include; improved reliability and increased efficiency in power supply, avoidance of transmission and distribution capacity upgrades, improved power quality and reduced line losses, minimize peak load demand, reduce voltage flicker, eliminate the need of having high spinning reserve among others. Despite these advantages, unintentional islanding remains a big challenge and has to be addressed in integration of Distributed Generation to the power system. Unlike inverter based distributed generators, rotating machine based generators with fast response governors and AVRs are highly capable of sustaining an island. Therefore, anti-islanding protection for these generators is a more challenging problem in comparison with the inverter-based DG. This paper analyses the use of wavelet transform in islanding detection for rotating based distributed generators.
An electric rotating machine can be defined as any form of apparatus which has a rotating member and generates, converts, transforms, or modifies electric power, such as a motor, generator, or synchronous generator. Although there are many variations, the two basic rotating machine types are synchronous and induction machines. The recent increasing use of rotating machines among other distributed generators is due to a number of advantages including peak shaving, improvement of the quality of power and reliability, power efficiency, environmental friendliness among others. Despite the above mentioned benefits of distributed power generation in the power grid, they have one major drawback, unintentional islanding. If this islanding condition is not detected in time or goes undetected, the distributed generator loses synchronism with the rest of the utility supply. This may lead to out of phase reconnection of the two systems and thus destroying the distributed generators and even lead to a total blackout in the power system. Again, upon the occurrence of an island, rotating machine based generators have another possible consequence of self-excitation. There is therefore need of fast detection of islanding condition especially when rotating machine based generators are integrated into the main power grid. There are many islanding detection methods and each has its merits and demerits. Their usage depends on certain factors including type of distributed generation in consideration and cost of implementation. Furthermore, the rotating machine based generators have the capability of sustaining an island. This makes the islanding detection and protection of these generators a bit challenging when compared with inverter based generators. This paper presents a passive islanding detection method, fuzzy logic algorithm, particularly on rotating machine based generators and its results analyzed under different conditions. After this analysis, it is concluded that the proposed method for islanding detection for rotating machine based generators is robust and accurate when implemented in the distribution network. This is because fuzzy logic control helps to improve the interpretability of knowledge-based classifiers through its semantics that provide insight in the classifier structure and decision-making process over crisp classifiers.
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