<span style="font-family:Verdana;">The ideal places and size of the distribution generators were determined by reducing the loss of power in the distribution networks. The ideal positioning of various ...<span style="font-family:Verdana;">The ideal places and size of the distribution generators were determined by reducing the loss of power in the distribution networks. The ideal positioning of various kinds of DGs has been suggested in the current job. In this job, the ideal power factor for DG supply has been acquired, both the active power as well as the reactive power. In the proposed approach</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> different types of distribution generation (DG) supply both reactive and real power. For the optimal placement of DG sources</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> particle swarm optimization technique</span><span style="font-family:Verdana;">s</span><span style="font-family:""><span style="font-family:Verdana;"> have been used in this job. Each of these innovations has its own strengths and drawbacks. Most of the methods that have been proposed so far to formulate DG’s optimum placement problem only consider Type-I DGs, Type-II and </span><span style="font-family:Verdana;">Type-III DGs </span></span><span style="font-family:Verdana;">that </span><span style="font-family:Verdana;">are considered for optimal position in the existing research.</span><span style="font-family:Verdana;"> In the reference, artificial bee colony algorithm was used to determine sites of DGs and condenser combinations and optimal size. The author used PSO method in the reference to determine the appropriate positioning of the DG’s and to maximize the savings of power loss and voltage profile in the distribution network.</span>展开更多
<span style="font-family:Verdana;">In the present deregulated electricity market, power system congestion is the main complication that an independent system operator (ISO) faces on a regular basis. Tr...<span style="font-family:Verdana;">In the present deregulated electricity market, power system congestion is the main complication that an independent system operator (ISO) faces on a regular basis. Transmission line congestion trigger serious problems for smooth functioning in restructured power system causing an increase in the cost of transmission hence affecting market efficiency. Thus, it is of utmost importance for the investigation of various techniques in order to relieve congestion in the transmission network. Generation rescheduling is one of the most efficacious techniques to do away with the problem of congestion. For optimiz</span><span style="font-family:Verdana;">ing the congestion cost, this work suggests a hybrid optimization based on</span><span style="font-family:Verdana;"> two effective algorithms viz Teaching learning-based optimization (TLBO) algorithm and Particle swarm optimization (PSO) algorithm. For binding the constraints, the traditional penalty function technique is incorporated. Modified IEEE 30-bus test system and modified IEEE 57-bus test system are used to inspect the usefulness of the suggested methodology.</span>展开更多
文摘<span style="font-family:Verdana;">The ideal places and size of the distribution generators were determined by reducing the loss of power in the distribution networks. The ideal positioning of various kinds of DGs has been suggested in the current job. In this job, the ideal power factor for DG supply has been acquired, both the active power as well as the reactive power. In the proposed approach</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> different types of distribution generation (DG) supply both reactive and real power. For the optimal placement of DG sources</span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> particle swarm optimization technique</span><span style="font-family:Verdana;">s</span><span style="font-family:""><span style="font-family:Verdana;"> have been used in this job. Each of these innovations has its own strengths and drawbacks. Most of the methods that have been proposed so far to formulate DG’s optimum placement problem only consider Type-I DGs, Type-II and </span><span style="font-family:Verdana;">Type-III DGs </span></span><span style="font-family:Verdana;">that </span><span style="font-family:Verdana;">are considered for optimal position in the existing research.</span><span style="font-family:Verdana;"> In the reference, artificial bee colony algorithm was used to determine sites of DGs and condenser combinations and optimal size. The author used PSO method in the reference to determine the appropriate positioning of the DG’s and to maximize the savings of power loss and voltage profile in the distribution network.</span>
文摘<span style="font-family:Verdana;">In the present deregulated electricity market, power system congestion is the main complication that an independent system operator (ISO) faces on a regular basis. Transmission line congestion trigger serious problems for smooth functioning in restructured power system causing an increase in the cost of transmission hence affecting market efficiency. Thus, it is of utmost importance for the investigation of various techniques in order to relieve congestion in the transmission network. Generation rescheduling is one of the most efficacious techniques to do away with the problem of congestion. For optimiz</span><span style="font-family:Verdana;">ing the congestion cost, this work suggests a hybrid optimization based on</span><span style="font-family:Verdana;"> two effective algorithms viz Teaching learning-based optimization (TLBO) algorithm and Particle swarm optimization (PSO) algorithm. For binding the constraints, the traditional penalty function technique is incorporated. Modified IEEE 30-bus test system and modified IEEE 57-bus test system are used to inspect the usefulness of the suggested methodology.</span>