16-06-2016, 08:43 PM
thesis matlab code optimal dg allocation placements
|
thesis matlab code optimal dg allocation placements
|
thesis matlab code optimal dg allocation placements
23-06-2016, 01:08 PM
Abstract
Distributed generations (DGs) play an important role in distribution networks. Among many of their merits, loss and THD reduction and voltage profile improvement can be the salient specifications of DG. Studies show that non-optimal locations and non-optimal sizes of DG units may lead to losses increase, together with bad effect on voltage profile and harmonics. So, this paper aims at determining optimal DG allocation and sizing. To do so, the heuristic optimization technique named Particle Swarm Optimization (PSO) is used as the solving tool to minimize simultaneously the economic cost of overall system by changing sitting and varying sizes of DGs. In this optimization method, the investment cost of DGs and power losses are considered in order to being minimized. Firstly, a radial distribution power flow (PF) algorithm is executed to find the global optimal solution. Then, with respect to voltage profile, THD and loss reduction and by using the sensitivity analysis, PSO is used to calculate the objective function and to verify bus voltage limits. To include the presence of harmonics, PSO was integrated with a harmonic power flow algorithm (HPF). The proposed (PSO-HPF) based approach is tested on an IEEE 15-bus radial distribution system. Finally, the returning of investmental cost is calculated to show the economic justification of DG placement. These scenarios yields efficiency in improvement of voltage profile and reduction of THD and power losses; it also permits an increase in power transfer capacity and maximum loading.
Distributed generations (DGs) play an important role in distribution networks. Among many of their merits, loss and THD reduction and voltage profile improvement can be the salient specifications of DG. Studies show that non-optimal locations and non-optimal sizes of DG units may lead to losses increase, together with bad effect on voltage profile and harmonics. So, this paper aims at determining optimal DG allocation and sizing. To do so, the heuristic optimization technique named Particle Swarm Optimization (PSO) is used as the solving tool to minimize simultaneously the economic cost of overall system by changing sitting and varying sizes of DGs. In this optimization method, the investment cost of DGs and power losses are considered in order to being minimized. Firstly, a radial distribution power flow (PF) algorithm is executed to find the global optimal solution. Then, with respect to voltage profile, THD and loss reduction and by using the sensitivity analysis, PSO is used to calculate the objective function and to verify bus voltage limits. To include the presence of harmonics, PSO was integrated with a harmonic power flow algorithm (HPF). The proposed (PSO-HPF) based approach is tested on an IEEE 15-bus radial distribution system. Finally, the returning of investmental cost is calculated to show the economic justification of DG placement. These scenarios yields efficiency in improvement of voltage profile and reduction of THD and power losses; it also permits an increase in power transfer capacity and maximum loading.
21-07-2016, 10:49 AM
Abstract
Distributed generations (DGs) play an important role in distribution networks. Among many of their merits, loss and THD reduction and voltage profile improvement can be the salient specifications of DG. Studies show that non-optimal locations and non-optimal sizes of DG units may lead to losses increase, together with bad effect on voltage profile and harmonics. So, this paper aims at determining optimal DG allocation and sizing. To do so, the heuristic optimization technique named Particle Swarm Optimization (PSO) is used as the solving tool to minimize simultaneously the economic cost of overall system by changing sitting and varying sizes of DGs. In this optimization method, the investment cost of DGs and power losses are considered in order to being minimized. Firstly, a radial distribution power flow (PF) algorithm is executed to find the global optimal solution. Then, with respect to voltage profile, THD and loss reduction and by using the sensitivity analysis, PSO is used to calculate the objective function and to verify bus voltage limits. To include the presence of harmonics, PSO was integrated with a harmonic power flow algorithm (HPF). The proposed (PSO-HPF) based approach is tested on an IEEE 15-bus radial distribution system. Finally, the returning of investmental cost is calculated to show the economic justification of DG placement. These scenarios yields efficiency in improvement of voltage profile and reduction of THD and power losses; it also permits an increase in power transfer capacity and maximum loading.
Distributed generations (DGs) play an important role in distribution networks. Among many of their merits, loss and THD reduction and voltage profile improvement can be the salient specifications of DG. Studies show that non-optimal locations and non-optimal sizes of DG units may lead to losses increase, together with bad effect on voltage profile and harmonics. So, this paper aims at determining optimal DG allocation and sizing. To do so, the heuristic optimization technique named Particle Swarm Optimization (PSO) is used as the solving tool to minimize simultaneously the economic cost of overall system by changing sitting and varying sizes of DGs. In this optimization method, the investment cost of DGs and power losses are considered in order to being minimized. Firstly, a radial distribution power flow (PF) algorithm is executed to find the global optimal solution. Then, with respect to voltage profile, THD and loss reduction and by using the sensitivity analysis, PSO is used to calculate the objective function and to verify bus voltage limits. To include the presence of harmonics, PSO was integrated with a harmonic power flow algorithm (HPF). The proposed (PSO-HPF) based approach is tested on an IEEE 15-bus radial distribution system. Finally, the returning of investmental cost is calculated to show the economic justification of DG placement. These scenarios yields efficiency in improvement of voltage profile and reduction of THD and power losses; it also permits an increase in power transfer capacity and maximum loading.
|
« Next Oldest | Next Newest »
|
