Abstract –– The large increase in load demands cause congestion in transmission lines which leads to instability in the power system operation. Distributed generation is used to minimize the power losses and thus to improve the system stability. Improper DG placement may increase system losses, network capital and operating costs. Which is important to find the size and location of distributed generation, inorder to minimize line losses of power system. This paper uses the Maximum Power Stability Index (MPSI) which is derived from the maximum power transfer theorem. The MPSI is employed as an objective to determine the optimal DG locations. The idea of maximum power transfer is to maximize the amount of active power that can be delivered to
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This method begins with initial estimation of all unknown variables. The main advantage of Newton Raphson method is the superior convergence because of quadratic convergence usually employed for large sized system. It is more accurate and smaller number of iterations than Gauss-Seidel method. The number of iterations is not dependent on the system size. The method is insensitive to factors like slack bus selection, regulating transformers and presence of series capacitors. It is comparatively faster and more …show more content…
MPSI values and potential places for DG placement
Optimal location based on the index
Location MPSI Index
7 0.9783
19 0.9727
DGs are inserted at these selected best locations in such a way that the size of the DG is varied from minimum value to maximum value. For both the test systems, the size of the DGs is varied from 0.1 MW to 10 MW. The sizes, which provide the minimum real power losses, are the best size of DGs to be placed at these optimal locations. The success of any algorithm or optimization is endorsed, only if it is suitable for a variety of situations. Here, to examine the success and stiffness of this proposed approach, two cases are considered for the test system as follows. Case I - Single DG placement Case II – Two DG placement
Case I - Single DG placement For IEEE 30 bus system the DG units is placed at the location at bus 7 obtained from the maximum MPSI value. The correct size of DG unit in the location is identified as 9.8985 MW. The value of real power losses for this case is observed as 2.15 MW.
Case II - Two DGs placement at all identified
This method begins with initial estimation of all unknown variables. The main advantage of Newton Raphson method is the superior convergence because of quadratic convergence usually employed for large sized system. It is more accurate and smaller number of iterations than Gauss-Seidel method. The number of iterations is not dependent on the system size. The method is insensitive to factors like slack bus selection, regulating transformers and presence of series capacitors. It is comparatively faster and more …show more content…
MPSI values and potential places for DG placement
Optimal location based on the index
Location MPSI Index
7 0.9783
19 0.9727
DGs are inserted at these selected best locations in such a way that the size of the DG is varied from minimum value to maximum value. For both the test systems, the size of the DGs is varied from 0.1 MW to 10 MW. The sizes, which provide the minimum real power losses, are the best size of DGs to be placed at these optimal locations. The success of any algorithm or optimization is endorsed, only if it is suitable for a variety of situations. Here, to examine the success and stiffness of this proposed approach, two cases are considered for the test system as follows. Case I - Single DG placement Case II – Two DG placement
Case I - Single DG placement For IEEE 30 bus system the DG units is placed at the location at bus 7 obtained from the maximum MPSI value. The correct size of DG unit in the location is identified as 9.8985 MW. The value of real power losses for this case is observed as 2.15 MW.
Case II - Two DGs placement at all identified