Electric power system networks are composed typically of four major subsystems: generation, transmission, distribution, and utilization. Distribution System (DS) links the generated power to the end user, and usually encompass distribution feeders configured radially and exclusively fed by a utility substation. There are two main aspects to the optimal DG integration problem; the first is the optimal DG placement, while the second is the optimal DG sizing. The criterion to be optimized in the process of choosing the optimal bus and size is minimizing the distribution network real power losses. Integrating Distribution Generation sources (DGs) into an electric power system has an overall positive impact on the system. This impact can be enhanced via optimal DG placement and sizing. The DG rating, on the other hand, is formulated as a nonlinear optimization problem subject to highly nonlinear equality and inequality constraints. Sizing the DG optimally is performed using a conventional Sequential Quadratic Programming (SQP) method and a Fast SQP (FSQP) method. The FSQP is an improved version of the conventional SQP method that incorporates the Fast and Flexible Radial Power Flow (FFRPF) routine, to satisfy the power flow requirements. This Matlab design is based Improved Sequential Quadratic Programming (ISQP) method as given below, Step 1: Find the best location of DG for IEEE 33 Bus System & IEEE15 Bus System, The mathematical objective function, The objective function H is the minimization of total loss of the system,PLoss.
Where, nline is number of transmission lines in the system Step 2: Find the optimum size of DG in order to get minimizing power loss and improves the voltage profile (at each bus) by using ISQP based on the reference paper, considering voltage and power loss as the constraints Step 3: Run the load flow analysis find the power loss and voltages at each bus with DG and Without DG, plot the graphs of voltage variations and mention power loss.
Reference Paper: Improved Sequential Quadratic Programming Approach for Optimal Distribution Generation Sizing in Distribution Networks Author’s Name: M. F. AlHajri, M. R. AlRashidi and M. E. ElHawary Source: IEEE Year:2010
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