Abstract
Distributed generation (DG) is gaining importance as electrical energy demand increases. DG is used to decrease power losses, operating costs, and improve voltage stability. Most DG resources have less environmental impact. In a particular region, the sizing and location of DG resources significantly affect the planned DG integrated distribution network (DN). The voltage profiles of the DN will change or even become excessively increased. An enormous DG active power, inserted into an improper node of the distribution network, may bring a larger current greater than the conductor’s maximum value, resulting in an overcurrent distribution network. Therefore, DG sizing and DG location optimization is required for a systematic DG operation to fully exploit distributed energy and achieve mutual energy harmony across existing distribution networks, which creates an economically viable, secure, stable, and dependable power distribution system. DG needs to access the location and capacity for rational planning. The objective function of this paper is to minimize the sum of investment cost, operation cost, and line loss cost utilizing DG access. The probabilistic power flow calculation technique based on the two-point estimation method is chosen for this paper’s load flow computation. The location and size of the DG distribution network are determined using a genetic algorithm in a MATLAB environment. For the optimum solution, the actual power load is estimated using historical data. The proposed system is based on the China distribution system, and the currency is used in Yuan. After DG access, active and reactive power losses are reduced by 53% and 26%, respectively. The line operating cost and the total annual cost are decreased by 53.7% and 12%, respectively.
Highlights
Distributed generation (DG) is a small-scale distributed power production unit, located near the load, meant to fulfil the load requirement of specialized customers or supplement the grid for economic efficiency
This paper collects and analyzes a series of research works on probabilistic power flow, DG location, and capacity problems based on the point estimation method
It can be seen that, when DG is only connected to node i on the distribution line and the active power PDGi of load node, i is larger than the total active load time of feeder node i to n, i.e., PDGi > PLi + PLi+1 + PLi+2 + . . . + PLn The direction of power flow will be reversed, and DG will transmit power to the power side of the distribution network, which is a potentially adverse effect on the stable operation of the distribution system after DG is connected
Summary
Distributed generation (DG) is a small-scale (usually 1 kW–50 MW) distributed power production unit, located near the load, meant to fulfil the load requirement of specialized customers or supplement the grid for economic efficiency. The probability of trend, Probabilistic Load Flow (PLF), is calculated using mathematical probability statistical methods It can reflect the impact of various uncertainties and random changes, in the grid system of electricity, to run the system [28]. The point estimate method (PEM) is a probability-to-certainty problem solving technique that considers the correlation between input variables [30,31] It can be used, in conjunction with the existing probabilistic load flow algorithm, to obtain an accurate distribution for quantity. This paper collects and analyzes a series of research works on probabilistic power flow, DG location, and capacity problems based on the point estimation method. Historical load data of the actual power grid is used for the simulation, the genetic algorithm is used to optimize the calculation. A graphical interface software for DG location is developed by MATLAB programming
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