Integration of Solar Photovoltaic Distributed Generators in Distribution Networks Based on Site’s Condition

Abstract

The significance of Distributed Generators (DGs) in the technical and economic operations of electric power distribution systems cannot be overemphasized in recent times. This is essential as a result of the incessant increase in electrical energy demand, which is becoming considerably difficult to meet with the conventional means of energy supply. Thus, DGs offer better alternatives for providing a quality supply of energy near the site of consumption. This type of energy supply is cleaner and cheaper most of the time due to the lessened transmission losses, which consequently reduced the cost of operation at the transmission and distribution levels of the power system. In this work, an approach for placement and sizing of solar PV DGs into radial distribution networks (RDN) based on the solar PV capacity factor of the site was analyzed using particle swarm optimization. The aim of this study is to analyze the effect of the approach on the real and reactive power losses within the network as well as the bus voltage profile. Constraints on credible system operation parameters, which includes bus voltage limits, power balance, and power flow limits, are considered in the formulation of the optimization problem. In order to verify the viability of the deployed approach, steady-state performance analyses were executed on IEEE 33-bus RDN; and the results obtained were compared with the results from other approaches reported in the literature.

Efficient Allocation and Sizing the PV-STATCOMs in Electrical Distribution Grids Using Mixed-Integer Convex Approximation

“…To contribute to efficient alternatives for improving performance in EDSs and allow these systems to deal with the new operation paradigm in the context of active EDSs, the subject of this study was the compensation of apparent power (i.e., active and reactive power simultaneously) in EDSs. As previously mentioned, there are multiple alternatives to improve the performance of EDSs, which include the integration (i.e., placement and dimension) of renewable energy generations (mainly photovoltaic (PV) sources) [18] and shunt compensators of the reactive power [19]. The primary idea of this study is to explore the possibility of dynamically apparent power (i.e., active and reactive power simultaneously) in EDSs, considering PV generation sources.…”

“…Equation (12) sets the voltage value at the slack bus, and inequalities ( 13) and ( 14) work to limit the voltage profiles in each node to their minimum and maximum values any each time t. Inequality (15) determines the maximum possible value of the PV-STATCOM devices, while inequalities ( 16) and ( 17) define the limits regarding the maximum active and reactive power that the PV-STATCOM devices can deliver/absorb for each node. Inequality (18) is the maximum value of the apparent power that can flow through the PV-STATCOM devices at node m and time t, and, finally, inequality (19) defines the maximum number of PV-STATCOM devices that will be located into the network.…”

Diseño óptimo de una micro-red para maximizar la generación de potencia eléctrica en Paragachi y Wildtecsa modelado en Homer Pro

“…Una de las principales características de las microredes, es que, por su propia definición, se comportan como pequeños centros de generación distribuida [12]. Este concepto engloba la generación de electricidad mediante instalaciones que son en general pequeñas (3 kW -10 MW) en relación con las grandes centrales de generación, de forma que se puedan conectar casi en cualquier punto de un sistema eléctrico [13]. La generación distribuida tiene diversas ventajas.…”

Stochastic Allocation of Photovoltaic Energy Resources in Distribution Systems Considering Uncertainties Using New Improved Meta-Heuristic Algorithm

“…In [13], allocation of PVs in distribution networks is developed using an Archimedes optimization algorithm (AOA) inspired by physical principles to minimize network dependence and greenhouse gas emissions. PSO is developed in [14] to allocate the photovoltaic resources for active and reactive losses reduction of the distribution systems. Multi-objective PSO is used in [15] to allocate the photovoltaic resources in the distribution systems to minimize the losses and minimize the voltage deviation and voltage stability enhancement.…”