KEYWORDS: Photovoltaics, Solar energy, Transformers, Solar radiation models, Analytical research, Computer simulations, Data modeling, Statistical analysis, Renewable energy
The increase in the number of photovoltaic installations connected to the low-voltage power grid, in addition to obvious benefits, under certain circumstances also adversely affects the network's operating conditions. Power generation from photovoltaic sources, strongly dependent on insolation, on the one hand is not able to cover the energy demand in the daily load peaks, and on the other hand - in another part of the day it exceeds the current demand, causing excess energy production. The randomness of photovoltaic generation negatively influences the voltage in the network. The article attempts to model the variability of network with PV sources operation conditions, using probabilistic methods for this purpose. The analyzes were carried out, based on actual measurement data, for a low-voltage test network with photovoltaic microinstallations. The result of the conducted research is the analysis of voltage levels in selected periods of the year and the day.
A dynamic increase in the share of renewable energy sources in the power industry may cause various changes related to the optimal functioning of the entire power system [7], [10]. A high concentration of renewable energy sources in the power system may force the need to reconfigure the network in order to ensure optimal work. The article presents the impact of renewable energy sources on the location of MV grid division points. As the function of the target, the minimization of active power losses in the network was selected. The research was carried out for a dozen or so variants of network operation to determine the magnitude of the impact of these sources on the location of optimal network partition points. The optimization calculations were carried out using the Cuckoo Search algorithm (cuckoo search).
Some quantities in the power industry, are subject to random changes, depending on the current state of the network, atmospheric conditions, or unforeseen, in normal conditions, events. It is difficult to describe them with classical dependencies, therefore a probabilistic approach seems to be appropriate. While analyzing the measurements of these quantities, for a certain period of time, an appropriate probability distributions can be assigned to them. The article presents the results of such considerations, for selected variables based on their real values. It should be noted that some quantities result from others (due to the connection), they are a kind of compilation.
KEYWORDS: Algorithms, Photovoltaics, Optimization (mathematics), MATLAB, Network security, Renewable energy, Control systems, Monte Carlo methods, Medium wave, Electrical engineering
Medium voltage networks work as radial. In reality, however, such configurations of linear SN lines are provided, so that in the event of disturbances, do not completely deprive the receivers of power only to be able to make the changeover and feed them from another substation. For this reason, they are designed so that it is possible to connect with other MV lines. In the normal state these places are referred to as cut points and selected to minimize power losses. The article presents the method of optimal determination of cut points, using the heuristic optimization method. The calculations included two PV sources and their random nature of generation as well as loads in nodes.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.