Bohomolova O. Methods and models for estimating the power of Solar and Wind Generation in the nodes of the Electrical Network

The thesis is devoted to solving the current scientific and applied problem of developing methods and models for finding the optimal node for connecting solar and wind sources to increase the efficiency of design and operational solutions, which creates conditions for improving the operating network by reducing power losses and improving the quality of electricity with normalizing voltage at the nodes. As the part of stochastic capacity of RES sources in the energy balance of Ukraine is growing dynamically, there are problems of optimizing the places of their installation in electrical networks and limiting the capacity of these sources. And the choice of connection only on the basis of primary indicators (such as solar insolation, wind strength and intensity, etc.) are less important than the local characteristics of the network and its condition and can worsen the technical and economic performance of electrical networks. To determine the optimal connection point of the RES source, a method of complex assessment of the sensitivity of electrical network nodes is used. This method builds on principles of minimization power losses in the network, voltage change in nodes taking into account investments in investment-innovative RES project, applying restrictions on total input power WG and compliance with voltage regime in nodes application of additional means of reactive power compensation. This method allows to: reduce the impact of stochastic power generation on the mode parameters of the network; evaluate the nodes and power of the source of solar and wind generation at the stage of pre-design options, and can also be used when choosing the best option at the design stage. The expert decision-making system regarding the location of the WG with the help of the MATLAB fuzzy logic toolkit is built on the basis of the rule base and multi-set selection, respectively. Input values are the sensitivity of active power losses, the sensitivity of the nodes to the voltage, the difference between intrinsic and mutual conductivity, the investment ratio. The initial value is the level of setting the power of the DG. The obtained transfer characteristic of the synthesized fuzzy logic controller allows to rank the nodes of the electrical network according to the input calculation parameters and select several points for installation with the maximum value of ratings, for which it is necessary to assess the physical possibility of installing DG sources. In the dissertation, the choice of the defining connection is performed using the methods of fuzzy logic theory, which operates on linguistic variables. In this case, the processing of linguistically formed expertise on the basis of phase technology is performed. The synthesized fuzzy logic controller allows you to generate a command to switch the soldering of the transformer and provide the required voltage value on the low side of the transformer. Improving the efficiency of voltage regulation in distribution networks in the introduction of distributed generation sources using a fuzzy logic controller allowed regulating the voltage level in the system to rational values, while minimizing electricity losses in compliance with its quality standards. The practical value of the obtained results is that the express method of estimating the maximum power and connection node of solar and wind generation at the stage of formation of design solutions is developed, which allows to increase the efficiency of network operation and ensure minimum power loss and normalized network voltage A new generalized method of short-term determination of solar and wind generation capacity in electrical network nodes in planning its operating modes based on universal generation factor, which takes into account power losses and changes in voltage level as indicators of electricity quality, which improves technical and economic efficiency of electricity network with solar and wind generation.