Urmia University. Urmia (Iran)
February 23rd, 2022
Summary:
The exploitation of the distributed generations (DGs) sources based on green energies, especially wind and solar, is surging day by day. Despite the technical, environmental, and economic privileges of wind and solar power plants in the distribution networks, causing the fluctuations in network quantities is one of the significant unwanted effects of these sources. These fluctuations are due to the changeable and somewhat unpredictable nature of their initial sources (wind speed and solar radiation). Uncertainties about wind and solar power plants, along with other sources of uncertainty in distribution networks, such as load changes or possible failures in components, keep the state of distribution networks in fluctuating conditions and cause challenges in the operation of these networks. In this regard, more awareness of the network state provides more certainty in making operational decisions and leads to better risk management. On the other hand, soft open point (SOP) devices have been introduced as modern power electronics-based technologies to employ in distribution networks. Because of the capability and benefits of SOP, it has been the subject of many research papers in recent years. Due to the structure of SOPs, these equipment are installed at the normally open (NO) or normally closed (NC) points of distribution networks so that they can provide active power flow control, reactive power compensation, and voltage regulation under normal operating conditions, as well as fast fault isolation and recovery after fault removal in abnormal conditions.
This thesis studies the SOP effects on the fluctuations of the network state caused by uncertainty sources. In this vein, appropriate quantitative criteria have been used to express the fluctuations and changes in distribution network quantities with the names of network predictability indices. In the following, the proposed method for solving the SOP optimal allocation (optimal location and settings) problem to increase network predictability will be elaborated. Since increasing of the network's predictability without considering other issues and operational constraints is not logical and practically justified, in this thesis, a novel framework for the optimal allocation of SOP in order to make a trade-off between various objective functions, including predictability indices, the expected value of active power losses and SOP size along with considering all operating constraints of the distribution networks is proposed. Consequently, the multi-objective particle swarm optimization (MOPSO) method, decision-making, and selection of the final solution based on the technique for order of preference by similarity to the ideal solution (TOPSIS) are employed in this study.
Keywords: Soft open point – Predictability - Multi-objective optimization – Decision making – Uncertainty – Distribution networks
Citation:
S. Rezaeian-Marjani (2022), Optimal allocation of soft open point (SOP) devices for increasing distribution networks predictability. Urmia University. Urmia (Iran).
