# Stochastic Approach to Hosting Limit of Transmission System and Improving Method Utilizing HVDC
###### Abstract  
According to the global de-carbonization trends, renewable energy integration has become an increasingly important issue in power systems. To achieve 100% renewable energy integration and operate a system with these resources, it is necessary to appropriately evaluate the system hosting capability and prepare appropriate planning and operation strategies using the evaluation result. So far, these interests have focused particularly on distribution-level systems. However, although the hosting limit in transmission-level systems requires further consideration, previous study is limited. This study introduces the constraints on the transmission-level hosting limit. In addition, a stochastic estimation of the hosting limit methodology in the transmission system and the use of a high voltage direct current system to improve hosting capacity are proposed and evaluated. Moreover, these methodology-based simulations are conducted using possible scenarios on the IEEE 39 bus system with some constraints, and the simulation results are presented herein. The results showed that the HVDC location selection and operation using the proposed method and optimization technique is appropriate. The strategy can be used to integrate more renewable energy. Furthermore, the proposed methodology can be applied to renewable energy integration scenario establishing a plan. hosting capacity; renewable energy integration; transmission system; stochastic analysis; HVDC system; operating strategy; power system planning +
Footnote †: journal: Applied  
_Applied_  
Footnote †: journal: Applied  
these problems, with several studies using a probabilistic method to evaluate the volatility and uncertainty. The generation output characteristics of solar energy, which depend on the locational property, were evaluated using a stochastic approach [8]. The generation output characteristics of wind energy were analyzed using probabilistic load flow modeling [9]. Moreover, to respond appropriately to these negative effects, the importance of accuracy for generation forecasts has increased. By utilizing these prediction results, a power generation schedule and reserve plans have been properly established to prevent unforeseen situations, such as demand and supply imbalance and under-frequency load shedding (UFLS), in worst-case power outages [10]. While efforts are being made to solve these problems through analytical approaches, operational and planning strategies have also been developed. These efforts include establishing a flexible operating strategy, limiting the output of DERs, and introducing special facilities, such as flexible AC transmission system (FACTS), high voltage direct current (HVDC), energy storage system (ESS), to reinforce the system [11; 12; 13; 14]. Moreover, newly constructed renewable energy facilities may be concentrated in specific areas because of public acceptance related to location restrictions and issues of available natural energy sources. In this case, HVDC can be an effective solution for integrating and transmitting the generation from large-scale renewable energy resources, such as photovoltaic (PV) and offshore wind farms, to demand areas [15; 16]. Many studies have been conducted on the hosting capacity of distribution systems through stochastic methods [17; 18; 19]. However, there is limited research on transmission systems. The hosting limit estimation of the transmission system has been carried out, and the dynamic characteristics of DERs, reactive power support related to voltage problems, and detailed load model have been analyzed [20]. This shows that the hosting limit of the entire system is highly dependent on these consideration options. In addition to the considered options of the distribution system in the renewable energy integration, some factors such as generator decommissioning, re-dispatch, operational reserves, inertia, or frequency, need to be considered in the transmission system hosting limit based on the grid code.