Jia-Zhang Jhan

Photovoltaic (PV) systems have experienced rapid global deployment. However, line-to-line short-circuit faults pose serious safety risks and can lead to significant power losses or fire hazards. While existing fault detection methods can identify fault types, they cannot precisely locate fault positions, resulting in time-consuming and costly maintenance. This paper proposes a heuristic algorithm for accurately locating such faults in PV arrays based on module group voltage measurements. The algorithm employs a two-phase approach: fault candidate marking and fault location determination, capable of handling both intra-string and cross-string faults. Simulation tests on a 21 × 2 PV array configuration demonstrate a 97.56% fault location success rate, reducing the troubleshooting scope to within a single-module group. The proposed method offers a simple, fast, and cost-effective solution for PV system maintenance, potentially saving significant labor costs and reducing system downtime.

Taiwan’s power system operates as an isolated grid, preventing the export of surplus energy. Excess electricity is either stored or discarded (curtailed). This study aims to estimate the energy storage requirement for the day with the most extreme electricity consumption behavior in a year without energy curtailment. Based on the installed capacity and actual power generation of renewable energy sources in 2022, this research estimates the power generation per GW of the installed capacity at full load. Integrating the government’s annual installation capacity plans, this study forecasts the annual power generation of renewable sources. Using the electrical load during the 2023 Spring Festival as a baseline and assuming an annual electricity consumption growth rate of 2%, combined with a minimum gas power output of approximately 6 GW, this study calculates the unused power generation, which represents the pumped-storage hydroelectricity and battery energy storage systems requirements for that day under a no-curtailment scenario. Considering the semi-annual adjustments in installation planning, this study’s code is open-sourced and designed to provide updated results with new planning data input, facilitating ongoing adjustments.

Replacing the traditional rotating generators with renewable energy will reduce the grid’s inertia and with it the minimum frequency when N-1 contingency occurs triggering an Under-Frequency Load Shedding (UFLS). This study proposes a method for the energy storage system (ESS) to simultaneously provide energy arbitrage, reserve capacity, and assist N-1 contingency, by modifying the restriction formula of economic dispatch (ED) and limiting the SOC range of the ESS. Let the ESS join the Spinning Reserve. Through the PSS^®E iterative ESS charging power required at moments when the frequency of contingency is too low in the ED. Let the ESS act as a N-1 contingency extra frequency reserve. This would prevent UFLS and still maintain the demand. The proposed method is applicable to different types of ESS. The method allows energy storages, originally designed for energy arbitrage, to participate in frequency support and spinning reserve.

The capacity aging of lithium-ion energy storage systems is inevitable under long-term use. It has been found in the literature that the aging performance is closely related to battery usage and the current aging state. It follows that different frequency regulation services, C-rates, and maintaining levels of SOC during operation will produce different battery aging rates. In the simulations, the researchers used real frequency data to generate SOC curves based on the Taiwan frequency regulation services under different C-rates and different battery SOC target levels. Then, the aging formula of lithium iron batteries (LiFePO₄ battery, LFP battery) and the proposed improved rainflow counting algorithm were used. The capacity aging situation and economy under different usage scenarios were analyzed. The simulation results showed that using a high C-rate and a low SOC level had a higher net profit, and the income of dReg was more than that of sReg. The SOC of BESS has an important impact on the life cycle. Keeping the SOC at a lower level will help prolong the life cycle and increase the net income. In dReg0.5, maintaining the SOC at 30% would yield 8.5% more lifetimes than 50%, 20.6% more lifetimes than 70%.