Modern power systems increasingly require forecasts that not only achieve statistical accuracy but also support reliable operational and planning decisions under uncertainty. This review synthesizes 107 studies on how probabilistic forecasts of load and renewable generation are converted into optimization decisions in renewable-integrated power systems. Unlike prior reviews that treat forecasting, uncertainty quantification (UQ), and optimization separately, this review treats all three as a single coupled decision chain, mapping which forecaster–UQ–optimizer combinations are methodologically mature and which remain unexplored. Using a PRISMA 2020-guided process, we classify studies by forecasting architecture, uncertainty representation, optimization paradigm, application domain, and time horizon. The review shows that short-term and day-ahead horizons dominate the corpus, while scenario generation and stochastic optimization remain the most common bridges from uncertainty representation to decision-making. However, only a minority of studies report calibration or proper scoring metrics, and geographic transferability remains weak. The strongest structural gap is the limited coupling between advanced probabilistic forecasters and downstream optimization objectives. We identify four research priorities—joint probabilistic forecasting for multi-energy systems, decision-focused forecast training, transfer learning for data-scarce grids, and conformal prediction linked to stochastic or distributionally robust optimization—alongside a fifth, cross-cutting priority: explainable and well-calibrated probabilistic forecasting. The review provides a decision-chain taxonomy for designing uncertainty-aware energy-management pipelines in renewable-rich power systems.
This study designed the micro-scale version of PeLUIt-10 with a thermal power of 10MWt for application in remote areas. The main focus was on optimizing the core geometry to facilitate transportation and evaluating fuel integrity. This work introduces an integrated trade-off analysis to systematically evaluate the coupled effects of core size reduction on reactor performance, safety, and core component transportability. The first geometry optimization was conducted by reducing the core volume from 5.0 m3 to 3.0 m3 with H/D ratio of 0.9, with a burnup limit of 40 MWd/kg-HM, and the second was reducing the total diameter of the core and side reflector to fit inside a standard container. Neutronic analysis was conducted using the PEBBED code, thermal hydraulic analysis using the one-dimensional solver in PEBBED code, and TRISO fuel particle failure was evaluated using the TRIAC-BATAN code with the Once Through Then Out (OTTO) refueling scheme. The results showed that the maximum burnup decreased with the reduction in core volume, and the design criteria for burnup (above 40 MWd/kg-HM) were fulfilled at the core volume of 3.7 m3 (41.58 MWd/kg-HM). Under the Depressurized Loss of Flow and Coolant accident, the reactor maintained the temperature well below the safety limit. The failure fraction was also calculated, which resulted in lower failure fraction in a smaller core volume. To address the core components transportability of the reactor, the core diameter was reduced to meet the standard issue container dimensions. When reducing the side reflector thickness at the previously acquired core volume, the reactor could not maintain criticality because the resulting increase in neutron leakage dominated the effect of the fissile inventory. However, increasing the volume and H/D ratio proved to be successful in reducing the core diameter while maintaining the performance, which is 4.3 m3 with H/D ratio of 2.5, resulting in a total core diameter of 2.499 m.
In tropical peatland regions, direct chlorination of peat water is a common household practice to improve clarity and ensure microbial safety. However, this simple treatment can produce toxic disinfection by-products (DBPs) due to the high organic matter and acidity of peat water. This perspective examines the dual nature of chlorination—its effectiveness in removing bacteria and reducing color, versus its role in generating hazardous halogenated compounds. Chlorine reacts with humic and fulvic substances, yielding trihalomethanes, haloacetic acids, and other DBPs with mutagenic and carcinogenic potential. In the absence of controlled dosing and residual monitoring, households often use excessive chlorine, allowing prolonged reactions and increasing DBP concentrations. Field observations in Indonesian peatland communities indicate that chlorination is typically guided by visual cues rather than quantitative control, leading to a false sense of safety. The paper highlights the urgent need for risk awareness, simple pre-treatment steps to remove precursors, and practical dosing guidance to balance microbial and chemical safety. Future efforts should emphasize locally appropriate technologies such as biochar filtration, natural coagulants, or hybrid UV-chlorination systems. Ensuring safe drinking water for peatland populations requires integrating scientific understanding, community education, and policy action to reduce DBP exposure without compromising microbial protection.
Effective and sustainable water resource management is crucial in monsoon-dominated regions This study examines rainfall variability and its hydrological implications in the Cimanuk-Jatigede watershed, West Java, Indonesia, using a 41-year record (1981–2022) from nine rain gauge stations. The rainfall variability was assessed using the Rainfall Anomaly Index (RAI), seasonal classification was determined by Water Availability Index (WAI) based on the precipitation-to-evapotranspiration ratio, and long-term trends were detected using the Mann–Kendall test and Sen's slope estimator. Results indicate substantial spatiotemporal variability, with annual precipitation ranging from 787 to 6561 mm. Five stations (P1, P3, P6, P7, and P8) exhibited statistically significant increasing rainfall trends (p < 0.05), with the highest rate observed at P7 Pamulihan (Sen's slope ≈ 57.96 mm yr−1). The wet season spans October to May while June to September constitutes the dry season. Direct runoff accounts for approximately 82
Previous studies on drag and lift topology optimization have only accounted for steady flow field information, despite the sufficiently high Reynolds number such that vortex shedding would occur which causes unsteadiness. This work investigates the incorporation of unsteady flow field information in the result of the topology optimization. To that end, we propose a topology optimization framework that combines Lattice Boltzmann Method (LBM) for unsteady incompressible flow simulation and the Level Set Method for a clear-boundary representation of the evolving topology. A continuous adjoint variational analysis is used to derive the optimization method, which includes the adjoint problem and the optimizer. Objective functions that are specific to LBM and level set are formulated and verified with results from Navier–Stokes optimizers. The Reynolds numbers treated here are 10, 20, 100, and 150, the first two being lower than the first critical value of an initial circular cylinder, while the last two being above. In both regimes, the optimizer results in geometries that stabilize the wake. Particularly for the case of lift maximization, stabilization is achieved through the appearance of trailing elements which, in combination with an elongated trailing edge, create a suction mechanism. The optimizer converges toward local optimized solutions depending on the averaging length and initial geometry. To verify that the proposed framework can handle and optimize truly unsteady flow phenomena, an optimization is carried out for a body in the wake of a cylinder, a region dominated by inherent vortex shedding. Unlike past lift-maximization results, rounder leading edges are found for the main structure of lift maximization, facilitating the reception of incoming vortices for larger production of time-averaged lift while adhering to the drag constraint. These results confirm that the proposed method successfully incorporates unsteady flow effects into the fluid topology optimization process.
