No abstract

Future climate change is a source of growing concerns for the supply of energy and resources, and it may have significant impacts on industry and the economy. Major effects are likely to arise from changes to the freshwater resources system, due to the connection of energy generation to these water systems. Using future climate data downscaled by a stochastic weather generator, this study investigates the potential impacts of climate change on long-term reservoir operations at the Chungju multipurpose dam in South Korea, specifically considering the reliability of the supply of water and hydropower. A reservoir model, Hydrologic Engineering Center-Reservoir System Simulation (HEC-ResSim), was used to simulate the ability of the dam to supply water and hydropower under different conditions. The hydrologic model Soil and Water Assessment Tool was used to determine the HEC-ResSim boundary conditions, including daily dam inflow from the 6,642 km 2 watershed into the 2.75 Gm 3 capacity reservoir. Projections of the future climate indicate that temperature and precipitation during 2070-2099 (2080s) show an increase of +4.1°C and 19.4%, respectively, based on the baseline (1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009). The results from the models suggest that, in the 2080s, the average annual water supply and hydropower production would change by +19.8 to +56.5% and by +33.9 to 92.3%, respectively. Model simulations suggest that under the new climatic conditions, the reliability of water and hydropower supply would be generally improved, as a consequence of increased dam inflow.(KEY TERMS: climate change; multipurpose dam; reservoir operation; water and hydropower supply; water resource system.)

The Southern High Plains (SHP) region of Texas in the United States, where cotton is grown in a vast acreage, has the potential to grow cellulosic bioenergy crops such as perennial grasses and biomass sorghum (Sorghum bicolor). Evaluation of hydrological responses and biofuel production potential of hypothetical land use change from cotton (Gossypium hirsutum L.) to cellulosic bioenergy crops enables better understanding of the associated key agroecosystem processes and provides for the feasibility assessment of the targeted land use change in the SHP. The Soil and Water Assessment Tool (SWAT) was used to assess the impacts of replacing cotton with perennial Alamo switchgrass (Panicum virgatum L.), Miscanthus 9 giganteus (Miscanthus sinensis Anderss. [Poaceae]), big bluestem (Andropogon gerardii) and annual biomass sorghum on water balances, water use efficiency and biofuel production potential in the Double Mountain Fork Brazos watershed. Under perennial grass scenarios, the average (1994-2009) annual surface runoff from the entire watershed decreased by 6-8% relative to the baseline cotton scenario. In contrast, surface runoff increased by about 5% under the biomass sorghum scenario. Perennial grass land use change scenarios suggested an increase in average annual percolation within a range of 3-22% and maintenance of a higher soil water content during August to April compared to the baseline cotton scenario. About 19.1, 11.1, 3.2 and 8.8 Mg ha À1 of biomass could potentially be produced if cotton area in the watershed would hypothetically be replaced by Miscanthus, switchgrass, big bluestem and biomass sorghum, respectively. Finally, Miscanthus and switchgrass were found to be ideal bioenergy crops for the dryland and irrigated systems, respectively, in the study watershed due to their higher water use efficiency, better water conservation effects, greater biomass and biofuel production potential, and minimum crop management requirements.

The large-scale integration of electric vehicles (EVs) into power systems is expected to lead to challenges in the operation of the charging infrastructure. In this paper, we deal with the problem of an aggregator coordinating charging schedules of EVs with the objective of minimizing the total charging cost. In particular, unlike most previous studies, which assumed constant maximum charging power, we assume that the maximum charging power can vary according to the current state of charge (SOC). Under this assumption, we propose two charging schemes, namely non-preemptive and preemptive charging. The difference between these two is whether interruptions during the charging process are allowed or not. We formulate the EV charging-scheduling problem for each scheme and propose a formulation that can prevent frequent interruptions. Our numerical simulations compare different charging schemes and demonstrate that preemptive charging with limited interruptions is an attractive alternative in terms of both cost and practicality. We also show that the proposed formulations can be applied in practice to solve large-scale charging-scheduling problems.