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This study aims to provide a detailed spatial and temporal characterization of China’s wind and solar energy resource potential. Quantifying this potential is necessary to identify pathways to achieve a deep decarbonization of its electric power system as this nation pursues carbon neutrality by 2060. This study identifies and characterizes sites suitable for onshore wind and ground-mounted solar PV deployment, quantifies their electricity generation potential, and assesses their spatial heterogeneity across the country and temporal variability throughout the seasons. Resource potential estimates are obtained by combining the latest data with high spatiotemporal resolution with a geographic information system (GIS) analysis that compiles information on wind and solar energy resources, land use, surface elevation and slope, and geomorphology. Results show that China’s vast resource potential for wind and solar is enough to provide one-and-a-half times 2050′s expected electricity demand. Results also demonstrate that China’s resource-rich areas do not correspond to demand centers, except for provinces like Shandong, Hebei, and Jiangsu, which have high electricity demand and renewable potential. The seasonal patterns show that China should develop wind and solar energy simultaneously, to exploit wind’s highest potential during winter and early spring, and solar’s higher production during late spring and summer. These findings shed light on the sites that should be prioritized for renewable development and the need to expand power transmission capacity connecting energy-rich areas with load centers, and energy storage capacity and flexible resources to balance variable renewable output with load.

This study explores the performance of the Duke Energy Progress/Carolinas (DEC/DEP) electric power system under eighty-five configurations combining different capacities of utility-scale photovoltaics (PV) and energy storage (lithium-ion batteries). The different configurations include PV installations capable of providing 5% to 25% of the systems energy and batteries with varying power capacities and storage of 2, 4, and 6 hours. A cost-based production model comprised of a day-ahead unit commitment and a real-time economic dispatch simulates the optimal operation of all the generation resources necessary to supply hourly demand and reserve requirements during the year 2016. The model represents in detail the generation fleet of the system, including 221 nuclear, natural gas, coal and hydro power generators accounting for an installed capacity of 37.8 GW. Results indicate that minimum carbon abatement costs for the configurations studied are obtained when the power capacity of the batteries is~12.5% of the PV capacity. For levels of PV penetration (measured as expected annual share of energy) above 17%, higher decarbonization targets are better pursued with increased storage capacity than with more PV. For more ambitious targets (e.g. $> 30\%$ ), carbon dioxide emissions reductions require increases in both PV and storage capacity. Like previous studies this analysis confirms the decreasing marginal value of storage especially in systems that already have important shares of low carbon generation, such as DEC/DEP where ~50% of the generation is provided by nuclear plants.

The role of dispatchable resources evolves over space and over time as the power sector decarbonizes; this evolution reconfigures the spatial layout of China's power system, eventually redrawing its economic, social, and environmental maps.

Abstract Hydropower facilities are an ideal solution to complement the intermittent production of energy from wind and solar photovoltaic facilities in electric power systems. However, adding this task to the multiple diverse duties of a reservoir (e.g., flood mitigation, water supply, and power generation) poses a challenge related to pursuing multiple and sometimes conflicting objectives. This study proposes an approach for integrating hydro, wind, and photovoltaic power during a reservoir’s refill period. Specifically, this approach simultaneously minimizes the fluctuation in the combined power output of these three resources and maximizes their combined power generation while adhering to the target reservoir’s water levels. The proposed approach uses a multiobjective optimization model that prescribes a day-ahead optimal hourly operation for a hydropower facility in terms of spilled water, water stored in the reservoir, and water used for power generation, while meeting a daily target to refill the reservoir. The prescribed scheduling is then used as the input into a model that simulates the actual operations of the power system. This study focuses on a hydro-wind-photovoltaic system located in southwestern China, where the peak power generating capacity of the hydropower facility is ten percent larger than the combined installed capacity of the wind and solar power. The results show that by using the proposed model, the hydropower facility effectively smooths the fluctuations in the combined power output caused by variable wind and photovoltaic power and concurrently meets the reservoir replenishing targets under dry, moderate, or wet hydrologic scenarios. Furthermore, the trade-offs between power generation maximization and power fluctuation reduction were found to depend on two conditions: whether the reservoir is full, and whether the turbine is generating electricity at its maximum capacity. The hydro-wind-photovoltaic integration is more cost-effective when the reservoir is not full and the turbines are not generating electricity at their maximum capacity. When the reservoir is full, hydropower still has the ability to balance the wind and photovoltaic power without curtailment but tends to result in water spillage (22–402 m3/s) and reductions in electricity generation (0.1–11.4 GWh per day). The proposed method for scheduling operations allows hydropower facilities to complement wind and photovoltaic power output, while meeting the target water levels during the refill period.

Abstract This study explores the performance of the Duke Energy Carolinas/Progress (DEC/DEP) electric power system under one hundred forty-one configurations combining different capacities of utility-scale photovoltaics (PV) and battery energy storage (lithium-ion batteries or BES). The different configurations include PV installations capable of providing 5–25% of the systems energy and batteries with varying duration (energy-to-power ratio) of 2, 4, and 6 h. A production cost model comprised of a day-ahead unit commitment and a real-time economic dispatch simulates the optimal operation of all the generation resources necessary to supply hourly demand and reserve requirements during the year 2016. The model represents in detail the generation fleet of the system, including 221 nuclear, natural gas, coal and hydro power generators with a combined installed capacity of 37.8 GW. Results indicate that: 1) adding BES to a power system that includes PV further reduces carbon dioxide emissions while also lowering the cost of carbon abatement. 2) The optimal power rating of a BES system that supports PV seems to be lower than 25% of the capacity of the PV. 3) BES of short duration (2-h) are more cost-effective (i.e., result in a lower cost of abatement) when the level of PV penetration is low (lower than ~12.5%), while BES of longer duration (6-h) are more cost-effective when there are larger shares of PV. 4) The installation of optimal configurations of PV + BES to reduce carbon emissions in the DEC/DEP system by ~14–57% would increase the levelized cost of electricity (LCOE) ~8–65%. 5) If projections of declining costs for the next decade materialize, the installation of up to 15 GW of PV + 1.88 GW / 3.76 GWh of BES would reduce the LCOE while achieving up to 33% reduction in carbon emissions.

Variable renewable energy (VRE) and energy storage systems (ESS) are essential pillars of any strategy to decarbonize power systems. However, there are still questions about the effects of their interaction in systems where coal’s electricity generation share is large. Some studies have shown that in the absence of significant VRE capacity ESS can increase CO2 emissions. This paper shows that contrary to this intuition, ESS reduces operational costs and emissions even without higher penetration of VRE in power systems with large shares of coal. It also shows that when combined with VRE, ESS delivers higher benefits. These findings are based on the examination of China Southern Power Grid under seven VRE and ESS penetration scenarios. Results show that at the 2018 penetration levels, ESS alone reduced operational costs by 2.8% and CO2 emissions by 1% and that by being paired with VRE, these reductions increased to 8.1% and 6.5%, respectively. The results clarify the synergy between ESS and VRE and explain the underlying mechanism. While VRE lowers coal units’ economic efficiency and environmental performance (measured in RMB/MWh and kg CO2/MWh), ESS offsets this effect by increasing large coal units’ power generation and improving their efficiency. ESS reduces coal consumption and CO2 emissions by substituting power generation from low-efficiency coal units with electricity from high-efficiency units and allowing them to operate at levels closer to full capacity and avoid start-ups.

AbstractHigher education institutions have long played a key role in solving society's most pressing problems. However, as the scale and complexity of socio‐environmental problems has grown, there has been a renewed debate about the role that academic institutions should play in developing solutions and how institutional structures should be redesigned to encourage greater interdisciplinarity. In the following pages, we present a graduate student perspective on this debate. Specifically, we identify challenges facing interdisciplinary graduate student researchers and present a series of recommendations for how institutions can better prepare them to become the next generation of leaders in interdisciplinary, action‐oriented research focused on solving socio‐environmental problems.

Resource adequacy, or ensuring that electricity supply reliably meets demand, is more challenging for wind- and solar-based electricity systems than fossil-fuel-based ones. Here, we investigate how the number of years of past weather data used in designing least-cost systems relying on wind, solar, and energy storage affects resource adequacy. We find that nearly 40 years of weather data are required to plan highly reliable systems (e.g., zero lost load over a decade). In comparison, this same adequacy could be attained with 15 years of weather data when additionally allowing traditional dispatchable generation to supply 5 % of electricity demand. We further observe that the marginal cost of improving resource adequacy increased as more years, and thus more weather variability, were considered for planning. Our results suggest that ensuring the reliability of wind- and solar-based systems will require using considerably more weather data in system planning than is the current practice. However, when considering the potential costs associated with unmet electricity demand, fewer planning years may suffice to balance costs against operational reliability.