| 1. |
- Fenstermacher, M.E., et al.
(författare)
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DIII-D research advancing the physics basis for optimizing the tokamak approach to fusion energy
- 2022
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Ingår i: Nuclear Fusion. - : IOP Publishing. - 0029-5515 .- 1741-4326. ; 62:4
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Tidskriftsartikel (refereegranskat)abstract
- DIII-D physics research addresses critical challenges for the operation of ITER and the next generation of fusion energy devices. This is done through a focus on innovations to provide solutions for high performance long pulse operation, coupled with fundamental plasma physics understanding and model validation, to drive scenario development by integrating high performance core and boundary plasmas. Substantial increases in off-axis current drive efficiency from an innovative top launch system for EC power, and in pressure broadening for Alfven eigenmode control from a co-/counter-I p steerable off-axis neutral beam, all improve the prospects for optimization of future long pulse/steady state high performance tokamak operation. Fundamental studies into the modes that drive the evolution of the pedestal pressure profile and electron vs ion heat flux validate predictive models of pedestal recovery after ELMs. Understanding the physics mechanisms of ELM control and density pumpout by 3D magnetic perturbation fields leads to confident predictions for ITER and future devices. Validated modeling of high-Z shattered pellet injection for disruption mitigation, runaway electron dissipation, and techniques for disruption prediction and avoidance including machine learning, give confidence in handling disruptivity for future devices. For the non-nuclear phase of ITER, two actuators are identified to lower the L-H threshold power in hydrogen plasmas. With this physics understanding and suite of capabilities, a high poloidal beta optimized-core scenario with an internal transport barrier that projects nearly to Q = 10 in ITER at ∼8 MA was coupled to a detached divertor, and a near super H-mode optimized-pedestal scenario with co-I p beam injection was coupled to a radiative divertor. The hybrid core scenario was achieved directly, without the need for anomalous current diffusion, using off-axis current drive actuators. Also, a controller to assess proximity to stability limits and regulate β N in the ITER baseline scenario, based on plasma response to probing 3D fields, was demonstrated. Finally, innovative tokamak operation using a negative triangularity shape showed many attractive features for future pilot plant operation.
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| 2. |
- Nagaraja, Ch., et al.
(författare)
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Opening remarks
- 2016
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Konferensbidrag (refereegranskat)
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| 3. |
- Mahmoud, Thair Shakir, et al.
(författare)
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The role of intelligent generation control algorithms in optimizing battery energy storage systems size in microgrids : A case study from Western Australia
- 2019
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Ingår i: Energy Conversion and Management. - : Elsevier. - 0196-8904 .- 1879-2227. ; 196, s. 1335-1352
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Tidskriftsartikel (refereegranskat)abstract
- Battery energy storage systems can play a substantial role in maintaining low-cost operation in microgrids, and therefore finding their optimal size is a key element of microgrids’ planning and design. This paper explores the optimal sizing options for batteries in microgrids that include wind turbines, solar photovoltaics, synchronous machines and a grid connection supply under various types of retail tariff schemes. The optimal size of batteries is hypothesized to be significantly related to the intelligent control rules applied to dispatch the microgrid sources. This problem can be formulated as a mixed linear integer problem and can be solved using linear/non-linear solvers depending on the complexity of the generation control plan. The main objective of this work is to apply online intelligent adaptation mechanism to tune the economic generation control (dispatch) rules of the microgrid. This tuning objectives are maintaining secure operation, maximizing profitable utilization of batteries and managing their charging life-cycles. While sizing options exploration has been formulated as a linear programming based optimization problem, Fuzzy-Logic is proposed to control the charging/discharging time and quantity for batteries. For the sake of performance comparison, various optimization techniques, i.e., Particle Swarm Optimization, Genetic Algorithm and Flower Pollination Algorithm are applied to perform the economic dispatch calculation. As a case study, a commercial type load connected to the 22 kV distribution network in south Western Australia was used in the testing and validation if the results of the proposed sizing method. The operation condition data was obtained from Western Power the distribution and transmission company in south Western Australia, the Australian Bureau Of Meteorology (BOM) and the Australian Energy Market Operator (AEMO). The results showed that employing intelligent batteries in operation can reduce the annual generation cost of microgrids. However, the decision on selecting the size of batteries depends heavily on the amount of upfront investment cost. The simulation results showed that the intelligence added to batteries’ control could achieve 6.5%, 7.6% and 11.5% of the annual generation cost in the Islanded, Grid-connected with no-export and Grid-connected with export operating modes respectively. Also, intelligent batteries operation control was proven to minimize their payback time to 2.8, 2.7 and 2.7 years in the Islanded, Grid-connected with no-export and Grid-connected with export operating modes respectively.
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