| 1. |
- Fu, Y., et al.
(författare)
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Effects of uncertainties on the capacity and operation of an integrated energy system
- 2021
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Ingår i: Sustainable Energy Technologies and Assessments. - : Elsevier Ltd. - 2213-1388 .- 2213-1396. ; 48
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Tidskriftsartikel (refereegranskat)abstract
- Uncertainty is a common and critical problem for planning the capacity and operation of integrated energy systems (IESs). This study evaluates the effects of uncertainties on the capacity and operation of an IES. To this aim, system planning and operation with uncertainties are optimized by a two-stage stochastic programming model and compared with a referencing deterministic case. Specifically, the uncertainties of photovoltaic (PV) generation and energy demand are investigated. Regarding system capacity, a larger energy storage capacity is needed to accommodate a higher uncertainty. The superimposed uncertainties have a higher effect on system capacity than the sum of the effect of each uncertainty. The uncertainty of energy demand has a higher impact than the uncertainty of PV generation. Regarding system operation, the increase in operation cost is smaller than the increase in investment cost and total cost. In addition, the average flexibility provided by the energy storage increases with uncertainty and uncertainties affect the change rate for power charging/discharging of the electric energy storage. Regarding the effect on the grid, the uncertainties increase not only the magnitude of ramping-rate, but also the frequency of power-dispatch.
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| 2. |
- Lin, H., et al.
(författare)
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Characteristics of electric vehicle charging demand at multiple types of location - Application of an agent-based trip chain model
- 2019
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Ingår i: Energy. - : Elsevier Ltd. - 0360-5442 .- 1873-6785. ; 188
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Tidskriftsartikel (refereegranskat)abstract
- This paper developed an agent-based trip chain model (ABTCM) to study the distribution of electric vehicles (EVs) charging demand and its dynamic characteristics, including flexibility and uncertainty, at different types of location. Key parameters affecting charging demand include charging strategies, i.e. uncontrolled charging (UC) and off-peak charging (OPC), and EV supply equipment, including three levels of charging equipment. The results indicate that the distributions of charging demand are similar as the travel patterns, featured by traffic flow at each location. A discrete peak effect was found in revealing the relation between traffic flow and charging demand, and it results in the smallest equivalent daily charging demand and peak load at public locations. EV charging and vehicle-to-grid (V2G) flexibility were examined by instantaneous adjustable power and accumulative adjustable amount of electricity. The EVs at home locations have the largest charging and V2G flexibility under the UC strategy, except for a period of regular working time. The V2G flexibility at work and public locations is generally larger than charging flexibility. Due to the fast charging application, the uncertainties of charging demand at public locations are the highest in all locations. In addition, the OPC strategy mitigates the uncertainty of charging demand.
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