The Alberta Energy Resources Allocation Model

1980 ◽  
pp. 185-205
Author(s):  
D. J. McConaghy ◽  
D. Quon
Keyword(s):  
Energy Resources ◽  
Resources Allocation ◽  
Allocation Model

scholarly journals Optimal Allocation Model of Water Resources Based on the Prospect Theory

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1289 ◽  
Author(s):  
Huaxiang He ◽  
Aiqi Chen ◽  
Mingwan Yin ◽  
Zhenzhen Ma ◽  
Jinjun You ◽  
...  
Keyword(s):  
Water Resources ◽  
Prospect Theory ◽  
Optimal Allocation ◽  
Cumulative Prospect Theory ◽  
Resources Allocation ◽  
Simulation Methods ◽  
Allocation Model ◽  
Rule Based ◽  
Highly Skilled ◽  
Optimal Allocation Model

The rational allocation of water resources in the basin/region can be better assisted and performed using a suitable water resources allocation model. Rule-based and optimization-based simulation methods are utilized to solve medium- and long-term water resources allocation problems. Since rule-based allocation methods requires more experience from expert practice than optimization-based allocation methods, it may not be utilized by users that lack experience. Although the optimal solution can be obtained via the optimization-based allocation method, the highly skilled expert experience is not taken into account. To overcome this deficiency and employ the advantages of both rule-based and optimization-based simulation methods, this paper proposes the optimal allocation model of water resources where the highly skilled expert experience has been considered therein. The “prospect theory” is employed to analyze highly skilled expert behavior when decision-making events occur. The cumulative prospect theory value is employed to express the highly skilled expert experience. Then, the various elements of the cumulative prospect theory value can be taken as the variables or parameters in the allocation model. Moreover, the optimal water allocation model developed by the general algebraic modeling system (GAMS) has been improved by adding the decision reversal control point and defining the inverse objective function and other constraints. The case study was carried out in the Wuyur River Basin, northeast of China, and shows that the expert experience considered as the decision maker’s preference can be expressed in the improved optimal allocation model. Accordingly, the improved allocation model will contribute to improving the rationality of decision-making results and helping decision-makers better address the problem of water shortage.

A Resilience-Based Architecture for Joint Distributed Energy Resources Allocation and Hourly Network Reconfiguration

2019 ◽  
Vol 15 (10) ◽  
pp. 5444-5455 ◽  
Author(s):  
Ehsan Kianmehr ◽  
Saman Nikkhah ◽  
Vahid Vahidinasab ◽  
Damian Giaouris ◽  
Philip C. Taylor
Keyword(s):  
Energy Resources ◽  
Distributed Energy Resources ◽  
Resources Allocation ◽  
Network Reconfiguration ◽  
Distributed Energy

A study of multi-objective dynamic water resources allocation modeling of Huai River

2015 ◽  
Vol 15 (4) ◽  
pp. 817-824 ◽  
Author(s):  
Jing Peng ◽  
Ximin Yuan ◽  
Lan Qi ◽  
Qiliang Li
Keyword(s):  
Water Resources ◽  
Dynamic Balance ◽  
Supply And Demand ◽  
Low Flow ◽  
Resources Allocation ◽  
Time Interval ◽  
Water Resources Allocation ◽  
Allocation Model ◽  
Multi Objective ◽  
Huai River

Water resources supply and demand has become a serious problem. Water resources allocation is usually a multi-objective problem, and has been of concern for many researchers. In the north of China, the lack of water resources in the Huai River Basin has handicapped the development of the economy, especially badly in the low-flow period. So it is necessary to study water resources allocation in this area. In this paper, a multi-objective dynamic water resources allocation model has been developed. The developed model took the overall satisfaction of water users in a time interval as the objective function, applied an improved simplex method to solve the calculation, considered the overall users' satisfaction variation with time, and followed the principle that the variation of the system satisfaction within adjacent periods of time must be minimal. The established model was then applied to the Huai River, for the present situation (2010), short-term (2020) and long-term (2030) planning timeframes. From the calculation results, the overall satisfaction in late May and mid September in 2030 was 0.65 and 0.70. After using the model allocation optimization, the overall satisfaction was improved, increasing to 0.78 and 0.79, respectively, thus achieving the dynamic balance optimization of water resources allocation in time and space. This model can provide useful decision support in water resources allocation, when it is used to alleviate water shortages occurring in the low-flow period.

scholarly journals Fuzzy logic controller and game theory based distributed energy resources allocation

AIMS Energy ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 474-492
Author(s):  
Akash Talwariya ◽  
◽  
Pushpendra Singh ◽  
Mohan Lal Kolhe ◽  
Jalpa H. Jobanputra ◽  
...  
Keyword(s):  
Game Theory ◽  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Resources Allocation ◽  
Distributed Energy
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