scholarly journals Research on bidding mechanism and strategy of hydropower unit based on coupling resources

2021 ◽  
Vol 675 (1) ◽  
pp. 012072
Author(s):  
Wenjiao Ding ◽  
Zhanhui Lu ◽  
Bangcan Wang ◽  
Peishan He ◽  
Yu Liu ◽  
...  
Keyword(s):  
2011 ◽  
Vol 2-3 ◽  
pp. 608-613
Author(s):  
Ying Zi Wei ◽  
Yi Jun Feng ◽  
Kan Feng Gu

This paper builds an efficient agent-based flexible scheduling for real-world manufacturing systems. Considering the alternative processes and alternative machines, the allocation of manufacturing resources is achieved through negotiation among the job and machine agents in a multi-agent system (MAS). Ant Colony Intelligence (ACI) is proposed to be combined with Contract Net Protocol (CNP) so as to make agents adaptive to changing circumstances. ACI is integrated into both machine agents and job agents to solve the task allocation and sequencing problem. CNP is introduced to allow the agents to cooperate and coordinate their local schedules in order to find globally near-optimal robust schedules. The negotiation protocol is an interactive bidding mechanism based on the hybrid contract net protocol. The implementation of the issues using CNP model is discussed. Experimental results verify the effectiveness and efficiency of the proposed algorithm integrated with ant-inspired coordination.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 28888-28901
Author(s):  
Zhaohui Liu ◽  
Zhongjie Wang

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 9 ◽  
Author(s):  
Debin Fang ◽  
Qiyu Ren ◽  
Qian Yu

The deepening of electricity reform results in increasingly frequent auctions and the surge of generators, making it difficult to analyze generators’ behaviors. With the difficulties to find analytical market equilibriums, approximate equilibriums were obtained instead in previous studies by market simulations, where in some cases the results are strictly bound to the initial estimations and the results are chaotic. In this paper, a multi-unit power bidding model is proposed to reveal the bidding mechanism under clearing pricing rules by employing an auction approach, for which initial estimations are non-essential. Normalized bidding price is introduced to construct generators’ price-related bidding strategy. Nash equilibriums are derived depending on the marginal cost and the winning probability which are computed from bidding quantity, transmission cost and demand distribution. Furthermore, we propose a comparative analysis to explore the impact of uncertain elastic demand on the performance of the electricity market. The result indicates that, there exists market power among generators, which lead to social welfare decreases even under competitive conditions but elastic demand is an effective way to restrain generators’ market power. The feasibility of the models is verified by a case study. Our work provides decision support for generators and a direction for improving market efficiency.


Author(s):  
Jonathan Lee ◽  
Hsi-Min Chen ◽  
Shang-Pin Ma ◽  
Yao-Chiang Wang ◽  
Shin-Jie Lee
Keyword(s):  

1981 ◽  
Vol 9 (2) ◽  
pp. 221-234 ◽  
Author(s):  
A. H. Barnett

Among the many problems faced by policy makers in attempts to use public funds efficiently, none is more troublesome than that of inducing users of public goods to reveal their demand prices. The difficulty in attempts to solicit demand prices falls under the general rubric of the free-rider problem, and is manifest in the propensity of users to behave strategically when asked to reveal evaluations. Several preference revelation devices have been proposed to surmount this problem, but all of these schemes are seriously flawed. This article presents a device which overcomes some of the flaws contained in previous work. The preference revealing mechanism proposed here is a bidding mechanism which takes advantage of the commonly found trait of risk-aversion to discourage strategic revelations.


2017 ◽  
Vol 2017 (13) ◽  
pp. 966-972
Author(s):  
Jiawei Zhou ◽  
Bingxing Yue ◽  
Jinrong Wu ◽  
Hua Huang ◽  
Chunliu Wang

Sign in / Sign up

Export Citation Format

Share Document