An Adaptive Route Planning Method of Connected Vehicles for Improving the Transport Efficiency

In recent years, the route-planning problem has gained increased interest due to the development of intelligent transportation systems (ITSs) and increasing traffic congestion especially in urban areas. An independent route-planning strategy for each in-vehicle terminal improves its individual travel efficiency. However, individual optimal routes pursue the maximization of individual benefit and may contradict the global benefit, thereby reducing the overall transport efficiency of the road network. To improve traffic efficiency while considering the travel time of individual vehicles, we propose a new dynamic route-planning method by innovatively introducing a bidding mechanism in the connected vehicle scenario for the first time. First, a novel bidding-based dynamic route planning is proposed to formulate vehicle routing schemes for vehicles affected by congestion via the bidding process. Correspondingly, a bidding price incorporating individual and global travel times was designed to balance the travel benefits of both objectives. Then, in the bidding process, a new local search algorithm was designed to select the winning routing scheme set with the minimum bidding price. Finally, the proposed method was tested and validated through case studies of simulated and actual driving scenarios to demonstrate that the bidding mechanism would be conducive to improving the transport efficiency of road networks in large-scale traffic flow scenarios. This study positively contributes to the research and development of traffic management in ITSs.

Renewable Energy Certificate Trading via Permissioned Blockchain

With the continuous advancement of the green certificate trading mechanism, information verification needs to span multiple departments, which causes the application process cumbersome and human errors. In order to solve problems of cumbersome issuance process of the renewable energy certificate (REC) and the inflexible pricing mechanism, in this paper, a hybrid REC trading system was proposed based on an permissioned blockchain technology (BT), which combined advantages of the BT and the continuous double auction (CDA). The operation process of the system was introduced in detail, and the view change protocol in the Practical Byzantine Fault Tolerance algorithm was revised according to the characteristics of the system to improve the system stability. The continuous double auction rule was also introduced in the system. And corresponding bidding strategies were designed to maximize the revenue of users (buyer and seller) and transaction probability. The simulation experiment proves that the bidding mechanism can flexibly adjust the REC price according to the supply and demand relationship. At the same time, the effectiveness and feasibility of trading rule and bidding strategy were also verified.

Impact of Process Misconception in Becker-DeGroot-Marschak Single Response Value Elicitation Procedures: An Experimental Investigation in Consumer Behavior Using the IKEA Effect

Consumer researchers frequently employ valuation experiments to assess consumer opinions and test related hypotheses. One popular method used in many such experiments is the Becker- DeGroot-Marschak (BDM) single-response value elicitation procedure that initiates an incentive for the subjects to respond with their true valuation by utilizing a random bid to which the participants’ bid is compared. However, the “random bid” is not a straightforward concept, and the participants may not fully understand the mechanics of the bidding process. Therefore, they may incorrectly associate the bidding mechanism with a conventional auction bidding process in which the highest bidder wins, causing biased valuation outcomes. In this paper, we introduce a comprehension measurement step to eliminate the process comprehension bias in BDM valuation experiments. We also discuss the potential impact of the treatment of “zero” bidders in the BDM procedure. The present work shows that the size and statistical significance of past consumer research results are positively correlated with the participant comprehension of the valuation procedure. The results suggest that consumer research using a single-response value elicitation procedure, which initiates an incentive for the subjects to respond with their true valuation, may not be trusted if the comprehension level is not controlled.

Hierarchical Coordinated Control Method for Multiload DC Microgrid Units

Electricity has become not merely a source of power but also a vital component of our lives in a rapidly changing world. However, according to a World Bank report, 17% of the globe’s population live without power. The key cause for such a huge population not being electrified is the proximity of the central electrical grid system or the high expenditure of installing the grid lines to such remote areas. The notion of a microgrid was first proposed more than a decade ago, but the numerous obstacles it entails have hampered its broad adoption and made it a research focus in recent years. A hierarchical control structure of the microgrid is designed, which is divided into layers according to the control objectives and control time scales of the microgrid, and the hierarchical control structure is realized by using multiagent technology. In the framework of hierarchical control, aiming at the demand of energy coordination and optimization of the microgrid, the operation strategy of the microgrid is proposed in grid-connected and/or off-grid mode. In the grid-connected mode, the large power grid is used for power supply and in the off-grid mode, the load bidding mechanism is introduced to ensure the power supply of important loads. Experiment results reveal the power quality and stability of the system.

An axiomatic and non-cooperative approach to the multi-step Shapley value

Inspired by the two-step Shapley value, in this paper we introduce and axiomatize the multi-step Shapley value for cooperative games with levels structures. Moreover, we design a multi-step bidding mechanism, which implements the value strategically in subgame perfect Nash equilibrium for superadditve games.

Effects of a Battery Energy Storage System on the Operating Schedule of a Renewable Energy-Based Time-of-Use Rate Industrial User under the Demand Bidding Mechanism of Taipower

Due to the increased development of the smart grid, it is becoming crucial to have an efficient energy management system for a time-of-use (TOU) rate industrial user in Taiwan. In this paper, an extension of the direct search method (DSM) is developed to deal with the operating schedule of a TOU rate industrial user under the demand bidding mechanism of Taipower. To maximize the total incentive obtained from the Taiwan Power Company (TPC, namely Taipower), several operational strategies using a battery energy storage system (BESS) are evaluated in the study to perform peak shaving and realize energy conservation. The effectiveness of the proposed DSM algorithm is validated with the TOU rate industrial user of the TPC. Numerical experiments are carried out to provide a favorable indication of whether to invest in a BESS for the renewable energy-based TOU rate industrial user in order to execute the demand bidding program (DBP).