Digital empowerment and the internationalization of SRDI enterprises: a dynamic game approach

It is expected that multiple virtual power plants (multi-VPPs) will appear and participate in the future local energy market (LEM). The trading behaviors of those VPPs need to be carefully studied in order to maximize the benefit brought to the local energy market operator (LEMO) and each VPP. we propose a bounded rationality based trading model of multi-VPPs in local energy market by using a dynamic game approach with different trading targets. Three kinds of power bidding models for VPPs are first set up with different trading targets. In the dynamic game process, VPPs can also improve the degree of rationality and then find the most suitable target at different requirements by evolutionary learning after considering the opponents' bidding strategies and its own clustered resources. LEMO would decide the electricity buying/selling price in the LEM. Furthermore, the proposed dynamic game model is solved by a hybrid method consisting of the improved particle swarm optimization (IPSO) algorithm and conventional large-scale optimization. Finally, case studies are conducted to show the performance of the proposed model and solution approach, which may provide some insights for VPPs to participate in the LEM in real-world complex scenarios.

Stability as well as robustness is the major concerns in the design of a trajectory tracking controller for an autonomous vehicle. In this paper, a novel lateral stability controller design for vehicle path tracking is developed. First, using dynamic game theory as a general framework, vehicle lateral stability can be viewed as a dynamic difference game so that its two players, namely, the active front steering (AFS) system and active rear steering (ARS) system can work together to provide more stability for vehicle path tracking control. The interactive steering control strategies between AFS and ARS are obtained by noncooperative closed-loop feedback Stackelberg game theory to ensure optimal performance for vehicle path tracking. Then, based on the proposed path-following shared control paradigm, by applying the method of zero-sum game theory, a finite-time robust regulator is developed to make the interaction model more robust to uncertain lateral disturbances. Finally, double-lane change and serpentine driving condition with and without uncertain time-varying lateral disturbance are used to evaluate the proposed control algorithm. Simulation and hardware-in-loop implementation results show that the proposed shared control paradigm based robust path-tracking controller can robustly provide better lateral stability when time-varying lateral disturbances are bounded.

“"Digital empowerment" means that through the application of digital technology, the empowered can enhance their capabilities, expand their functions, enhance their development momentum, and open up development space. Based on the digitally-empowered ideological and political teaching model of college English listening course, this paper proposes a reform path to promote the intelligent, personalized, efficient and collaborative development of the ideological and political education process of college English listening course. The teaching model examines digital technology, critical thinking and political literacy. The reform path requires a combination of various factors, including: Digital empowerment advocates new ideas, digital empowerment optimizes new designs, digital empowerment adds new content, digital empowerment uses new methods, digital empowerment develops new resources, digital empowerment education new evaluation, digital empowerment disciplines new integration, and digital empowerment creates a new platform.

Time-varying [formula omitted] control for a class of linear quantum systems: A dynamic game approach

Robust model matching control of immune systems under environmental disturbances: Dynamic game approach

Exploring the co-opetition mechanism of renewable energy trade between China and the “Belt and Road” countries: A dynamic game approach

On Capturing Rent from a Non-Renewable Resource International Monopoly: A Dynamic Game Approach

This paper proposes an energy market management framework to address the day-ahead optimization of a distribution network (DN) with a multi-microgrid (MMG). In this framework, an economic optimization based on a dynamic game is designed to ensure the reliability and stability of the DN operation while setting the internal transaction price to minimize the operation cost of the distribution network operator (DNO). The DNO, as a leader, sets the power flow constraints and microgrid operators (MGOs), as followers, respond to the internal transaction price and in turn affect the DNO’s price decision. The price incentive mechanism of the DNO is to encourage MGs to participate in energy market management, to promote joint operation of MGs and to reduce the operation cost of MGOs. The differential evolution algorithm and mixed integer programming method are applied to find the equilibrium solution to the dynamic game. Numerical simulations of a modified IEEE 33-bus system show the effectiveness of the proposed energy market management framework.

Cooperative diversity protocols are designed with the assumption that terminals always help each other in a socially efficient manner. This assumption may not be valid in commercial wireless networks where terminals may misbehave for selfish or malicious intentions. The presence of misbehaving terminals creates a social-dilemma where terminals exhibit uncertainty about the cooperative behavior of other terminals in the network. Cooperation in social-dilemma is characterized by a suboptimal Nash equilibrium where wireless terminals opt out of cooperation. Hence, without establishing a mechanism to detect and mitigate effects of misbehavior, it is difficult to maintain a socially optimal cooperation. In this paper, we first examine effects of misbehavior assuming static game model and show that cooperation under existing cooperative protocols is characterized by a noncooperative Nash equilibrium. Using evolutionary game dynamics we show that a small number of mutants can successfully invade a population of cooperators, which indicates that misbehavior is an evolutionary stable strategy (ESS). Our main goal is to design a mechanism that would enable wireless terminals to select reliable partners in the presence of uncertainty. To this end, we formulate cooperative diversity as a dynamic game with incomplete information. We show that the proposed dynamic game formulation satisfied the conditions for the existence of perfect Bayesian equilibrium.

Sensors are energy constrained, which leads to possible selfishness as the sensor may decline to forward packets for other nodes. Sensors also face the problem of unfair depletion of their energy if communication protocols were energy-unaware. To address the above concern, we propose the dynamic Bayesian game approach: our algorithm derives mutually acceptable path selection strategies between the sensor and its neighbor, thereby resulting in fairer use of their energy. We validate the feasibility of this technique via analysis and simulations. The results show that it can efficiently handle the sensor's changes in energy and mobility while improving the energy efficiency — network lifetime.

In the presence of the increasing penetration of electric vehicles (EVs) and conflict of independent optimization objectives among each electric vehicle aggregator (EVA), real-time optimal scheduling (RTOS) of large-scale EVs based on dynamic non-cooperative game approach is proposed for optimal decision makings in a dynamic pricing market. First, real-time optimal scheduling framework is designed to describe the flow of energy and information. Then, equivalent model of large-scale EVs is formulated to address “curse of dimensionality” caused by a large number of decision variables. Then, the potential game theory is used to study the existence and uniqueness of the Nash equilibrium (NE) solution. Finally, a distributed approach based on alternating direction method of multipliers (ADMM) is designed to achieve the equilibrium. Case studies demonstrate that the proposed approach achieves peak load shifting and reduces cost of EVAs significantly. Furthermore, the proposed method obtains higher-quality solution compared with other methods and is more applicable for real-time optimal scheduling of large-scale EVs due to its high computation efficiency and privacy protection.

Technology innovation in high-end equipment manufacturing (HEM) enterprises technology innovation plays an important role in supporting national economies and social development, accelerating the speed of digital transformation. Digital empowerment aggravates the dynamics, complexity, and uncertainty of technology innovation in HEM enterprises. In order to improve the innovation performance mechanism of China’s HEM enterprises, the adaptability of technology embedding and digital empowerment are introduced to further explain the direct and the moderating effect. Specifically, through a literature review and practical research, the connotation and dimensional division of digital empowerment are defined. According to empowerment tools, digital empowerment is divided into resource empowerment and structural empowerment, and according to the empowerment actor relationships, digital empowerment is divided into platform empowerment and ecological empowerment. Additionally, 436 HEM enterprises are used as research objects to build a conceptual model of the different digital empowerment dimensions, adaptability to technology embedding and technology innovation performance. The research results show that resource empowerment and structural empowerment have U–shaped effects on technology innovation performance, and platform empowerment and ecological empowerment positively affect technology innovation performance. Then, adaptability to technology embedding positively moderates the U-shaped relationship between structural empowerment and technology innovation performance. Adaptability to technology embedding positively moderates the relationship between resource empowerment, platform empowerment, ecological empowerment and technology innovation performance. The research findings deepen the connotation and dimension of digital empowerment, demonstrating the nonlinear relationship between digital empowerment and technology innovation performance of HEM enterprises. Additionally, the research expands on the new applications of adaptability to technology embedding in the digital transformation of manufacturing.

In this paper, we consider the reliable data fusion problem in a tactical environment in the presence of adversary. First, we characterize malicious behavior of compromised sensors assuming probabilistic models. Performance of the fusion process, in the presence of malicious sensors, is then quantified. The performance analysis shows that malicious sensors incur significant degradation on the fusion process. Our goal is to substantially improve reliability and robustness of data fusion in sensor networks. To this end, we introduce monitoring nodes (MN) that are distributed across a sensor network to detect, identify and isolate malicious sensors. We formulate the interaction between sensors and MN as a dynamic game with incomplete information, which provides a platform for designing reputation based data fusion. The reputation system ensures reliable data fusion by confining the fusion process to trustworthy sensors. We evaluate performance of the reputation system both by analysis and simulation.

Dynamic delay-based game approach in car and petrol supply chains under government intervention

The rapid development and distribution of digital media over the last two decades and access to this media has become crucial of being an active player in our contemporary society. The accessibility of the ICTs must be there because it is digital access which divides the society not the digital technology as technology integrates the society. So an effort is to be made to provide digital technologies to the members of the society. Simply providing access is not the only solution but also making the people empowered to use the digital technologies. Therefore, there is a need to know the digital empowerment status of the individuals by developing a tool. If the tool is not standardized and only applied then result will be questionable. Hence, a scale on digital empowerment has been developed based on summated rating (Likert technique). Digital empowerment is operationally defined as ‘a process through which an individual is making fit to the digital technology and harvesting the maximum potentials of the technology with reference to psychological, economical, legal and technical competency’. The scale consists of 38 items under the subcategory, namely, psychological (5 items), legal (3 items), economical (8 items) and technical competency (22 items) based on the critical ratio technique.