Does search boost efficiency?

Poaching externality, arising from job-to-job turnovers, implies that a planner should allocate fewer resources to costly job creations. However, these search efforts increase competition among employers, and this could in turn internalize the externality, whereas the congestion externality requires a unit-elastic matching function

Urbanization, inequality and property prices : equilibrium pricing and transaction in the Chinese housing market

The particularly overheated Chinese housing market, with its soaring property prices, has attracted a large amount of research. We point out three of its striking empirical features, which current literature leaves unexplored: co-existence of steady growth of real transaction price and excess supply, accelerations in price-to-income ratio, and significantly strong positive correlation between real transaction prices and income inequality. A search-equilibrium model is built to explain these facts. Heterogeneous buyers and homogeneous sellers randomly search for partners to trade in a frictional property market. The search equilibrium of the property market is either a high-price-and-low-transaction elitist matching equilibrium, or a low-price-and-high-transaction pooled matching equilibrium. The terms of trade determine which equilibrium arises. Empirical observations argue for the development of China's property market through evolution from a pooled matching equilibrium to an elitist matching equilibrium. We set out to show that the market equilibrium is always inefficient, due to crowding out externalities and market incompleteness. Policy experiments support redistributive tax, as a means to improve social welfare

Cyber-Resilient Self-Triggered Distributed Control of Networked Microgrids Against Multi-Layer DoS Attacks

Networked microgrids with high penetration of distributed generators have ubiquitous remote information exchange, which may be exposed to various cyber security threats. This paper, for the first time, addresses a consensus problem in terms of frequency synchronisation in networked microgrids subject to multi-layer denial of service (DoS) attacks, which could simultaneously affect communication, measurement and control actuation channels. A unified notion of Persistency-of-Data-Flow (PoDF) is proposed to characterise the data unavailability in different information network links, and further quantifies the multi-layer DoS effects on the hierarchical system. With PoDF, we provide a sufficient condition of the DoS attacks under which the consensus can be preserved with the proposed edgebased self-triggered distributed control framework. In addition, to mitigate the conservativeness of offline design against the worst-case attack across all agents, an online self-adaptive scheme of the control parameters is developed to fully utilise the latest available information of all data transmission channels. Finally, the effectiveness of the proposed cyber-resilient self-triggered distributed control is verified by representative case studies

Event-triggered distributed MPC for resilient voltage control of an islanded microgrid

This paper addresses the problem of distributed secondary voltage control of an islanded microgrid (MG) from a cyber-physical perspective. An event-triggered distributed model predictive control (DMPC) scheme is designed to regulate the voltage magnitude of each distributed generators (DGs) in order to achieve a better trade-off between the control performance and communication and computation burdens. By using two novel event triggering conditions that can be easily embedded into the DMPC for the application of MG control, the computation and communication burdens are significantly reduced with negligible compromise of control performance. In addition, to reduce the sensor cost and to eliminate the negative effects of non-linearity, an adaptive non-asymptotic observer is utilized to estimate the internal and output signals of each DG. Thanks to the deadbeat observation property, the observer can be applied periodically to cooperate with the DMPC-based voltage regulator. Finally, the effectiveness of the proposed control method has been tested on a simple configuration with 4 DGs and the modified IEEE-13 test system through several representative scenarios

Event-triggered distributed model predictive control for resilient voltage control of an islanded microgrid

This article addresses the problem of distributed secondary voltage control of an islanded microgrid (MG) from a cyber‐physical perspective. An event‐triggered distributed model predictive control (DMPC) scheme is designed to regulate the voltage magnitude of each distributed generators (DGs) in order to achieve a better trade‐off between the control performance and communication and computation burdens. By using two novel event triggering conditions that can be easily embedded into the DMPC for the application of MG control, the computation and communication burdens are significantly reduced with negligible compromise of control performance. In addition, to reduce the sensor cost and to eliminate the negative effects of nonlinearity, an adaptive nonasymptotic observer is utilized to estimate the internal and output signals of each DG. Thanks to the deadbeat observation property, the observer can be applied periodically to cooperate with the DMPC‐based voltage regulator. Finally, the effectiveness of the proposed control method has been tested on a simple configuration with four DGs and the modified IEEE‐13 test system through several representative scenarios

Managing financing risk in capacity investment under green supply chain competition

In this paper, we study the asymmetric duopoly models of competing supply chains with financing uncertainty. The financing uncertainty of the green supply chain’s capacity investment could be available as complete or incomplete information to the traditional supply chain. By analyzing and comparing the optimal quantities, optimal prices, and optimal profits of both cases, we find that the financing uncertainty of capacity investment does not affect either chain’s choices of equilibrium quantities and prices in the complete information case. If this information is incomplete for the traditional supply chain, financing uncertainty plays an important role in determining optimal quantities and optimal prices, together with the lending interest rate. To encourage the use of environmentally friendly technologies, government should use per-unit subsidies if the green supply chain suffers the cost disadvantage, and should encourage financial institutions to provide preferential loans to the green supply chain that suffers manufacturing or retailing capacity restrictions

Fixed-Time Convergent Distributed Observer Design of Linear Systems: A Kernel-Based Approach

The robust distributed state estimation for a class of continuous-time linear time-invariant systems is achieved by a novel kernel-based distributed observer, which, for the first time, ensures fixed-time convergence properties. The communication network between the agents is prescribed by a directed graph in which each node involves a fixed-time convergent estimator. The local observer estimates and broadcasts the observable states among neighbours so that the full state vector can be recovered at each node and the estimation error reaches zero after a predefined fixed time in the absence of perturbation. This represents a new distributed estimation framework that enables faster convergence speed and further reduced information exchange compared to a conventional Luenberger-like approach. The ubiquitous timevarying communication delay across the network is suitably compensated by a prediction scheme. Moreover, the robustness of the algorithm in the presence of bounded measurement and process noise is characterised. Numerical simulations and comparisons demonstrate the effectiveness of the observer and its advantages over the existing methods