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Demand response (DR) has been recognized as a powerful tool to help mitigate power imbalances in a future smart energy system. This paper takes the point of view of a grid operator (GO) to establish an intraday resource trading framework, over which DR resources from different sectors (large industrial consumers and small- or middle-sized customers) are brought to the system level and are assessed by the GO along with the generators, with the aim of procuring the required system resources at minimal cost. Considering the distinct behaviors of the involved entities, Stackelberg game theory was adopted to analyze the coordination among the various decision makers. A unique Stackelberg equilibrium was identified that yields the optimal outcome for the resource trading game between the GO and demand-side participators. Simulation results demonstrated that the total procurement cost was minimized by applying the proposed approach. [ABSTRACT FROM AUTHOR]

A hybrid generator with a photovoltaic energy conversion system is proposed with supercapacitors and lead-acid batteries in a dc-coupled structure. The objective of this system is to supply the prescribed reactive and active power to the grid. This paper focuses on the strategy, which makes it possible to ensure a high battery state of charge and overcharge security by designing a dedicated local control system. A continuous dynamic model and a control design of the power system studied are proposed in this paper. Simulation and experimental results illustrate the performances obtained. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of distributed energy management for both generation and demand sides in a smart grid by formulating the economic dispatch and demand response in a united framework. Our main contribution is to formulate a social welfare maximization problem for a more practical scenario by taking wind power, and temporally coupled constraints of the demands into account. The complexity lies in the nonquadratic cost function of wind power, the temporally coupled constraints of the demands, and the nonconvexity of the optimization problem. Meanwhile, a smart grid has to guarantee privacy and accommodates plug-and-play features. Aiming at these challenges, we first relax an equality constraint to obtain a new convex optimization problem. Because of the coupling in the constraint, the Lagrange duality method is then adopted to decompose the problem into subproblems for generators and demands, which are regarded as agents. As a result, each agent solves its subproblem by exchanging information with only neighbor agents, and coordinates with others using the global information discovered by a distributed finite-time consensus algorithm. We also prove the convergence and optimality of the proposed distributed energy management algorithm (DEMA). Finally, simulations are performed on the IEEE 39-bus system to illustrate the performance of our DEMA. [ABSTRACT FROM AUTHOR]

Multirobot systems represent an enticing area of research with numerous real-world applications. Teams of multiple robots can achieve tasks that are more difficult or even impossible for a single robot, e.g., environment exploration, search and rescue, or surveillance operations. In a previous work, the authors developed a system for the single-operator manual control of a multirobot system. However, such teleoperation systems commonly suffer from inadequate perception of the remote environment. This paper extends the previously presented work by adding a fuzzy force-feedback (FFF) augmentation for the manual control of a multirobot system. The FFF augmentation delivers additional information to the operator. Moreover, it guides the operator toward the smooth control of the robotic group. The force feedback was generated by a system of fuzzy controllers monitoring the state of the multirobot group. The performance of the system was evaluated in a virtual environment, and the recorded forces were explored in various scenarios. The force-feedback augmentation demonstrated the following improvements: 1) operator's increased obstacle awareness and 2) improved maneuvering performance. [ABSTRACT FROM PUBLISHER]

According to the complex structure characteristics of a 330-MW water–hydrogen–hydrogen-cooled turbogenerator, the flow network within a half-axial segment of the generator was established. The total flow rate, pressure, flow rates of various ventilation ducts, and the chambers in the generator were obtained after solving the equations of the flow network. The 3-D transient electromagnetic field in the generator end was calculated, and the eddy-current losses of the end parts were gained. Using the finite volume method, the fluid and thermal mathematic and physical models for the whole end region were given. The flow velocity and the pressure values from the flow-network calculations were applied to the end region as boundary conditions, and the losses measured from electromagnetic field calculations were applied to the end parts as heat sources in the temperature field. Thus, both the distribution of the temperature of the end parts and the distribution of the fluid flow in the whole end region were obtained under rated operating conditions. Comparing the calculated temperature results with the test values, the errors meet the engineering requirement. All of the aforementioned data will provide an effective basis for accurately calculating the temperature of the end parts in a large turbogenerator. [ABSTRACT FROM PUBLISHER]