This paper introduces a distributed algorithm for sparse load shifting in demand-side management with focus on the scheduling problem of residential smart appliances. By strategy, customers' discomfort is reduced. Although there are many game theoretic models problem, computational efficiency finding Nash equilibrium that globally minimizes total energy consumption cost and peak-to-average ratio still an outstanding issue. We develop bidirectional framework solving way to substantially...

In this paper, we consider the event-triggered distributed average-consensus of discrete-time first-order multiagent systems with limited communication data rate and general directed network topology. framework digital network, each agent has a real-valued state but can only exchange finite-bit binary symbolic sequence its neighborhood agents at time step due to channels energy constraints. Novel dynamic encoder decoder for are designed, based on which control algorithm is proposed. A scheme...

This paper proposes a generalized Hopfield network for solving general constrained convex optimization problems. First, the existence and uniqueness of solutions to in Filippov sense are proved. Then, Lie derivative is introduced analyze stability using differential inclusion. The optimality solution nonsmooth problems shown be guaranteed by enhanced Fritz John conditions. convergence rate can estimated second-order energy function. effectiveness proposed evaluated on several typical used...

Communication data rates and energy constraints are two important factors that have to be considered in the coordination control of multiagent networks. Although some encoder-decoder-based consensus protocols available, there still exists a fundamental theoretical problem: how can we further reduce update rate input for each agent without changing performance? In this paper, consider problem average over directed time-varying digital networks discrete-time first-order systems with limited...

This paper proposes a second-order sliding mode-based damping controller of DFIG for interarea oscillations. The proposed control strategy aims to utilize the reactive power modulation ability stabilize system in event oscillations caused by disturbances. First, is derived based on two-area system, and then it extended multiarea systems. Compared with conventional controller, one insensitive modeling uncertainties parameter variations. Given wide variation operation points, demonstrates...

Reinforcement learning (RL) is essential for the computation of game equilibria and estimation payoffs under incomplete information. However, it has been a challenge to apply RL-based algorithms in energy trading among smart microgrids where no information concerning distribution priori available strategy chosen by each microgrid private opponents, even partners. This paper proposes new framework based on repeated that enables individually randomly choose with probability trade an...

This paper considers solving a class of optimization problems which are modeled as the sum all agents' convex cost functions and each agent is only accessible to its individual function. Communication between agents in multiagent networks assumed be limited: can interact information with neighbors by using time-varying communication channels limited capacities. A technique overcomes limitation implement quantization process interacted information. The quantized first encoded binary sequence...

Recently, game theory has been used to design optimized strategies for defending an electric power system against deliberate attacks. In this paper, we extend the current static model a more generalized framework which includes several interaction models between defenders and attackers. A new criterion of reliable systems derived. addition, two allocation algorithms have developed seek types defense tasks. The are complementary security criteria can provide useful information decision-makers...

With increasing large-scale wind farms being integrated into the power grids, transmission expansion planning (TEP) increasingly requires more flexibility to account for intermittency as well other uncertainty factors involved in process. In this study, a probabilistic TEP model is proposed planners tackle variability and associated with grid connected farms. Both load forecast output uncertainties are considered model. Other include forced outage rates of lines generators, speed correlation...

This paper considers the problem of designing adaptive learning algorithms to seek Nash equilibrium (NE) constrained energy trading game among individually strategic players with incomplete information. In this game, each player uses automaton scheme generate action probability distribution based on his/her private information for maximizing his own averaged utility. It is shown that if one admissible mixed-strategies converges NE one, then utility and quantity almost surely converge their...

Dynamic security assessment (DSA) is an important issue in modern power system analysis. This paper proposes a novel pattern discovery (PD)-based fuzzy classification scheme for the DSA. First, PD algorithm improved by integrating proposed centroid deviation analysis technique and prior knowledge of training data set. improvement can enhance performance when it applied to extract patterns from Secondly, based on results algorithm, logic-based method developed predict index given operating...