Sharif Digital Repository

This paper analyzes the oligopolistic equilibria of multiple price-maker agents in performance-based regulation (PBR) markets. In these markets, there are price-maker agents representing some frequency regulation (FR) providers and a number of independent price-taker FR providers. A model of equilibrium problem with equilibrium constraints (EPECs) is employed in this paper to study the equilibria of a PBR market in the presence of price-maker agents and price-taker FR providers. Due to the incorporation of the FR providers' dynamics, the proposed model is reformulated as a mixed-integer linear programming (MILP) problem over innovative mathematical techniques. An optimal equilibrium point is... 

Multiple energy carriers (MECs) have been broadly engrossing power system planners and operators toward a modern standpoint in power system studies. Energy hub, though playing an undeniable role as the intermediate in implementing the MECs, still needs to be put under examination in both modeling and operating concerns. Since wind power continues to be one of the fastest-growing energy resources worldwide, its intrinsic challenges should be also treated as an element of crucial role in the vision of future energy networks. In response, this paper aims to concentrate on the online economic dispatch (ED) of MECs for which it provides a probabilistic ED optimization model. The presented model... 

Providing an efficient resource allocation mechanism is a challenge to computational grid due to large-scale resource sharing and the fact that Grid Resource Owners (GROs) and Grid Resource Consumers (GRCs) may have different goals, policies, and preferences. In a real world market, various economic models exist for setting the price of grid resources, based on supply-and-demand and their value to the consumers. In this paper, we discuss the use of multiagent-based negotiation model for interaction between GROs and GRCs. For realizing this approach, we designed the Market- and Behavior-driven Negotiation Agents (MBDNAs). Negotiation strategies that adopt MBDNAs take into account the... 

There are many practical situations where it is desirable or even required to achieve stable convergence in the finite-time domain. In this paper, a simple distributed continuous-time protocol is introduced that guarantees finite-time consensus in networks of autonomous agents. Protocol convergence in weighted directed/undirected and fixed/switching networks is explored based on a Lyapunov analysis. The stability of the system and the solvability of the consensus algorithm are proved for network topologies that contain a spanning tree frequently enough over contiguous time intervals. The decision value for different topologies and for multi-rate integrator agents is investigated, and a novel... 

Femtocell networks are a common means of offloading in current mobile networks. Game theoretic and learning-based self-organization schemes are known as two viable approaches for interference control in co-existing macro/femtocell networks. Nevertheless, extensions of these schemes to concurrent multi-agent scenarios often face several challenges including high computational complexity, cyclic behaviors, and lack of convergence. This paper addresses such challenges by introducing local games based on a graph representation of the network. The goal of the games is to optimize the aggregate network capacity through power control. Fairness among femtocells and quality of service (QoS) for... 

Control of collective behavior is one of the most desirable goals in many applications related to social networks analysis and mining. In this work we propose a simple yet effective algorithm to control opinion formation in complex networks. We aim at finding the best spreaders whose connection to a reasonable number of informed agents results in the best performance. We consider an extended version of the bounded confidence model in which the uncertainty of each agent is adaptively controlled by the network. A number of informed agents with the desired opinion value is added to the network and create links with other agents such that large portion of the network follows their opinions. We... 

The deployment of multi-agent systems in presence of obstacle deals with autonomous motion of agents toward a specified target by sensing each other and boundaries of obstacles. In this paper, asynchronous, scalable, distributed algorithm is used to deploy agents. Boundaries of obstacles are modeled by virtual agents. Algorithm was implemented by solving continuous n-median problem called generalized Fermat-Weber problem. It is shown that deployment is performed when position of real agents are the geometric median of their Voronoi cells. Simulation results show the validity of the proposed algorithm very well  

We consider the computational complexity of pure Nash equilibria in graphical games. It is known that the problem is NP-complete in general, but tractable (i.e., in P) for special classes of graphs such as those with bounded treewidth. It is then natural to ask: is it possible to characterize all tractable classes of graphs for this problem? In this work, we provide such a characterization for the case of bounded in-degree graphs, thereby resolving the gap between existing hardness and tractability results. In particular, we analyze the complexity of PURE-GG(C, -), the problem of deciding the existence of pure Nash equilibria in graphical games whose underlying graphs are restricted to class... 

In this paper a fuzzy control strategy of autonomous multiagent systems is presented. The main purpose is to obtain an improvement on the results of designed sliding mode controllers in previous articles using supervisory fuzzy controller. Similarly, a quasi-static swarm model in ndimensional space is introduced wherein the inter-individual interactions are based on artificial potential functions; and the motions of members are in direction with the negative gradient of the combined potentials which are the result of a balance between inter-individual interactions and the simultaneous interactions of the swarm members with their environment. Then a general model for vehicle dynamics of each... 

Multi-agent systems (MAS) try to formulate dynamic world which surround human being in every aspect of his life. One of the important challenges encountered in multiagent systems is the credit assignment problem, simply means distributing the result of the work of a group of agents, such that every agent will have the capability of individual learning. This paper presents the result of a solution suggested for multi-agent credit assignment problem. With the help of observing history of credit assignment in the environment, we will understand what actions are reward-deserving. Results are reported on a multi agent domain, addition agents. © 2009 IEEE  

This paper proposes a novel distributed noise-resilient secondary control for voltage and frequency restoration of islanded microgrid inverter-based distributed generations (DGs) with an additive type of noise. The existing distributed methods commonly are designed as secondary control system systems that operate on the assumption of ideal communication networks among DGs. However, the channels are prone to stochastic noise, whereas each DG obtains noisy measurements of the states of its neighbors via environmental noises. The existing distributed noise-resilient methods, ignore a complete model of the system. In contrast, this paper proposes consensus protocols that take into account both... 

A facility location problem deals with locating the best place for a group of facilities, among distinct demand points, minimizing a certain locational optimization function. In this paper, distributed, asynchronous, and scalable algorithms are presented for solving a facility location problem known as continuous n-median problem (generalized Fermat-Weber problem) via multi-agent robotic systems. The algorithms are discussed both in continuous and discrete time domain, and their validity is proved. It is also shown that the solution of this facility location problem is the set of points that are the geometric medians of their corresponding Voronoi cells  

Grid computing is a type of parallel and distributed system that provides the possibility of sharing, choosing and collecting the autonomous resources (such as computer, software, databases, and equipments) that are distributed geographically. Resource discovery is one of the key subjects in distributed systems and especially Grids. We should consider that Grid consists of different applications that each of them consist of different hardware and software resources, therefore recognizing these resources is important in a Grid system. Classical approaches to Grid resource discovery are either centralized or hierarchical [1] (and will maybe prove inefficient as the scale of Grid systems... 

In this article, a novel cooperative secondary voltage/frequency control considering time-varying delays and noises in fading channels is presented for an autonomous alternating current (AC) voltage sourced-based converter (VSC)-based microgrid (MG), including inverter-interfaced distributed generations (DGs). Fading phenomenon makes complex random fluctuations on the voltage and frequency of every DG received from its neighbor DGs. In multi-agent cooperative systems, in addition to the total additive noise and time-variant delay, a multiplicative complex random variable is considered to model the main received signal and its replicas due to multipath propagation. The proposed... 

This paper proposes a distributed attack detection and mitigation technique based on distributed estimation over a multi-agent network, where the agents take partial system measurements susceptible to (possible) biasing attacks. In particular, we assume that the system is not locally observable via the measurements in the direct neighborhood of any agent. First, for performance analysis in the attack-free case, we show that the proposed distributed estimation is unbiased with bounded mean-square deviation in steady-state. Then, we propose a residual-based strategy to locally detect possible attacks at agents. In contrast to the deterministic thresholds in the literature assuming an upper... 

Restructuring and privatization in power systems have resulted in a fundamental transition of conventional distribution systems into modern multi-agent systems. In these structures, each agent of the distribution system would independently operate its local resources. In this regard, uncertainties associated with load demands and renewable energy sources could challenge the operational scheduling conducted by each agent. Therefore, this paper aims to develop a distributed operational management for multi-agent distribution systems taking into account the uncertainties of each agent. The developed framework relies on alternating direction method of multipliers (ADMM) to coordinate the... 

Distribution networks are undergoing a fundamental transition due to the expansion of flexible resources as well as renewable energy sources in the system. In this regard, multi-agent structures are developed in modern distribution systems to facilitate the independent operation of local resources. Nevertheless, the non-coordinated operation of independent agents could result in a deviation between the real-time power purchased from transmission network and the day-ahead scheduling. Consequently, this paper aims to provide a novel framework that enables the decentralized management of multi-agent distribution systems, while coordinating the real-time power request and the day-ahead... 

This paper develops a novel insight and procedure that includes a variety of algorithms for finding the best solution in a structured multi-agent system with internal communications and a global purpose. In other words, it finds the optimal communication structure among agents and the optimal policy in this structure. First, a unique reinforcement learning algorithm is proposed to find the optimal policy of each agent in a fixed structure with non-linear function approximators like artificial neural networks (ANN) and with eligibility traces. Secondly, a mechanism is presented to perform self-organization based on the information of the learned policy. Finally, an algorithm that can discover...