The increasing integration of the distributed renewable energy sources highlights the requirement to design various control strategies for microgrids (MGs) and microgrid clusters (MGCs). The multiagent system (MAS)-based distributed coordinated control strategies show the benefits to balance the power and energy, stabilize voltage and frequency, achieve economic and coordinated operation among the MGs and MGCs. However, the complex and diverse combinations of distributed generations (DGs) in MAS increase the complexity of system control and operation. In order to design the optimized configuration and control strategy using MAS, the topology models and mathematic models such as the graph topology model, noncooperative game model, the genetic algorithm, and particle swarm optimization algorithm are summarized. The merits and drawbacks of these control methods are compared. Moreover, since the consensus is a vital problem in the complex dynamical systems, the distributed MAS-based consensus protocols are systematically reviewed. On the other hand, the communication delay issue, which is inevitable no matter in the low- or high-bandwidth communication networks, is crucial to maintain the stability of the MGs and MGCs with fixed and random delays. Various control strategies to compensate the effect of communication delays have been reviewed, such as the neural network-based predictive control, the weighted average predictive control, the gain scheduling scheme, and synchronization schemes based on the multitimer model for the case of fixed communication delay, and the generalized predictive control, networked predictive control, model predictive control, Smith predictor, $H_{\infty}$ -based control, sliding mode control for the random communication delay scenarios. Furthermore, various control methods have been summarized to describe switching topologies in MAS with different objectives, such as the plug-in or plug-out of DGs in an MG, and the plug-in or plug-out of MGs in an MGC, and multiagent-based energy coordination and the economic dispatch of the MGC. Finally, the future research directions of the multiagent-based distributed coordinated control and optimization in MGs and MGCs are also presented.

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MAS-Based Distributed Coordinated Control and Optimization in Microgrid and Microgrid Clusters: A Comprehensive Overview

Recently, cloud manufacturing has attracted much attention from both academic and industry communities. Manufacturing cloud service composition and optimization is critical to the optimal resources allocation in cloud manufacturing. Since there are many manufacturing cloud services available with similar functions but different quality of service (QoS), and with potential quality correlations among them, such correlations must to be considered for manufacturing cloud service composition. In this paper, a correlation-aware manufacturing cloud service description model is presented to characterize the QoS dependence of an individual service on other related services. Based on such a model, a service correlation mapping model is proposed for getting correlation QoS values among services automatically. In addition, an effective approach for the correlation-aware optimal service selection is proposed based on a genetic algorithm. A case study indicates that services composition of higher quality can be obtained when such correlations are considered. And the effectiveness and efficiency of the proposed approach are demonstrated via simulation studies.

Correlation-aware QoS modeling and manufacturing cloud service composition

A virtual enterprise is an emerging business cooperation model which allows rapid response to the unpredictable market behavior and opportunity. For service oriented enterprises, where computing resources are encapsulated as services and published online, establishing a virtual enterprise can be regarded as a process of service composition. As there are increasing numbers of available services providing similar functionalities but with different quality values, and with potential business correlations among them, it is not trivial to orchestrate a composite service with optimal overall quality of service (QoS). In this paper, we formally propose a business correlation model including both quality correlations and selection correlations, and then present an efficient approach for correlation-driven QoS-aware optimal service selection based on a genetic algorithm. The genetic algorithm is tailored with niching technology, a repair operator and a penalty mechanism. The effectiveness and efficiency of the approach are demonstrated via empirical studies at last.

A correlation-driven optimal service selection approach for virtual enterprise establishment

Product modelling is an essential issue in the configurable product design. Many attempts have been made for modelling the configurable products. However, most of conducted research considers the configurable product modelling as an arrangement problem of a predefined set of components into a valid product structure. This paper considers configuration not only as a structural problem but also as a collaborative design problem. Product configuration must consider explicitly different actors and their perspectives influencing simultaneously the design of configurable products. Solving product configuration problems requires collaboration of actors from multiple distributed views. Therefore, from process and product point of views, engineering design of configurable products can be assisted by multi-agents systems. Following up this consideration, this paper proposes a Fuzzy Configuration Grammar based agents to assist collaborative and distributed design for configuration. Based on the distributed fuzzy models, fuzziness of interactions during the collaborative and distributed design for configuration, a computational approach for product configuration is developed. Modelling and implementation of an agent-based system, called G-APIC (Grammars based Agents for Product Integrated Configuration), is presented. In this agent-based system, there are four communities of agents: requirement community of agents, function community of agents, physical solution community of agents and process constraint community of agents. A fuzzy set of consensual physical solution agents, a sub community of alternative physical solution agents satisfying both customer's requirements and different process views constraints, emerges from intra and inter-communities interactions of agents. Then, the proposed Fuzzy Configuration Grammar allows the interactions between these fuzzy consensual solution agents. The optimal product configuration, a fuzzy set of interacted consensual solution agents, emerges from these interactions. A case study illustrates the proposed approach.

A fuzzy configuration multi-agent approach for product family modelling in conceptual design

Manufacturing process monitoring systems is evolving from centralised bespoke applications to decentralised reconfigurable collectives. The resulting cyber-physical systems are made possible through the integration of high power computation, collaborative communication, and advanced analytics. This digital age of manufacturing is aimed at yielding the next generation of innovative intelligent machines. The focus of this research is to present the design and development of a cyber-physical process monitoring system; the components of which consist of an advanced signal processing chain for the semi-autonomous process characterisation of a CNC turning machine tool. The novelty of this decentralised system is its modularity, reconfigurability, openness, scalability, and unique functionality. The function of the decentralised system is to produce performance criteria via spindle vibration monitoring, which is correlated to the occurrence of sequential process events via motor current monitoring. Performance criteria enables the establishment of normal operating response of machining operations, and more importantly the identification of abnormalities or trends in the sensor data that can provide insight into the quality of the process ongoing. The function of each component in the signal processing chain is reviewed and investigated in an industrial case study.

Cyber physical process monitoring systems

This paper offers a service-oriented architecture (SOA) for ontology-based multi-agent system (MAS) negotiations in the context of virtual enterprises (VEs). The objective of this paper is fourfold. First, it is to design a SOA which utilizes ontology and MAS to provide a distributed and interoperable environment for automated negotiations in VE. In this architecture, individual ontologies for both the VE initiator and its potential partners are constructed to describe and store resources and service knowledge. Second, a series of semantic ontology matching methods are developed to reach agents' interoperability during the negotiation process. Third, correspondence-based extended contract net protocol is presented, which provides basic guidelines for agents' reaching mutual understandings and service negotiation. Last, a fuzzy set theory based knowledge reuse approach is proposed to evaluate the current negotiation behaviors of the VE partners. A walkthrough example is presented to illustrate the methodologies and system architecture proposed in this paper.

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Gong Wang

Papers

Service-oriented architecture for ontologies supporting multi-agent system negotiations in virtual enterprise