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In this paper, an agent-based decentralized control model for islanded microgrids is proposed, which consists of a two-layer control structure. The bottom layer is the electrical distribution microgrid, while the top layer is the communication network composed of agents. An agent is regarded as a local control processor together with communication devices, so agents can collect present states of distributed generators and loads, when communication lines are added between two layers. Moreover, each agent can also exchange information with its neighboring agents of the network. After information is processed according to control laws, agents adjust the production of distributed generators to which they connect. The main contributions of this paper are (i) an agent-based model for decentralized secondary control is introduced and the rules to establish the communication network are given; (ii) a systematic method is presented, which can be used to derive a set of control laws for agents from any given communication network, where only local information is needed. Furthermore, it has been seen that the output power supplied by distributed generators satisfies the load demand in the microgrid, when agents use the proposed control laws. Finally, the simulation results show that frequency and voltage fluctuations are small and meet the requirements. ).Manuscript received XX, 2014; revised XX, 2015. between two layers, and then exchanges the information with its neighboring agents. After all the information is processed according to control laws, agents adjust the output power of the DGs at the next time step in order to balance the supplies and demands in the MG.Further, we formulate the rules for how a communication network is constructed. Once an MG is given, many communication networks may be built in terms of the rules, and apparently the control laws for agents on each communication network are different. Therefore, we present a systematic method to derive a set of control laws for agents from any given communication network, where only local information is needed. Furthermore, we prove a theorem that shows the output power supplied by DGs equals the load demand in the MG, if each agent applies the control law that is derived. To evaluate the performance of our control laws, four cases are designed, in which the illumination intensity, the wind speed or/and the load demand change over time. Finally, simulations are carried out in MATLAB/Simulink and the results show that the frequency and the voltage satisfy the requirements, and the system remains stable, even in extreme conditions. Compared with a centralized control method, the proposed decentralized method only needs local information, which reduces the communication complexity.The rest of the paper is organized as follows. In Section II, the two layer control model with an agent-based communication network is introduced in detail. Using the steps and rules given, one can construct an agent-based communication network as the top layer of the control model, and ...

In this paper, cost based droop schemes are proposed, to minimize the total active power generation cost in an islanded microgrid (MG), while the simplicity and decentralized nature of the droop control are retained. In cost based droop schemes, the incremental costs of distributed generators (DGs) are embedded into the droop schemes, where the incremental cost is a derivative of the DG cost function with respect to output power. In the steady state, DGs share a single common frequency, and cost based droop schemes equate incremental costs of DGs, thus minimizing the total active power generation cost, in terms of the equal incremental cost principle. Finally, simulation results in an islanded MG with high penetration of intermittent renewable energy sources are presented, to demonstrate the effectiveness, as well as plug and play capability of the cost based droop schemes.Index Terms-Microgrid (MG), incremental cost, generation cost, cost based droop schemes, decentralized control.

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The averaging algorithm for consensus is widely used as a distributed secondary method for the control and management of microgrids. However, during each iteration it may break the system balance obtained by the primary control. In this paper, a distributed and networked method for the control and management of islanded microgrids is proposed, in which there is an agent based communication network as the top layer over a microgrid as the bottom layer. Further, a systematic method is presented to derive a set of distributed control laws for agents from any given communication network, where only nearest neighbor information is needed. The control laws consist of two terms, dynamic and fixed weights, in which the term with dynamic weights reassigns outputs of distributed generators in order to reach different targets. Moreover, this method offers a convenient way to achieve different targets of control and management by substituting a parameter in the control laws with dynamic weights. More importantly, the control laws with dynamic weights never break the system balance during iterations. We formally show that if agents apply the control laws to regulate distributed generators, their outputs will iteratively satisfy the given targets. Finally, simulations are carried out to evaluate the performance of the control laws. The results show that equal outputs, proportional outputs and the optimal incremental cost are obtained. Moreover, the voltage and frequency are still stable, when fluctuations of load demand and environmental conditions are considered.

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