Agent-Based Decentralized Control Method for Islanded Microgrids

In this paper, an agent-based decentralized control model for islanded microgrids (MGs) is proposed, which consists of a two-layer control structure. The bottom layer is the electrical distribution MG, 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 (DGs) 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 DGs to which they connect. Further, a systematic method is presented, which can be used to derive a set of control laws for agents from any given communication network, after the rules to establish the communication network are given. Furthermore, it has been seen that the output power supplied by DGs satisfies the load demand in the MG when agents use the proposed control laws. Finally, the simulation results show that frequency and voltage fluctuations are small and meet the requirements.Qiang L, Feixiong Chen, Minyou Chen, Josep M. Guerrero, Derek Abbot

Multiagent-Based Reactive Power Sharing and Control Model for Islanded Microgrids

In islanded microgrids (MGs), the reactive power cannot be shared proportionally among distributed generators (DGs) with conventional droop control, due to the mismatch in feeder impedances. For the purpose of proportional reactive power sharing, a multiagent system (MAS)-based distributed control model for droop-controlled MGs is proposed. The proposed control model consists of two layers, where the bottom layer is the electrical distribution MG, while the top layer is a communication network composed of agents. Moreover, agents on the communication network exchange the information acquired from DGs with neighbors, and calculate set points for DGs they connect to, according to the control laws. Furthermore, a theorem is demonstrated, which yields a systematic method to derive the control laws from a given communication network. Finally, three cases are carried out to test the performance of the control model, in which the uncertainty of intermittent DGs, variations in load demands, as well as impacts of time delays are considered. The simulation results demonstrate the effectiveness of the control model in proportional reactive power sharing, and the plug and play capability of the control model is also verified.Feixiong Chen, Minyou Chen, Qiang Li, Kaikai Meng, Josep M. Guerrero, Fellow and Derek Abbot

Networked and Distributed Control Method with Optimal Power Dispatch for Islanded Microgrids

In this paper, a two-layer network and distributed control method is proposed, where there is a top-layer communication network over a bottom-layer microgrid. The communication network consists of two subgraphs, in which the first is composed of all agents, while the second is only composed of controllable agents. The distributed control laws derived from the first subgraph guarantee the supply-demand balance, while further control laws from the second subgraph reassign the outputs of controllable distributed generators, which ensure active and reactive power are dispatched optimally. However, for reducing the number of edges in the second subgraph, generally a simpler graph instead of a fully connected graph is adopted. In this case, a near-optimal dispatch of active and reactive power can be obtained gradually, only if controllable agents on the second subgraph calculate set points iteratively according to our proposition. Finally, the method is evaluated over seven cases via simulation. The results show that the system performs as desired, even if environmental conditions and load demand fluctuate significantly. In summary, the method can rapidly respond to fluctuations resulting in optimal power sharing

Cost-Based Droop Schemes for Economic Dispatch in Islanded Microgrids

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 a 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.Feixiong Chen, Minyou Chen, Qiang Li, Kaikai Meng, Yongwei Zheng, Josep M. Guerrero, Derek Abbot

A temperature gradient based Condition Estimation Method for IGBT Module

The paper presents a temperature gradient based method for device state evaluation, taking the insulated Gated Bipolar Transistor (IGBT) modules as an example investigation. Firstly, theoretical basis of this method is presented and the results from example calculation on temperature gradient indicate that the increased thermal resistance and power loss of IGBT modules would increase the temperature gradient. Then an electrical-thermal- mechanical finite element method (FEM) model of IGBT modules, which takes the material temperature-dependent characteristic into account, is utilized to estimate the temperature gradient distribution for both healthy and fatigue conditions. It is found that the temperature gradient varies with power loss. Furthermore, both the experimental and simulation investigation on the temperature gradient for different conditions were conducted, and it is concluded that the temperature gradient can not only track the change of power loss, but have a better sensitivity compared with temperature distribution. In addition, the temperature gradient can reflect the defects location and distinguish failures degree. In the end the influence on the temperature gradient distribution caused by solder fatigue, void and delamination are discussed

Quantum Strategies Win in a Defector-Dominated Population

Quantum strategies are introduced into evolutionary games. The agents using quantum strategies are regarded as invaders whose fraction generally is 1% of a population in contrast to the 50% defectors. In this paper, the evolution of strategies on networks is investigated in a defector-dominated population, when three networks (Regular Lattice, Newman-Watts small world network, scale-free network) are constructed and three games (Prisoners' Dilemma, Snowdrift, Stag-Hunt) are employed. As far as these three games are concerned, the results show that quantum strategies can always invade the population successfully. Comparing the three networks, we find that the regular lattice is most easily invaded by agents that adopt quantum strategies. However, for a scale-free network it can be invaded by agents adopting quantum strategies only if a hub is occupied by an agent with a quantum strategy or if the fraction of agents with quantum strategies in the population is significant.Comment: 8 pages, 7figure

Coevolution of quantum and classical strategies on evolving random networks

We study the coevolution of quantum and classical strategies on weighted and directed random networks in the realm of the prisoners dilemma game. During the evolution, agents can break and rewire their links with the aim of maximizing payoffs, and they can also adjust the weights to indicate preferences, either positive or negative, towards their neighbors. The network structure itself is thus also subject to evolution. Importantly, the directionality of links does not affect the accumulation of payoffs nor the strategy transfers, but serves only to designate the owner of each particular link and with it the right to adjust the link as needed. We show that quantum strategies outperform classical strategies, and that the critical temptation to defect at which cooperative behavior can be maintained rises, if the network structure is updated frequently. Punishing neighbors by reducing the weights of their links also plays an important role in maintaining cooperation under adverse conditions. We find that the self-organization of the initially random network structure, driven by the evolutionary competition between quantum and classical strategies, leads to the spontaneous emergence of small average path length and a large clustering coefficient

Distributed Event-Triggered Voltage Control with Limited Re-Active Power in Low Voltage Distribution Networks

A high proportion of photovoltaic (PV) connections to a low-voltage distribution network (LVDN) causes serious voltage problems. In order to ensure voltage stability for renewable energy networks, we propose a distributed reactive voltage control strategy that is event-triggered. The voltage information of the PV nodes is transmitted to the upper layer of the communication network, where the agent calculates the output set value of the PV inverter. The underlying control strategy is based on the voltage sensitivity matrix, and the upper-level control strategy is based on an event-triggered consensus protocol. This strategy can accommodate the requirements for multi-time modeling and control. We verified the convergence of the event-triggered control algorithm using numerical analysis and proved the reduction of the communication times. We conducted case studies and simulation experiments to verify the effectiveness of our proposed voltage control strategies

Distributed Event-Triggered Voltage Control with Limited Re-Active Power in Low Voltage Distribution Networks

A high proportion of photovoltaic (PV) connections to a low-voltage distribution network (LVDN) causes serious voltage problems. In order to ensure voltage stability for renewable energy networks, we propose a distributed reactive voltage control strategy that is event-triggered. The voltage information of the PV nodes is transmitted to the upper layer of the communication network, where the agent calculates the output set value of the PV inverter. The underlying control strategy is based on the voltage sensitivity matrix, and the upper-level control strategy is based on an event-triggered consensus protocol. This strategy can accommodate the requirements for multi-time modeling and control. We verified the convergence of the event-triggered control algorithm using numerical analysis and proved the reduction of the communication times. We conducted case studies and simulation experiments to verify the effectiveness of our proposed voltage control strategies