DC microgrids (MGs) have been gaining a continually increasing interest over the past couple of years both in academia and industry. The advantages of dc distribution when compared to its ac counterpart are well known. The most important ones include higher reliability and efficiency, simpler control and natural interface with renewable energy sources, and electronic loads and energy storage systems. With rapid emergence of these components in modern power systems, the importance of dc in today's society is gradually being brought to a whole new level. A broad class of traditional dc distribution applications, such as traction, telecom, vehicular, and distributed power systems can be classified under dc MG framework and ongoing development, and expansion of the field is largely influenced by concepts used over there. This paper aims first to shed light on the practical design aspects of dc MG technology concerning typical power hardware topologies and their suitability for different emerging smart grid applications. Then, an overview of the state of the art in dc MG protection and grounding is provided. Owing to the fact that there is no zero-current crossing, an arc that appears upon breaking dc current cannot be extinguished naturally, making the protection of dc MGs a challenging problem. In relation with this, a comprehensive overview of protection schemes, which discusses both design of practical protective devices and their integration into overall protection systems, is provided. Closely coupled with protection, conflicting grounding objectives, e.g., minimization of stray current and common-mode voltage, are explained and several practical solutions are presented. Also, standardization efforts for dc systems are addressed. Finally, concluding remarks and important future research directions are pointed out.

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DC Microgrids—Part II: A Review of Power Architectures, Applications, and Standardization Issues

A survey on smart grid technologies and applications

This paper proposes a novel game-theoretic model for peer-to-peer (P2P) energy trading among the prosumers in a community. The buyers can adjust the energy consumption behavior based on the price and quantity of the energy offered by the sellers. There exist two separate competitions during the trading process: 1) price competition among the sellers; and 2) seller selection competition among the buyers. The price competition among the sellers is modeled as a noncooperative game. The evolutionary game theory is used to model the dynamics of the buyers for selecting sellers. Moreover, an M-leader and N-follower Stackelberg game approach is used to model the interaction between buyers and sellers. Two iterative algorithms are proposed for the implementation of the games such that an equilibrium state exists in each of the games. The proposed method is applied to a small community microgrid with photo-voltaic and energy storage systems. Simulation results show the convergence of the algorithms and the effectiveness of the proposed model to handle P2P energy trading. The results also show that P2P energy trading provides significant financial and technical benefits to the community, and it is emerging as an alternative to cost-intensive energy storage systems.

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Peer-to-Peer Energy Trading in a Prosumer-Based Community Microgrid: A Game-Theoretic Model

This paper proposes a distributed mechanism for energy trading among microgrids in a competitive market. We consider multiple interconnected microgrids in a region where, at a given time, some microgrids have superfluous energy for sale or to keep in storage facilities, whereas some other microgrids wish to buy additional energy to meet local demands and/or storage requirements. Under our approach, sellers lead the competition by independently deciding the amount of energy for sale subject to a tradeoff between the attained satisfaction from the received revenue and that from the stored energy. Buyers follow the sellers' actions by independently submitting a unit price bid to the sellers. Correspondingly, the energy is allocated to the buyers in proportion to their bids, whereas the revenue is allocated to the sellers in proportion to their sales. We study the economic benefits of such an energy trading mechanism by analyzing its hierarchical decision-making scheme as a multileader–multifollower Stackelberg game. We show that distributing the energy based on a well-defined utility function converges to a unique equilibrium solution for maximizing the payoff of all participating microgrids. This game-theoretic study provides an incentive for energy trading among microgrids in future power grids.

Distributed Energy Trading in Microgrids: A Game-Theoretic Model and Its Equilibrium Analysis

The microgrid concept is gaining popularity with the proliferation of distributed generation. Control techniques in the microgrid are an evolving research topic in the area of microgrids. A large volume of survey articles focuses on the control techniques of the microgrid; however, a systematic survey of the hierarchical control techniques based on different microgrid architectures is addressed very little. The hierarchy of control in microgrid comprises three layers, which are primary, secondary, and tertiary control layers. A review of the primary and secondary control strategies for the ac, dc, and hybrid ac–dc microgrid is addressed in this paper. Furthermore, it includes the highlights of the state-of-the-art control techniques and evolving trends in the microgrid research.

Control Techniques in AC, DC, and Hybrid AC–DC Microgrid: A Review

DC microgrids (DCMGs) are becoming more popular in modern power systems due to their simplicity, efficiency, and reliability. Autonomous control of DCMG is primarily based on the droop control. Typically, the droop coefficients of each distributed generator (DG) are fixed and assigned based on their capacity. This article introduces a multiobjective optimization (MOO) based intelligent computation approach to derive the optimal droop coefficients for DGs in an islanded DCMG. The proposed approach takes into consideration not only the capacities of the DGs but also the system voltage regulation, system total loss minimization, and enhanced current sharing among the DGs. The Pareto optimal front of the constructed MOO problem is obtained using the elitist nondominated sorting genetic algorithm (NSGA II). A best compromise solution is extracted from the generated Pareto optimal front by employing a fuzzy membership function approach. Moreover, a state feedback linearization based controller is introduced to facilitate the control actions to experimentally validate the effectiveness and the applicability of the generated optimal droop relationships. The proposed approach was tested with a parallel connected dc 9-bus system, IEEE 30-bus system, and experimentally validated on a 5-bus system. However, the same concept can be extended to any other bus system without loss of generality.

Multiobjective Optimization of Droop-Controlled Distributed Generators in DC Microgrids

An interconnected electrical network that has electrical sources and loads makes a small-scale power system (SSPS). These systems have low inertia, which makes the modeling and controlling of them dissimilar to that of traditional large-scale power systems. A differential game-theoretic framework allows for the design of the distributed control structures for SSPS with player dynamics under simultaneous player movement. Under this approach, both loads and sources are defined as players in the system to form a game of energy between them. Game-theory-based modeling is necessary in this case since it optimizes the multiobjective optimization problem based on local control without the need for a communication channel. In this paper, a differential game-theoretic approach is used for path optimization of load players during a cold start that minimizes losses and achieves a desired steady-state operating point. Example simulation cases are obtained for a dc power system that has nine buses and dynamic load players. This power system is used to show the applicability, effectiveness, and performances of the proposed concepts. However, this method can be easily applied to other types of larger dc or ac networks. Finally, experimental results are yielded to validate the theoretical results and show that the proposed controller has higher performance compared with the traditional proportional-integral controller during transients.

Game-Theoretic Cold-Start Transient Optimization in DC Microgrids

This paper presents a game-theoretic communication structure, which is a network constructed among distributed controllers in the microgrid. This helps to share local controller information, such as control input, individual objectives among controllers, and finds a better optimized cost for the individual objectives. The modeling follows a game-theoretic framework for the energy conversion and control elements inside small-scale power systems (SSPS) or microgrids. These elements form teams to optimize performance and operation based on available information and communication. The team players are able to minimize a common objective when there is communication, and shift to the individual local objectives when communication fails. This paper also presents analysis to determine the minimal performance standards for the given level of communicated information. Then it shows optimal information mixing for team player modeling. In addition, a Stackelberg model is proposed for the microgrid with a leader-follower modeling approach. The last part of this paper shows possible examples with network contingency study with team player participation.

Game-Theoretic Communication Structures in Microgrids

Along with the rapid growth in green energy utilization, microgrids are becoming an interesting part of the future power systems. This paper presents a transient trajectory optimization of parallel connected inverter system in an islanded microgrid. Optimal state and control transient trajectories are generated which drive each individual inverter from given initial conditions to their respective desired steady state equilibrium. This trajectory optimization is performed in decentralized manner and they are the open loop, local optimal control signals of the inverters. The Pontryagin’s minimum principle is employed to obtain the optimal state and control signal trajectories. Then, a stability analysis of the system with the local optimal control signals is done by a Lyapunov approach. Dynamic model of the system and the optimum trajectories are obtained in the d-q reference frame. Two example microgrid systems, one with three inverters and the other one with five inverters, were used to demonstrate the effectiveness and performance of the proposed approach which can be easily extended to any type of microgrid such as AC, DC, hybrid microgrids in both islanded or grid connected mode.

Transient Optimization of Parallel Connected Inverters in Islanded AC Microgrids

DC power systems with multiple buses for redundancy are more reliable and provide reconfiguration options. A game-theoretic-based modeling approach for bus selection is proposed in this paper, which is based on local information of the player and does not require a centralized controller. The initial section provides the modeling and optimization of a single-input player. This modeling mainly follows on the players' local objectives and discrete choices of bus connections. Therefore, in this case, the controller obtains Nash equilibrium (NE) for the pure strategy game. Then, the approach is extended for the integration of global objectives with minimal communication. In addition, different objective priorities are integrated into the optimization routine. Next, the analysis is extended to multi-input player situations which are related to the class of mixed and continuous strategy games. This modeling is important, since the payoff matrix approach does not find an NE in all cases. Finally, the bus selection modeling is carried out by taking the system dynamics into account. This is important for the cases where the system has sudden load or source fluctuations. Experimental results are obtained, which validate the theory.

Nishantha C. Ekneligoda

Papers

Multiobjective Optimization of Droop-Controlled Distributed Generators in DC Microgrids

Game-Theoretic Cold-Start Transient Optimization in DC Microgrids

Game-Theoretic Communication Structures in Microgrids

Transient Optimization of Parallel Connected Inverters in Islanded AC Microgrids

A Game Theoretic Bus Selection Method for Loads in Multibus DC Power Systems