Microgrids In Distribution Systems Research Articles

A Bilevel Voltage Regulation Operation for Distribution Systems With Self-Operated Microgrids

The emerging of microgrids in distribution systems has significantly enhanced the resilience of power grids. However, the operators of a distribution system and microgrids therein can be different and have accessibility to different devices. To model the operation of such a grid, this paper proposes a bilevel formulation and probes into the voltage regulation operation, considering the interaction between different systems. The proposed bilevel formulation considers the cooperation of active energy resources (AER), transformer tap-changers, and capacitor banks that are controlled by different operators. To facilitate the solution time of the target bilevel optimization, the lower-level problems with different objectives are modeled using deep neural networks (DNNs) which are then converted into a set of constraints. Hence, the bilevel problem can be reformed to a single-level problem. Lastly, the proposed solution procedures are validated using a customized joint system constructed by the IEEE 123-bus system and a real distribution system in Iowa. According to the numerical validation results, the solution time of the proposed nonlinear activation function based DNN model is 69 times faster than other methods in solving voltage regulation with a bilevel structure.

Reliability Analysis Algorithm for Multiple Microgrids in Distribution Systems Based on Complex Network Mathematical Theory

It exists a great potential in microgrids connected to distribution systems of being taken into advantage reconfiguration possibilities with the purpose of achieving the quality of service regulatory requirements that become more demanding each day. In addition, it is possible to optimize the network operators’ income by increasing the incentives for upgrading the quality indexes. In this paper, it's proposed an evaluation algorithm of the connection points of multiple microgrids in a distribution system that upgrades the reliability of the system as a whole, being based in complex network analysis (CNA), a perspective of power systems that allows the evaluation of an electrical system as a graph. For that, a model of a trial system is made from the CNA point of view utilizing the MATLAB software and afterwards, as validation of the proposal of this work, the system's reliability is evaluated by connecting multiple microgrids into critical nodes provided by the CNA making use of the NEPLAN tool of power systems simulation.

Risk-Based planning and partitioning of multiple micro-grids in distribution systems

The rapid fluctuations of renewable power generation such as wind turbines and photovoltaic power plants make significant risks in Multiple Micro-Grids (MMGs) planning and partitioning problem. To control the risk, in this paper a risk-based model is presented for optimal planning and partitioning of MMGs under uncertainties. In addition, two term technical risk and economical risk are introduced to analyze the total risk on MMGs. Genetic algorithm is used for solving the optimization problem. Distributed energy resources and storages placement in MGs and tie switches status for MGs connection to grid or MGs neighbors have been determined, simultaneously. A voltage stability index is formulated and applied for the optimal placement of MMGs via AC power flow tool. Simulation studies is established on the 33-bus IEEE test distribution system and the consequent discussions demonstrate the efficiency of the proposed methodology.

Rank‐based energy scheduling strategy of networked microgrids in distribution systems

Microgrids (MGs) have emerged as a key platform for integrating distributed energy resources into distribution systems. However, a high penetration of renewable energy resources in an MG causes an imbalance frequently between energy generation and load. One solution to this problem is internal energy trading among MGs, where MGs trade (i.e. buy or sell) energy with other MGs in the network. In internal trading, multiple buyer MGs may compete to obtain energy from seller MGs with surplus energy. By contrast, seller MGs also compete to sell their surplus to those confronted with a deficit. Considering this scenario, we propose a novel rank-based energy scheduling strategy for networked MGs in a distribution system to solve the competition between buyer and seller MGs. The technique for order of preference by similarity to the ideal solution method, which is a multi-criteria decision-making approach, is applied to prioritise the MGs. The proposed strategy determines the amount of internal energy to trade for each seller/buyer MG. Different from existing mechanisms, the proposed rank-based approach evaluates each MG with respect to four criteria: ratio of energy, forecasting accuracy, contribution of supply, and historical performance. The proposed strategy is compared with existing no-rank-based scheduling and absolute contribution-based method. Moreover, the effect of each criterion on the cost of each MG is illustrated by considering and disregarding the criterion in the proposed strategy that demonstrates the effectiveness of the proposed strategy in reducing the cost of MGs according to their rank in the network.

Incorporating microgrids coupling with utilization of flexible switching to enhance self-healing ability of electric distribution systems

Electric distribution networks have to deal with issues caused by natural disasters. These problems possess unique characteristics, and their severity can make load restoration methods impotent. One solution that can help in alleviating the aftermath is the use of microgrids (MGs). Employing the cumulative capacity of the generation resources through MG coupling facilitates the self-healing capability and leads to better-coordinated energy management during the restoration period, while the switching capability of the system should also be considered. In this paper, to form and schedule dynamic MGs in distribution systems, a novel model based on mixed-integer linear programming (MILP) is proposed. This approach employs graph-related theories to formulate the optimal formation of the networked MGs and management of their proper participation in the load recovery process. In addition, the Benders decomposition technique is applied to alleviate computability issues of the optimization problem. The validity and applicability of the proposed model are evaluated by several simulation studies.

Design for independent and self‐adequate microgrids in distribution systems considering optimal allocation of DG units

Introducing the concept of distributed generations (DGs) and local demand supply have led to significant changes in distribution networks. The idea of aggregating loads and DGs in an appropriate way have resulted in microgrids' (MGs) appearance. Considering the economic and environmental concerns, MGs will play important roles in future distribution systems. However, it is necessary to implement an efficient procedure for the optimal design of MGs. This study proposes optimised methods in order to construct a set of independent, self-sufficient MGs in distribution networks. Increasing self-adequacy of constructed MGs is obtained by minimising the power imbalance within them or minimising transferred power between them. The stochastic nature of DGs and consumed loads are also considered. In this regard, optimal allocating and sizing of distributed resources are also studied. In this study, the optimal DG placement is considered with the aim of improving system load factor and decreasing system losses. The presented strategy facilitates controlling strategies of smart distribution systems, such as self-healing, by using virtual MGs in the future distribution systems. The related formulation and solution algorithms are presented in this study. Moreover, the proposed strategy is studied in the PG&E 69-bus distribution system.

A Transactive Energy Framework for Coordinated Energy Management of Networked Microgrids With Distributionally Robust Optimization

Networked microgrids (MGs) are considered as an emerging grid design for the future distribution system (DS). The coordination of the networked MGs is critical in order to further enhance the operation efficiency and reliability of the system. In this paper, a transactive energy (TE) framework is proposed for the coordinated energy management of networked MGs in DS. Instead of direct coordination signals and fixed pricing schemes, the distribution network operator (DNO) organizes a transactive market with the MGs to coordinate the energy management in the operation. Further, a distributionally robust optimization (DRO)-based algorithm is developed to provide a robust solution of the detailed scheduling decisions in the proposed TE framework under uncertainty without being too conservative. Case studies with the proposed framework were conducted with the IEEE 33-bus system with three MGs and the IEEE 123-bus system with nine MGs. The results of the case studies show that the proposed TE-based framework can effectively coordinate the energy scheduling of the MGs. The operational cost of the DS is reduced significantly. Meanwhile, the proposed DRO-based algorithm provides a robust but not over-conservative solution for the operation decisions of the DNO and MGs in the proposed framework.

A Planning Framework for Optimal Partitioning of Distribution Networks Into Microgrids

This paper proposes a novel methodology for the optimal design of microgrids in distribution systems with multiple distributed generation units (DGs). Following the IEEE Standard 1547.4-2011, the operation and control of large distribution networks can be enhanced by dividing these networks into multiple virtual microgrids. The proposed planning framework incorporates the necessary conditions for microgrids to operate efficiently in grid-connected operating mode and successfully during islanding. To obtain a robust design, the clustering process considers three objectives: maximizing the self-adequacy of the designed microgrids, maximizing microgrid islanding success probability, and a combination of both targets. For this purpose, the PG&E distribution system with 69 buses is selected as a test case. Backtracking search optimization algorithm, a probabilistic load flow approach, and graph-based theories are used to accomplish this research. Simulation results demonstrate the effectiveness of combining the self-adequacy and the islanding success probability objectives in the clustering process. Compared with other strategies present in the previous literature, the proposed framework results in more self-sufficient and successful islands assessed in terms of active and reactive power adequacy as well as voltage constraints. Next, the effects of increased penetration level of DGs and installation of both distributed energy-storage units and distributed reactive sources on the design process are examined. Finally, a comparison with other microgrid design objectives applied in previous researches reveals that the resultant design is sensitive to the system's reliability, security, and economic requirements.

A Multiagent-Based Game-Theoretic and Optimization Approach for Market Operation of Multimicrogrid Systems

This paper proposes a multiagent-based energy market for multimicrogrid systems using game-theoretic and hierarchical optimization approaches. The proposed method is tailored to achieve the optimal operation of smart microgrids in distribution systems. Because of rapid load variations in distribution systems, it is necessary to develop fast optimization algorithms which minimize the power mismatch in and among microgrids. In this paper, a three-level market framework is proposed. The first level comprises a game-theoretic double-auction mechanism for the day-ahead market while the next two levels are optimal rescheduling and intermicrogrid reverse auction model for the hour-ahead and real-time markets, respectively. Using the hierarchical optimization algorithm in a multiagent-based area, it is anticipated to not only minimize the optimization solution time, but also reduce the dependency on the network in grid-connected mode or load shedding in islanded mode. Using this approach, load demand response capabilities along with rescheduling of Distributed Energy Storage Systems and distributed generations could be utilized in all market levels, which will lead to optimal operation of multimicrogrid systems. Agents are developed in DIgSILENT PowerFactory and dynamic data exchange is activated for communication among agents communicating through a data distribution service which utilizes the real-time publish-subscribe communication protocol. The developed framework is applied to the modified 37-bus IEEE distribution test feeder system to validate the effectiveness of this market structure.

Centralized Unbalanced Dispatch of Smart Distribution DC Microgrid Systems

This paper proposes three new operation strategies such that a set of dc microgrids in distribution systems can cooperate pursuing particular objectives: 1) loss reduction; 2) full unbalance compensation; and 3) partial unbalance compensation. Loss reduction is a regular strategy for distribution utilities operating their systems efficiently by optimal dispatch of three-phase in/out powers of dc microgrids. Full and partial unbalance compensation strategies can solve single- or two-phase overloading problems of substation transformers temporarily and slow down their aging process. To validate the performance of the proposed operation strategies, several steady-state studies are performed in the IEEE 123-bus test system. According to the simulation results, the operation losses can be reduced by up to 34% with 15.2% DG penetration. The maximum single-phase loading of the substation transformer can be reduced by up to 30%.

Multiagent-based transactive energy framework for distribution systems with smart microgrids

The increasing population of microgrids with various kinds of plug and play energy resources and rapidly varying demand in distribution systems are multiplying the complexity involved in overall system management. This paper proposes an agent-based transactive energy management framework with a comprehensive energy management system (CEMS) as a solution to address the aggregated complexity induced by microgrids in distribution systems. In this framework, microgrids sell or buy the energy in transactive market, which is an inter-microgrid auction based electricity market, to manage the excess supply or residual demand. CEMS follows a dual phase energy management strategy. In the first stage local auxiliary resources such as demand response and distributed energy storage systems of the microgrids are optimally integrated into system operation to level off the forecasted energy imbalances in microgrids. In the latter stage, the operating configuration of the local auxiliary resources is adjusted in real time along with transactive energy to address the imbalances leftover in the former phase and the forecast errors. The efficacy of the proposed framework and CEMS is verified on a IEEE distribution test feeder system with microgrids.

A New Load-shedding Approach for Microgrids in the Presence of Wind Turbines

Following the penetration of microgrids in distribution systems, frequency deviations in contingency conditions are becoming increasingly important. Therefore, effective load shedding is necessary to regulate the frequency. This article develops a new load-shedding method for microgrids considering wind speed changes. The proposed method uses a combination of frequency and voltage data for determining load-shedding amounts in each contingency condition. For this purpose, the total required load shedding is determined first by using transient stability analysis in different contingency scenarios in microgrids. This will establish a database for an adaptive neuro-fuzzy inference system network to determine the total required load shedding. Then a fuzzy system is used to determine the load shedding in each step dynamically based on the severity of contingencies. The proposed method capability is compared with the conventional load-shedding method. Simulation results show the effectiveness of the proposed method for microgrid control in contingency conditions.

Coordinated Energy Management of Networked Microgrids in Distribution Systems

This paper proposes a novel control strategy for coordinated operation of networked microgrids (MGs) in a distribution system. The distribution network operator (DNO) and each MG are considered as distinct entities with individual objectives to minimize the operation costs. It is assumed that both the dispatchable and nondispatchable distributed generators (DGs) exist in the networked MGs. In order to achieve the equilibrium among all entities and take into account the uncertainties of DG outputs, we formulate the problem as a stochastic bi-level problem with the DNO in the upper level and MGs in the lower level. Each level consists of two stages. The first stage is to determine base generation setpoints based on the load and nondispatchable DG output forecasts and the second stage is to adjust the generation outputs based on the realized scenarios. A scenario reduction method is applied to enhance a tradeoff between the accuracy of the solution and the computational burden. Case studies of a distribution system with multiple MGs of different types demonstrate the effectiveness of the proposed methodology. The centralized control, deterministic formulation, and stochastic formulation are also compared.

New Metrics for Assessing the Reliability and Economics of Microgrids in Distribution System

This paper proposes a series of new metrics for the reliability and economic assessment of microgrids in distribution system. These metrics include reliability parameters for a microgrid in the islanded mode, indices indicating distributed generation (DG) and load characteristics in the microgrid, microgrid economic indices, and customer based microgrid reliability indices. A two-step Monte Carlo simulation (MCS) method is proposed to assess the reliability and economics of a microgrid with intermittent DGs as well as the reliability of distribution system with microgrids. An application in IEEE-RBTS shows the effectiveness of the reliability and economic assessment technique with the proposed metrics, which can provide scientific and comparative information for the design and operation of microgrids.

Microgrid-Based Co-Optimization of Generation and Transmission Planning in Power Systems

This paper presents an algorithm for the microgrid planning as an alternative to the co-optimization of generation and transmission expansion planning in electric power systems. The integration of microgrids in distribution systems will offer a decentralized control of local resources for satisfying the network reliability and the power quality required by local loads. The objective in this paper is to minimize the total system planning cost comprising investment and operation costs of local microgrids, the co-optimized planning of large generating units and transmission lines, and the expected cost of unserved energy. The cost of unserved energy reflects the cost of load shedding which is added to the objective function for reliability considerations. The microgrid-based co-optimization planning problem is decomposed into a planning problem and annual reliability subproblem. The optimal integer planning decisions calculated in the planning problem will be examined against the system reliability limits in the subproblem and the planning decisions will be revised using proper feasibility cuts if the annual reliability limits are violated. Numerical simulations demonstrate the effectiveness of the proposed microgrid-based co-optimization planning in power systems and explore the economic and reliability merits of microgrid planning as compared to grid-based generation and transmission upgrades.