This paper is concerned with active power sharing and frequency regulation in an islanded microgrid under event-triggered communication. A distributed secondary control scheme with a sampled-data-based event-triggered communication mechanism is proposed to achieve active power sharing and frequency regulation in a unified framework, where neighborhood sampled-data exchange occurs only when the predefined triggering condition is violated. Compared with traditional periodic communication mechanisms, the proposed event-triggered communication mechanism shows some prominent ability in reducing the number of communication among neighbors while guaranteeing the desired performance level of microgirds. By employing the Lyapunov–Kravovskii functional method, some sufficient conditions are derived to characterize the effects of control gains, system parameters, and sampling period on stability of microgrids. Finally, case studies on a modified IEEE 34-bus test system are conducted to evaluate the performance of the proposed distributed control scheme, showcasing its effectiveness, robustness against load changes, and plug-and-play ability.

Distributed Secondary Control for Active Power Sharing and Frequency Regulation in Islanded Microgrids Using an Event-Triggered Communication Mechanism

This paper proposes a distributed two-layer control structure for ac microgrids. Inverter-based distributed generators (DGs) can operate either as voltage-controlled voltage source inverters (VCVSI) or current-controlled voltage source inverters (CCVSI). VCVSIs provide the voltage and frequency support, whereas CCVSIs regulate the generated active and reactive powers. The proposed control structure has two main layers. The first layer deals with the voltage and frequency control of VCVSIs. The second layer regulates the active and reactive powers of CCVSIs. These controllers are implemented through two communication networks with one-way communication links and are fully distributed; each DG only requires its own information and the information of its neighbors on the communication network graph. The proposed control framework is verified on a microgrid test system and IEEE 34 test feeder.

A Multiobjective Distributed Control Framework for Islanded AC Microgrids

With an increasing deployment of plug-in electric vehicles, evaluating and mitigating the impacts of additional electrical loads created by these vehicles on power distribution grids become more important. This paper explores the use of prices of electricity at public charging stations as an instrument, in couple of road pricing, to better manage both power distribution and urban transportation networks. More specifically, a multi-class combined distribution and assignment model is formulated to capture the spatial distribution of plug-in electric vehicles across the transportation network and estimate the electrical loads they impose on the power distribution network. Power flow equations are subsequently solved to estimate real power losses. Prices of electricity at public charging stations and road tolls are then optimized to minimize both real power losses in the distribution grid and total travel time in the urban transportation network. The pricing model is formulated as a mathematical program with complementarity constraints and solved by a manifold suboptimization algorithm and a pattern search method. Numerical examples are presented to demonstrate the proposed model and solution algorithms.

Sustainability SI: Optimal Prices of Electricity at Public Charging Stations for Plug-in Electric Vehicles

A novel meta-heuristic optimization algorithm known as QOMJaya to solve different MOOPF problems is proposed.Essential modifications to the basic Jaya algorithm are done (i.e. MJaya).The proposed algorithm is scrutinized and validated using the IEEE 30-bus test system.Simulation results reveal the proposed algorithms supremacy over many previous algorithms in terms of solution optimality and feasibility.The obtained results disclose the proposed algorithms ability to produce real and well-distributed Pareto optimum fronts. This study introduces a novel meta-heuristic optimization algorithm known as quasi-oppositional modified Jaya (QOMJaya) to solve different multi-objective optimal power flow (MOOPF) problems. An intelligence strategy called quasi-oppositional based learning is incorporated into the proposed algorithm to enhance its convergence property, exploration capability, and solution optimality. Significant modifications to the basic Jaya algorithm are done to create a modified Jaya (MJaya) algorithm that can handle the MOOPF problem. A fuzzy decision-making strategy is proposed and incorporated into the Jaya algorithm as selection criteria for best and worst solutions. A new criterion for comparing updated and current candidate solutions is proposed. The concept of Pareto optimality is used to extract a set of non-dominated solutions. A crowding distance measure approach is utilized to maintain the diversity of Pareto optimality. In addition, a novel external elitist repository is developed to conserve discovered non-dominated solutions and to produce true and well-distributed Pareto optimal fronts. The proposed algorithm is scrutinized and validated using the modified IEEE 30-bus test system. Simulation results reveal the proposed algorithms ability to produce real and well-distributed Pareto optimum fronts for all considered multi-objective optimization cases. Furthermore, the obtained results disclose the superiority of the proposed QOMJaya algorithm over both the proposed MJaya algorithm and several previous algorithms in terms of solution optimality and feasibility.

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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution

This paper proposes a model for planning isolated microgrids. The goal of the proposed model is to minimize the investment, operational, and total costs of an isolated microgrid through the full identification of the system configuration. The model designates the optimal type of microgrid, i.e., ac, dc, or hybrid ac/dc, and the optimal sizing of both the distributed energy resources (DERs) and the electronic power converters, if needed. To render this planning approach generic, the model accommodates a wide variety of DERs, including ac and dc generators, capacitors, and energy storage systems. The detailed operational criteria of each power apparatus are taken into account in order to provide reliable operational scenarios. As a means of guaranteeing active and reactive power adequacy in isolated microgrids, the stochastic nature of generation and demand are also considered. The proposed model was developed analytically as a mixed integer nonlinear problem so that obtaining solution optima is thus possible with the use of a deterministic branch-and-bound nonlinear solver. The validity and effectiveness of the new formulation have been demonstrated through several case studies involving varied load topologies.

Optimal Configuration of Isolated Hybrid AC/DC Microgrids

The IEEE 34 node distribution test feeder incorporates all possible practical configurations and load profiles, such as three phase asymmetry, single phase laterals and distributed loads, among others. Simplifying assumptions leading to the balanced three phase main feeder and spot loads are common in the papers published in the literature on distribution system planning and operation. The purpose of this paper is to compare the results obtained using such simplifications with exact results given in the IEEE node test feeder data. Typical simplifying scenarios are assumed and the resulting balanced system analyzed. Comparison of voltage profiles and system losses validates the use of simplified balanced three phase system in the determination of equipment sizing, location and control parameters.

Comparative Study of the IEEE 34 Node Test Feeder under Practical Simplifications

This paper presents a methodology using graph theory to determine the specific generator contributions to different loads and the transmission system usage of different utilities. Starting from a power load flow solution, the method first identifies the buses as load buses or generation buses by getting the net power. Then a directed graph is formed with vertices representing buses and the edges representing transmission lines. Second, it constructs all possible directed and rooted subgraphs of the system from its generator vertices. Notice that the union of these subgraphs is the original directed graph. Using proportionality and average assumptions, it is possible to calculate the specific generator contributions to different loads and the transmission system usage of different utilities.

Graph theory application to deregulated power system

A voltage stability problem mainly occurs in heavily stressed systems. The maximum power that can be delivered to loads and relationship between load power and network voltage are the two basic properties that require thorough analysis. In much of the analysis reported on voltage stability the study of effect of variation of X/R ratio of transmission line on receiving end voltage is not explicitly portrayed. This paper develops a procedure to investigate the effect of variation of active load, reactive load and X/R ratio of line on the terminal voltage (receiving end voltage) of a radial line. A normalized approach using the maximum power in a resistive tie (X/R=0) as the base power enables deriving P-V curves with X/R ratio and load power factor as parameters.

Study of the effect of X/R ratio of lines on voltage stability

Capacitor placement in the distribution system has been considered as the best measure to improve voltage profile and power factor. Genetic algorithm (GA) as one of the evolutionary algorithms has been employed to come up with an optimal number of capacitors and location in the distribution system. The method was chosen due to its robustness and its ability to handle many practical constraints and explore all possible combinations on the solutions set, and find optimal solution at reasonable amount of computation time. The discrete nature of the sizes of capacitors and other physical aspects of a distribution system lead to difficulties in the use of conventional algorithms. By deploying appropriate value of capacitors at suitable locations in the distribution systems, the losses can be reduced and hence obtain minimum total operational cost. The standard IEEE Node 13 Test Feeder is the example used to demonstrate the feasibility of the technique.

Study of the Application of Evolutionary Algorithms for the Solution of Capacitor Deployment Problem in Distribution Systems

The strong coupling between bus voltages and reactive power injections has been widely used in steady state power flow algorithms. In the Newton-Raphson formulation the Jacobian matrix represents small-signal sensitivities relating real and reactive power injections to bus phase angles and voltage magnitudes respectively [1]. Decoupled approaches neglect real power-voltage and reactive power-phase angle relationships. While running the power flow analysis, the generator busses, where the real power injection and voltage magnitude are specified a priori, are changed to load busses with the voltage specification dropped if reactive power limits are violated. The papers describing optimal reactive power scheduling methods follow a similar procedure for evaluating appropriate generator reactive power levels [2]. Direct relationships between bus voltage and reactive power injection limits leading to useful sensitivities are derived in this paper using a line-voltage-drop model. Additional relationships between bus injection and line reactive flows become available in this approach. The paper presents detailed derivation of the new relationships, and applies the procedure to a typical power system network. The results illustrate the practical usefulness of the new approach in determining the limits on reactive power injection for a given bus voltage in generator busses. The conclusions outline future application of the approach for developing new reactive power optimization algorithms.

A. Sekar

Papers

Comparative Study of the IEEE 34 Node Test Feeder under Practical Simplifications

Graph theory application to deregulated power system

Study of the effect of X/R ratio of lines on voltage stability

Study of the Application of Evolutionary Algorithms for the Solution of Capacitor Deployment Problem in Distribution Systems

Study of reactive power/voltage sensitivities in interconnected power system networks