Distributed generation modelling for unbalanced three-phase power flow calculations in smart grids

Distributed Generators (DG) are generally modeled as PQ or PV buses in power flow studies. But in order to integrate DG units into the distribution systems and control the reactive power injection it is necessary to know the operation mode and the type of connection to the system. This paper presents a single-phase and a three-phase mathematical model to integrate DG in power flow calculations in distribution systems, especially suited for Smart Grid calculations. If the DG is in PV mode, each step of the power flow algorithm calculates the reactive power injection from the DG to the system to keep the voltage in the bus in a predefined level, if the DG is in PQ mode, the power injection is considered as a negative load. The method is tested on two well known test system, presenting single-phase results on 85 bus system, and three-phase results in the IEEE 34 bus test system. © 2011 IEEE.

A multi-objective evaluation of the impact of the penetration of Distributed Generation

This paper proposes a methodology to consider the effects of the integration of DG on planning. Since DG has potential to defer investments in networks, the impact of DG on grid capacity is evaluated. A multi-objective optimization tool based on the meta-heuristic MEPSO is used, supporting an alternative approach to exploiting the Pareto front features. Tests were performed in distinct conditions with two well-known distribution networks: IEEE-34 and IEEE-123. The results combined minimization and maximization in order to produce different Pareto fronts and determine the extent of the impact caused by DG. The analysis provides useful information, such as the identification of futures that should be considered in planning. A future means a set of realizations of all uncertainties. MEPSO also presented a satisfactory performance in obtaining the Pareto fronts. © 2011 IEEE.

Optimal allocation of capacitors in radial distribution systems with distributed generation

This paper presents a mixed-integer linear programming approach to solving the optimal fixed/switched capacitors allocation (OCA) problem in radial distribution systems with distributed generation. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system and one real distribution system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. © 2011 IEEE.

A mixed-integer LP model for the reconfiguration of radial electric distribution systems considering distributed generation

The problem of reconfiguration of distribution systems considering the presence of distributed generation is modeled as a mixed-integer linear programming (MILP) problem in this paper. The demands of the electric distribution system are modeled through linear approximations in terms of real and imaginary parts of the voltage, taking into account typical operating conditions of the electric distribution system. The use of an MILP formulation has the following benefits: (a) a robust mathematical model that is equivalent to the mixed-integer non-linear programming model; (b) an efficient computational behavior with exiting MILP solvers; and (c) guarantees convergence to optimality using classical optimization techniques. Results from one test system and two real systems show the excellent performance of the proposed methodology compared with conventional methods. © 2012 Published by Elsevier B.V. All rights reserved.

A mixed-integer linear programming approach for optimal type, size and allocation of distributed generation in radial distribution systems

This paper presents a mixed-integer linear programming approach to solving the problem of optimal type, size and allocation of distributed generators (DGs) in radial distribution systems. In the proposed formulation, (a) the steady-state operation of the radial distribution system, considering different load levels, is modeled through linear expressions; (b) different types of DGs are represented by their capability curves; (c) the short-circuit current capacity of the circuits is modeled through linear expressions; and (d) different topologies of the radial distribution system are considered. The objective function minimizes the annualized investment and operation costs. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique.© 2012 Elsevier B.V. All rights reserved.

Bilevel approach for optimal location and contract pricing of distributed generation in radial distribution systems using mixed-integer linear programming

In this study, a novel approach for the optimal location and contract pricing of distributed generation (DG) is presented. Such an approach is designed for a market environment in which the distribution company (DisCo) can buy energy either from the wholesale energy market or from the DG units within its network. The location and contract pricing of DG is determined by the interaction between the DisCo and the owner of the distributed generators. The DisCo intends to minimise the payments incurred in meeting the expected demand, whereas the owner of the DG intends to maximise the profits obtained from the energy sold to the DisCo. This two-agent relationship is modelled in a bilevel scheme. The upper-level optimisation is for determining the allocation and contract prices of the DG units, whereas the lower-level optimisation is for modelling the reaction of the DisCo. The bilevel programming problem is turned into an equivalent single-level mixed-integer linear optimisation problem using duality properties, which is then solved using commercially available software. Results show the robustness and efficiency of the proposed model compared with other existing models. As regards to contract pricing, the proposed approach allowed to find better solutions than those reported in previous works. © The Institution of Engineering and Technology 2013.

Fault location in power distribution networks with distributed generation.

This research presents the development and implementation of fault location algorithms in power distribution networks with distributed generation units installed along their feeders. The proposed algorithms are capable of locating the fault based on voltage and current signals recorded by intelligent electronic devices installed at the end of the feeder sections, information to compute the loads connected to these feeders and their electric characteristics, and the operating status of the network. In addition, this work presents the study of analytical models of distributed generation and load technologies that could contribute to the performance of the proposed fault location algorithms. The validation of the algorithms was based on computer simulations using network models implemented in ATP, whereas the algorithms were implemented in MATLAB.

Modeling of Distributed Generation under Next Generation Interconnection Requirements

Thesis (Master's)--University of Washington, 2016-06

Impacts of distributed generation on low-voltage distribution network protection

This paper reports work of a MEng student final year project, which looks in detail at the impacts that distributed generation can have on existing low-voltage distribution network protection systems. After a review of up-to-date protection issues, this paper will investigate several key issues that face distributed generation connections when it comes to network protection systems. These issues include, the blinding of protection systems, failure to automatically reclose, unintentional islanding, loss of mains power and the false tripping of feeders. Each of these problems impacts on protection systems in its own way. This study aims to review and investigate these problems via simulation demonstrations on one representative network to recommend solutions to practices.

Ultrahigh step-up dc-dc converter for distributed generation by three Degrees of Freedom (3DoF) approach

This paper proposes a novel dc-dc converter topology to achieve an ultrahigh step-up ratio while maintaining a high conversion efficiency. It adopts a three degree of freedom approach in the circuit design. It also demonstrates the flexibility of the proposed converter to combine with the features of modularity, electrical isolation, soft-switching, low voltage stress on switching devices, and is thus considered to be an improved topology over traditional dc-dc converters. New control strategies including the two-section output voltage control and cell idle control are also developed to improve the converter performance. With the cell idle control, the secondary winding inductance of the idle module is bypassed to decrease its power loss. A 400-W dc-dc converter is prototyped and tested to verify the proposed techniques, in addition to a simulation study. The step-up conversion ratio can reach 1:14 with a peak efficiency of 94% and the proposed techniques can be applied to a wide range of high voltage and high power distributed generation and dc power transmission.

Development of distributed generation infrastructure for microgrid connectivity to operational power systems

Distributed Generation (DG) from alternate sources and smart grid technologies represent good solutions for the increase in energy demands. Employment of these DG assets requires solutions for the new technical challenges that are accompanied by the integration and interconnection into operational power systems. A DG infrastructure comprised of alternate energy sources in addition to conventional sources, is developed as a test bed. The test bed is operated by synchronizing, wind, photovoltaic, fuel cell, micro generator and energy storage assets, in addition to standard AC generators. Connectivity of these DG assets is tested for viability and for their operational characteristics. The control and communication layers for dynamic operations are developed to improve the connectivity of alternates to the power system. A real time application for the operation of alternate sources in microgrids is developed. Multi agent approach is utilized to improve stability and sequences of actions for black start are implemented. Experiments for control and stability issues related to dynamic operation under load conditions have been conducted and verified.

Optimal energy management of smart households with electric vehicles, energy storage and distributed generation

In this thesis, the optimal operation of a neighborhood of smart households in terms of minimizing the total energy cost is analyzed. Each household may comprise several assets such as electric vehicles, controllable appliances, energy storage and distributed generation. Bi-directional power flow is considered for each household . Apart from the distributed generation unit, technological options such as vehicle-to-home and vehicle-to-grid are available to provide energy to cover self-consumption needs and to export excessive energy to other households, respectively.

Time-series-based maximization of distributed wind power generation integration

Energy policies and technological progress in the development of wind turbines have made wind power the fastest growing renewable power source worldwide. The inherent variability of this resource requires special attention when analyzing the impacts of high penetration on the distribution network. A time-series steady-state analysis is proposed that assesses technical issues such as energy export, losses, and short-circuit levels. A multiobjective programming approach based on the nondominated sorting genetic algorithm (NSGA) is applied in order to find configurations that maximize the integration of distributed wind power generation (DWPG) while satisfying voltage and thermal limits. The approach has been applied to a medium voltage distribution network considering hourly demand and wind profiles for part of the U.K. The Pareto optimal solutions obtained highlight the drawbacks of using a single demand and generation scenario, and indicate the importance of appropriate substation voltage settings for maximizing the connection of MPG.