Hybrid ga-socp approach for placement and sizing of distributed generators in DC networks

This research addresses the problem of the optimal location and sizing distributed generators (DGs) in direct current (DC) distribution networks from the combinatorial optimization. It is proposed a master–slave optimization approach in order to solve the problems of placement and location of DGs, respectively. The master stage applies to the classical Chu & Beasley genetic algorithm (GA), while the slave stage resolves a second-order cone programming reformulation of the optimal power flow problem for DC grids. This master–slave approach generates a hybrid optimization approach, named GA-SOCP. The main advantage of optimal dimensioning of DGs via SOCP is that this method makes part of the exact mathematical optimization that guarantees the possibility of finding the global optimal solution due to the solution space’s convex structure, which is a clear improvement regarding classical metaheuristic optimization methodologies. Numerical comparisons with hybrid and exact optimization approaches reported in the literature demonstrate the proposed hybrid GA-SOCP approach’s effectiveness and robustness to achieve the global optimal solution. Two test feeders compose of 21 and 69 nodes that can locate three distributed generators are considered. All of the computational validations have been carried out in the MATLAB software and the CVX tool for convex optimization

Power Loss Minimization in a Radial Distribution Network by Optimal Sizing and Placement of Energy Storage Units

It is possible to reduce distribution losses by strategically placing and sizing DG and BESS sources. Assuring low loss requires strategically placing the aforementioned devices; otherwise, the system may experience either under- or overvoltage. It is preferable to choose bus stations with less risk for loss. The proposed approach tries to pinpoint the optimal BESS size and placement to cut down on investment and operating expenses while still achieving the desired level of energy reduction. The development of optimisation algorithms for finding and scaling BESS units is the fundamental focus of this study. Two such strategies are being explored here: the Genetic Algorithm (GA) and the Ant Colony Optimization Algorithm (ACOA). The goal function, like the original issue, seeks to minimise system-wide power losses while adhering to specified levels of equality and inequality. This article explores the appropriate capacity and placement of the DGs in a 33-bus radial distribution grid to reduce power dissipations. Matlab code is used to perform a simulation, and the results are put to use gauging the method's sturdiness

Grid-Connected Renewable Energy Sources

The use of renewable energy sources (RESs) is a need of global society. This editorial, and its associated Special Issue “Grid-Connected Renewable Energy Sources”, offers a compilation of some of the recent advances in the analysis of current power systems that are composed after the high penetration of distributed generation (DG) with different RESs. The focus is on both new control configurations and on novel methodologies for the optimal placement and sizing of DG. The eleven accepted papers certainly provide a good contribution to control deployments and methodologies for the allocation and sizing of DG

Operation and planning of distribution networks with integration of renewable distributed generators considering uncertainties: a review

YesDistributed generators (DGs) are a reliable solution to supply economic and reliable electricity to customers. It is the last stage in delivery of electric power which can be defined as an electric power source connected directly to the distribution network or on the customer site. It is necessary to allocate DGs optimally (size, placement and the type) to obtain commercial, technical, environmental and regulatory advantages of power systems. In this context, a comprehensive literature review of uncertainty modeling methods used for modeling uncertain parameters related to renewable DGs as well as methodologies used for the planning and operation of DGs integration into distribution network.This work was supported in part by the SITARA project funded by the British Council and the Department for Business, Innovation and Skills, UK and in part by the University of Bradford, UK under the CCIP grant 66052/000000

Modified analytical approach for PV-DGs integration into radial distribution network considering loss sensitivity and voltage stability

Abstract: Achieving the goals of distribution systems operation often involves taking vital decisions with adequate consideration for several but often contradictory technical and economic criteria. Hence, this paper presents a modified analytical approach for optimal location and sizing of solar PV-based DG units into radial distribution network (RDN) considering strategic combination of important power system planning criteria. The considered criteria are total planning cost, active power loss and voltage stability, under credible distribution network operation constraints. The optimal DG placement approach is derived from the modification of the analytical approach for DG placement using line-loss sensitivity factor and the multiobjective constriction factor-based particle swarm optimization is adopted for optimal sizing. The effectiveness of the proposed procedure is tested on the IEEE 33-bus system modeled using Matlab considering three scenarios. The results are compared with existing reports presented in the literature and the results obtained from the proposed approach shows credible improvement in the RDN steady-state operation performance for line-loss reduction, voltage profile improvement and voltage stability improvement

Microgrids/Nanogrids Implementation, Planning, and Operation

Today’s power system is facing the challenges of increasing global demand for electricity, high-reliability requirements, the need for clean energy and environmental protection, and planning restrictions. To move towards a green and smart electric power system, centralized generation facilities are being transformed into smaller and more distributed ones. As a result, the microgrid concept is emerging, where a microgrid can operate as a single controllable system and can be viewed as a group of distributed energy loads and resources, which can include many renewable energy sources and energy storage systems. The energy management of a large number of distributed energy resources is required for the reliable operation of the microgrid. Microgrids and nanogrids can allow for better integration of distributed energy storage capacity and renewable energy sources into the power grid, therefore increasing its efficiency and resilience to natural and technical disruptive events. Microgrid networking with optimal energy management will lead to a sort of smart grid with numerous benefits such as reduced cost and enhanced reliability and resiliency. They include small-scale renewable energy harvesters and fixed energy storage units typically installed in commercial and residential buildings. In this challenging context, the objective of this book is to address and disseminate state-of-the-art research and development results on the implementation, planning, and operation of microgrids/nanogrids, where energy management is one of the core issues

Power quality enhancement in electricity networks using grid-connected solar and wind based DGs

The integration of DG into utility networks has significantly increased over the past years primarily as a result of growing energy demand, coupled with the environmental impacts posed by conventional fossil fuel-based power generation. The prominent DG technologies which are capable of meeting bulk energy demands and are clean energy sources are wind and solar energy sources. The resources for solar and wind based DG are available in abundance in most geographical locations in South Africa and the rest of Africa. Through the Renewable Energy Independent Power Producer Procurement Programme (REIPPPP) introduced by the South African government in 2011, 3 920 MW of renewable energy has been procured to date. Out of this, solar and wind energy constitute 2 200 MW and 960 MW, respectively. Grid integration of solar and wind-based intermittent DGs may however pose negative impacts on the quality of power supplied by the utility network. Some of the detrimental impacts of DG include voltage fluctuations, flicker, etc. which are in general categorised as power quality (PQ) problems. The proper planning of DG integration is required to mitigate the negative impacts they pose on system's PQ to ensure that the performance of the utility network is enhanced in terms of the overall PQ improvement of the system. This dissertation reviews general PQ problems in utility networks with DG integration and whether poor planning of DG integration affects PQ negatively. The work emphasizes on the impacts of grid integration of wind and solar PV sources on power quality. It investigates the manner in which wind and solar energy systems differ in their impacts and capacity to improve PQ of the network in terms of a number of factors such as point of integration and capacity of DG, type of DG, network loading, etc. The role of grid-integrated DG in PQ improvement in electricity network is also investigated by exploring different PQ improvement techniques. The networks considered for the grid integration of DG for PQ improvement in this work are the IEEE 9-bus sub-transmission network at the nominal voltage of 230kV and the IEEE 33-bus distribution network at the nominal voltage of 12 kV. The aspects essential for facilitating proper planning of DG integration for PQ improvement and total loss reduction are investigated and the comparative analysis is made between grid integration of wind and solar PV based DGs. The simulations of different case studies in this work are done using DIgSILENT PowerFactory version 14.1 as well as coding in MATLAB. The cases studies conducted are aimed at facilitating the proper planning of grid integration of wind and solar PV-based DGs by comparing their PQ improvement capabilities under different scenarios. First the investigation of how their location and capacity affect the network voltage profiles and active power losses is conducted. Their ability to improve the system's PQ is also studied by observing PQ improvement strategies such as voltage control, installation of energy storage and the optimal placement of DGs under different scenarios. In order to account for the weakness of most South African utility grids, PQ improvement in weak networks with DG integration is also studied by investigating how DG integration in networks with different grid strengths affect the system's PQ. The results provide an understanding of the role of grid integration of wind and solar based DGs on PQ which is useful in the planning of grid integration of RE, particularly in South African electricity networks. The results revealed that the location and capacity of integrated DGs indeed affect the quality of power as well as active power losses in the grid. It is also established that a significant improvement in network's PQ and line loss reduction can be achieved in networks with wind and solar integration. The results however indicated that wind and solar PV based DGs differ in their impacts and capacity to improve the quality of power in the network. Furthermore, the results revealed that wind and solar plants integration into weak utility grids may pose adverse impacts on the system's PQ. It was however established that including reactive power control devices such as STATCOM and SVC at the PCC can successfully improve the system's PQ and enable grid code compliance in electricity networks with DG integration

Intelligent control of PV co-located storage for feeder capacity optimization

Battery energy storage is identified as a strong enabler and a core element of the next generation grid. However, at present the widespread deployment of storage is constrained by the concerns that surround the techno-economic viability. This thesis addresses this issue through optimal integration of storage to improve the efficiency of the electricity grid. A holistic approach to optimal integration includes the development of methodologies for optimal siting, sizing and dispatch coordination of storage