Optimization Techniques for the Developing Distribution System

The most rapidly changing part of today’s power grid is the distribution system. Many new technologies have emerged that revolutionize the way utilities provide, and now sometimes receive, power to and from their customers. To an extent, the push for de-regulation of utilities has also led to an increased focus on reliability and efficiency. These changes make design and operation of power systems more complex causing utilities to question if they are operating optimally. Operations Research (OR) is an area of mathematics where quantitative analysis is used to provide a basis for complex decision making. The changing landscape in electric distribution makes it a prime candidate for the application of OR techniques. This research seeks to develop optimization methods that can be applied to any distribution feeder or group of feeders that allows for optimal decisions to be made in a reasonable time frame. Two specific applications identified in this thesis are optimal reconfiguration during outage situations and optimal location of Battery Energy Storage Systems (BESS). Response to outages has traditionally relied on human-in-the-loop approaches where a dispatcher or a crew working the field decides what switching operations are needed to isolate affected parts of the system and restore power to healthy ones. This approach is time consuming and under-utilizes the benefits provided by widely-adopted, remotely-controlled switching technologies. Chapters Two and Three of this thesis develop a partitioning method for determining the switching operations required to optimize the amount of load that is restored during an event. Most people would agree that renewable forms of Distributed Generation (DG) provide great benefits to the power industry, especially through reduced impact on the environment. The variable nature of renewables, however, can cause many issues for operation and control of a utilities’ system, especially for distribution interconnections. Storage technologies are thought to be the primary solution to these issues with much research focused on sizing and control of BESSs. Equally important for integration, but often overlooked, is the location at which the device is connected. Chapter Four explores this idea by drawing conclusions about optimal BESS location based on well-studied ideas of optimal capacitor location

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

Intelligent Microgrids

Center for Electromechanic

A combined analytical method for optimal location and sizing of distributed generation considering voltage stability and power loss in a power distribution system

In this paper, a multi-objective analytical method to evaluate the impacts of optimal location and sizing of distributed generation is presented. This method is based on an analysis of the exact loss formula and continuous power flow in a radial distribution system. Based on two methods of analysis, power loss and weakest voltage buses and lines are calculated and then the optimal size of distributed generation is determined. After that, by considering the minimum power losses and the maximisation of voltage stability, the proposed index determines and ranks positions to decide the optimal distributed generation location in the system. This method allows us to find the best places and size to connect a number of distributed generation units by optimising the objective functions. The simulation results were obtained using a 33-bus radial distribution system to determine the location and size of the distributed generation units. The results show the effectiveness of voltage profile improvement, loading factor improvement and power loss reduction. Further, the problems of a single objective function and the placement of the distributed generation unit using analytical methods are solved by the proposed approach

Solar-Based DG Allocation Using Harris Hawks Optimization While Considering Practical Aspects

The restructuring of power systems and the ever-increasing demand for electricity have given rise to congestion in power networks. The use of distributed generators (DGs) may play a significant role in tackling such issues. DGs may be integrated with electrical power networks to regulate the drift of power in the transmission lines, thereby increasing the power transfer capabilities of lines and improving the overall performance of electrical networks. In this article, an effective method based on the Harris hawks optimization (HHO) algorithm is used to select the optimum capacity, number, and site of solar-based DGs to reduce real power losses and voltage deviation. The proposed HHO has been tested with a complex benchmark function then applied to the IEEE 33 and IEEE 69 bus radial distribution systems. The single and multiple solar-based DGs are optimized for the optimum size and site with a unity power factor. It is observed that the overall performance of the systems is enhanced when additional DGs are installed. Moreover, considering the stochastic and sporadic nature of solar irradiance, the practical size of DG has been suggested based on analysis that may be adopted while designing the actual photovoltaic (PV) plant for usage. The obtained simulation outcomes are compared with the latest state-of-the-art literature and suggest that the proposed HHO is capable of processing complex high dimensional benchmark functions and has capability to handle problems pertaining to electrical distribution in an effective manner.publishedVersio