Fast yet Accurate Energy-Loss-Assessment Approach for Analyzing/Sizing PV in Distribution Systems Using Machine Learning
TL;DR: A fast yet accurate energy-loss assessment approach in distribution systems using machine learning that uses all data to estimate losses, which yields accurate results close to the exact solutions in a very short time.
Abstract: The penetration of photovoltaic (PV) has obviously been increased in distribution systems throughout the world. To sufficiently assess the energy losses with PV, comprehensive simulations with high time-resolution data are required. These simulations have a heavy computational burden, which makes it difficult to analyze distribution systems and evaluate PV impacts with fine resolutions. To cope with this issue, most related works down-sample, cluster, or quantize the full data to reduce the computational time on the expense of the accuracy. In this paper, we propose a fast yet accurate energy-loss assessment approach in distribution systems using machine learning. The unique feature of the proposed approach is that it uses all data to estimate losses, which yields accurate results close to the exact solutions in a very short time. The simulation results demonstrate that the proposed approach extremely reduces the computational time of energy-loss estimation with high accuracy rates. The speedup of the proposed approach with respect to power flow simulations for a yearlong at a 30-s time resolution is 28 691 (99.9965 $\%$ reduction in computational time). The effectiveness of the proposed approach is also illustrated by applying it to optimize the PV size for minimizing energy losses.
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TL;DR: A novel stochastic approach based on a coordinated management scheme of control devices in distribution systems that can maximize the hosting capacity of photovoltaics while optimally managing transformers, VAr sources, and electric vehicles in a coordinated manner.
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TL;DR: Results demonstrate that the proposed control strategy effectively coordinates between the various voltage control units while minimizing VD and VF.
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TL;DR: An improved optimization algorithm is proposed to solve the DED optimization problem for a sustainable power system that includes fuel-based generators, PV, and energy storage devices in sustainable power systems, considering various profiles of PV (clear and cloudy).
Abstract: Worldwide, the penetrations of photovoltaic (PV) and energy storage systems are increased in power systems. Due to the intermittent nature of PVs, these sustainable power systems require efficient managing and prediction techniques to ensure economic and secure operations. In this paper, a comprehensive dynamic economic dispatch (DED) framework is proposed that includes fuel-based generators, PV, and energy storage devices in sustainable power systems, considering various profiles of PV (clear and cloudy). The DED model aims at minimizing the total fuel cost of power generation stations while considering various constraints of generation stations, the power system, PV, and energy storage systems. An improved optimization algorithm is proposed to solve the DED optimization problem for a sustainable power system. In particular, a mutation mechanism is combined with a salp–swarm algorithm (SSA) to enhance the exploitation of the search space so that it provides a better population to get the optimal global solution. In addition, we propose a DED handling strategy that involves the use of PV power and load forecasting models based on deep learning techniques. The improved SSA algorithm is validated by ten benchmark problems and applied to the DED optimization problem for a hybrid power system that includes 40 thermal generators and PV and energy storage systems. The experimental results demonstrate the efficiency of the proposed framework with different penetrations of PV.
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Cites background from "Fast yet Accurate Energy-Loss-Asses..."
...The earth receives a massive amount of energy from the sun that can be converted into clean electricity directly through photovoltaics (PVs) [15,16] or indirectly through concentrating solar power (CSP) [17]....
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TL;DR: The effectiveness of the proposed method is demonstrated for solving the optimal allocation problem with different combinations of multi-type DG units and capacitors for minimizing reactive power losses in distribution systems.
Abstract: This paper proposes a method for determining the optimal sites and sizes of multi-type distributed generations (DG) and capacitors for minimizing reactive power losses (RPL) in distribution systems. The proposed method is developed based on generic closed-form analytical expressions for calculating optimal sizes of DG units and capacitors at their candidate sites. The reduction in RPL with DG and capacitors is evaluated using another analytical expression that relates power injections of DG and capacitors with RPL. An optimal power flow algorithm (OPF) is incorporated in the proposed method to consider the constraints of the distribution systems, DG, and capacitors. Various types of DG are considered, and their optimal power factors can be accurately computed while optimizing the sizes of capacitors in a simultaneous manner to reduce RPL. The 69-bus distribution system is used to test the proposed method. An exact search method is employed to verify the accuracy of the proposed method. The effectiveness of the proposed method is demonstrated for solving the optimal allocation problem with different combinations of multi-type DG units and capacitors.
30 citations
TL;DR: In this paper, the impacts of EVs integration approaches on enhancing the operation of utility grids with installed energy storage devices have been investigated, and fuzzy logic controller (FLC) systems have been proposed for controlling EVs and the superconducting magnetic energy storage system (SMES) device.
Abstract: Recently, electric vehicles (EVs) have proven remarkable impacts on reducing pollution and their suitability for utilizing renewable energy sources (RESs) instead of fossil fuels. The continuously increasing number of installed EVs has encouraged their employment for performing additional functionalities in utility grids. This paper provides study for the impacts of EV integration approaches on enhancing the operation of utility grids. The proposed study considers the targeted renewable energy powered utility grids with installed energy storage devices. Wind energy has been utilized as a case study for the RES with considering its stochastic characteristics and its continuous fluctuations with wind speed. Additionally, the superconducting magnetic energy storage system (SMES) device is chosen due to its promising long-life operation. The various aspects of point of common coupling (PCC) voltage fluctuations, reactive power support, leveling active power of the on-peak period, and power losses are considered in the proposed study. Moreover, fuzzy logic controller (FLC) systems have been proposed for controlling EVs and the SMES device. The energy management between the installed EVs, SMES, wind, and utility grid side is achieved through the coordination of the FLC systems. The results show that reduced peak and mean values of total power losses and line active power are obtained by the proposed coordination method. Moreover, improved profiles of the PCC voltage, reactive power support, active power leveling, and sustainable and reliable power supply are obtained by the proposed method for wide operating ranges and modes of operation.
25 citations
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TL;DR: In this paper, an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail, is described, and a reported shortcoming of the basic algorithm is discussed.
Abstract: The technology for building knowledge-based systems by inductive inference from examples has been demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail. Results from recent studies show ways in which the methodology can be modified to deal with information that is noisy and/or incomplete. A reported shortcoming of the basic algorithm is discussed and two means of overcoming it are compared. The paper concludes with illustrations of current research directions.
17,177 citations
TL;DR: This section will review those books whose content and level reflect the general editorial poltcy of Technometrics.
Abstract: This section will review those books whose content and level reflect the general editorial poltcy of Technometrics. Publishers should send books for review to Ejaz Ahmed, Depatment of Mathematics and Statistics, University of Windsor, Windsor, ON N9B 3P4 (techeditor@uwindsoxca). The opinions expressed in this section are those of the reviewers These opinions do not represent positions of the reviewer's organization and may not reflect those of the editors or the sponsoring societies. Listed prices reflect information provided by the publisher and may not be current The book purchase programs of the American Society for Quality can provide some of these books at reduced prices for members. For infbrmation, contact the American Society for Quality at 1-800-248-1946.
2,342 citations
"Fast yet Accurate Energy-Loss-Asses..." refers methods in this paper
...In this paper, we use RegTree because it is simple to use, easy to interpret, and has several merits compared to other techniques [33], [34]....
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TL;DR: In this article, a methodology has been proposed for optimally allocating different types of renewable distributed generation (DG) units in the distribution system so as to minimize annual energy loss.
Abstract: It is widely accepted that renewable energy sources are the key to a sustainable energy supply infrastructure since they are both inexhaustible and nonpolluting. A number of renewable energy technologies are now commercially available, the most notable being wind power, photovoltaic, solar thermal systems, biomass, and various forms of hydraulic power. In this paper, a methodology has been proposed for optimally allocating different types of renewable distributed generation (DG) units in the distribution system so as to minimize annual energy loss. The methodology is based on generating a probabilistic generation-load model that combines all possible operating conditions of the renewable DG units with their probabilities, hence accommodating this model in a deterministic planning problem. The planning problem is formulated as mixed integer nonlinear programming (MINLP), with an objective function for minimizing the system's annual energy losses. The constraints include the voltage limits, the feeders' capacity, the maximum penetration limit, and the discrete size of the available DG units. This proposed technique has been applied to a typical rural distribution system with different scenarios, including all possible combinations of the renewable DG units. The results show that a significant reduction in annual energy losses is achieved for all the proposed scenarios.
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TL;DR: In this article, the authors investigate the effects of renewable energy consumption on the economic growth of major renewable energy consuming countries in the world and conclude that renewable energy investment has a significant positive impact on economic output for 57% of the selected countries.
967 citations
"Fast yet Accurate Energy-Loss-Asses..." refers background in this paper
...photovoltaic (PV) and wind systems, are preferable sources of electricity due to environmental and economical aspects [1]–[4]....
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TL;DR: An overview of the state-of-the-art models and methods applied to the optimal DG placement problem can be found in this article, where the authors analyze and classify current and future research trends in this field.
Abstract: The integration of distributed generation (DG) units in power distribution networks has become increasingly important in recent years. The aim of the optimal DG placement (ODGP) is to provide the best locations and sizes of DGs to optimize electrical distribution network operation and planning taking into account DG capacity constraints. Several models and methods have been suggested for the solution of the ODGP problem. This paper presents an overview of the state of the art models and methods applied to the ODGP problem, analyzing and classifying current and future research trends in this field.
767 citations