Research

17 pages, 3169 KiB

Open AccessArticle

Fast Heuristic AC Power Flow Analysis with Data-Driven Enhanced Linearized Model

by Xingpeng Li

Energies 2020, 13(13), 3308; https://doi.org/10.3390/en13133308 - 28 Jun 2020

Cited by 2 | Viewed by 2202

Though the full AC power flow model can accurately represent the physical power system, the use of this model is limited in practice due to the computational complexity associated with its non-linear and non-convexity characteristics. For instance, the AC power flow model is [...] Read more.

Though the full AC power flow model can accurately represent the physical power system, the use of this model is limited in practice due to the computational complexity associated with its non-linear and non-convexity characteristics. For instance, the AC power flow model is not incorporated in the unit commitment model for practical power systems. Instead, an alternative linearized DC power flow model is widely used in today’s power system operational and planning tools. However, DC power flow model will be useless when reactive power and voltage magnitude are of concern. Therefore, a linearized AC (LAC) power flow model is needed to address this issue. This paper first introduces a traditional LAC model and then proposes an enhanced data-driven linearized AC (DLAC) model using the regression analysis technique. Numerical simulations conducted on the Tennessee Valley Authority (TVA) system demonstrate the performance and effectiveness of the proposed DLAC model. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2018)

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15 pages, 4700 KiB

Open AccessArticle

Development of an Integrated Assessment Model at Provincial Level: GCAM-Korea

by Seungho Jeon, Minyoung Roh, Jaeick Oh and Suduk Kim

Energies 2020, 13(10), 2565; https://doi.org/10.3390/en13102565 - 18 May 2020

Cited by 7 | Viewed by 4035

Abstract

Integrated assessment modeling at a higher spatial scale is a prerequisite for deriving region-specific implications from the model. The Global Change Assessment Model (GCAM) was chosen for GCAM-Korea, a detailed integrated assessment model (IAM) of Korea’s socioeconomic and energy systems. GCAM-Korea is developed [...] Read more.

Integrated assessment modeling at a higher spatial scale is a prerequisite for deriving region-specific implications from the model. The Global Change Assessment Model (GCAM) was chosen for GCAM-Korea, a detailed integrated assessment model (IAM) of Korea’s socioeconomic and energy systems. GCAM-Korea is developed based on GCAM-USA. Data for 16 provinces have been collected from various sources. Some data have been pre-processed to fit within the specific structure of GCAM-USA data. Other types of data were newly added through new structures. The model results were validated to be compatible with historical trends. It was found that provincial energy plans or policies could be compiled in detail using the proposed model while maintaining consistency with national level modeling results. The cross-border air pollution issue in Northeast Asia could also be addressed by combining GCAM-Korea and air quality models in the future. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2018)

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12 pages, 2849 KiB

Open AccessArticle

Research on Modeling of a Micro Variable-Pitch Turboprop Engine Based on Rig Test Data

by Xiaochun Zhao, Xianghua Huang and Tianqian Xia

Energies 2020, 13(7), 1768; https://doi.org/10.3390/en13071768 - 07 Apr 2020

Cited by 2 | Viewed by 2261

Abstract

Exact component characteristics are required for establishing an accurate component level aeroengine model. When component characteristics is lacking, the dynamic coefficient method based on test data, is suitable for establishing a single-input and single-output aeroengine model. When it is applied to build multiple-input, [...] Read more.

Exact component characteristics are required for establishing an accurate component level aeroengine model. When component characteristics is lacking, the dynamic coefficient method based on test data, is suitable for establishing a single-input and single-output aeroengine model. When it is applied to build multiple-input, multiple-output aeroengine models, some parameters are assumed to be unchanged, which causes large error. An improved modeling method based on rig data is proposed to establish a double-input, double-output model for a micro variable-pitch turboprop engine. The input variables are fuel flow and pitch angle, and the output variables are rotational speeds of the core engine and the propeller. First, in order to gather modeling data, a test bench is designed and rig tests are carried out. Then, two conclusions are obtained by analyzing the rig data, based on which, the power turbine output is taken as the function of the core speed and the propeller speed. The established model has the property that the input variables can vary arbitrarily within the defined domain, without any restriction to the output variables. Simulation results showed that the model has a high dynamic and steady-state accuracy. The maximum error was less than 8%. The real-time performance was greatly improved, compared to the component level model. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2018)

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16 pages, 2077 KiB

Open AccessArticle

Direct Consideration of Eddy Current Losses in Laminated Magnetic Cores in Finite Element Method (FEM) Calculations Using the Laplace Transform

by Marek Gołębiowski, Lesław Gołębiowski, Andrzej Smoleń and Damian Mazur

Energies 2020, 13(5), 1174; https://doi.org/10.3390/en13051174 - 04 Mar 2020

Cited by 3 | Viewed by 2706

Abstract

The following article presents a computation procedure that enables us to simulate the dynamic states of electric machines with a laminated magnetic core, with direct consideration of the eddy current losses. The presented approach enables a significant reduction of the simulation process computational [...] Read more.

The following article presents a computation procedure that enables us to simulate the dynamic states of electric machines with a laminated magnetic core, with direct consideration of the eddy current losses. The presented approach enables a significant reduction of the simulation process computational complexity. The verification of the obtained data correctness is based on a detailed balance of energy and power in the investigated system. The correctness of the obtained results was also confirmed by comparing them with the results included in norms that describe the losses in laminated sheets. The presented approach is based on expressing the equivalent permeability of transformer metal sheets by using RC or RL circuits. The impedances of these circuits are treated as the transmittance of Infinite Impulse Response filters (IIR) of the Laplace s variable. In this form they are implemented in direct calculations of the dynamics of electric machines based on field-circuital models, using the Finite Element Method (FEM). In this way, we present the method of including eddy current losses in laminated metal circuits of chokes or transformers, during calculations using the finite element method, with the IIR filter in the domain of the variable s of the Laplace transform. Eddy current losses are directly included in the calculation process. Therefore, they have a direct impact on the transient state waveforms. However, the use of the Laplace variable s caused an excessive increase in the number of state variables, and the overall computational efficiency of the presented method is sufficiently low so as to be used in the simulation process of electrical machine dynamic states with a relatively large number of elements in the FE Model. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2018)

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16 pages, 2626 KiB

Open AccessArticle

Computationally Efficient Method of Co-Energy Calculation for Transverse Flux Machine Based on Poisson Equation in 2D

by Andrzej Smoleń, Lesław Gołębiowski, Marek Gołębiowski and Damian Mazur

Energies 2019, 12(22), 4340; https://doi.org/10.3390/en12224340 - 14 Nov 2019

Cited by 5 | Viewed by 1985

Abstract

The article presents an original method for numerical determination of the value of magnetic co-energy of a transverse construction motor. The aim of the developed method is initial determination of the co-energy value for the analyzed structure in the function of rotor rotation [...] Read more.

The article presents an original method for numerical determination of the value of magnetic co-energy of a transverse construction motor. The aim of the developed method is initial determination of the co-energy value for the analyzed structure in the function of rotor rotation angle. The main requirement set to the presented method was the lowest possible complexity of the process computation, lack of the necessity to apply costly dedicated software, as well as creating construction 3D models. These requirements were met by applying specific cross-section/development of the analyzed machine geometry, as well as application of specific boundary conditions, which enabled reduction of the analyzed problem to solving a Poisson equation in 2D. The calculations were done with the Finite Element Method. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2018)

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24 pages, 5431 KiB

Open AccessArticle

Optimal Load Dispatch in Competitive Electricity Market by Using Different Models of Hopfield Lagrange Network

by Thanh Long Duong, Phuong Duy Nguyen, Van-Duc Phan, Dieu Ngoc Vo and Thang Trung Nguyen

Energies 2019, 12(15), 2932; https://doi.org/10.3390/en12152932 - 30 Jul 2019

Cited by 7 | Viewed by 2553

Abstract

In this paper, a Hopfield Lagrange network (HLN) method is applied to solve the optimal load dispatch (OLD) problem under the concern of the competitive electric market. The duty of the HLN is to determine optimal active power output of thermal generating units [...] Read more.

In this paper, a Hopfield Lagrange network (HLN) method is applied to solve the optimal load dispatch (OLD) problem under the concern of the competitive electric market. The duty of the HLN is to determine optimal active power output of thermal generating units in the aim of maximizing the benefit of electricity generation from all available units. In addition, the performance of the HLN is also tested by using five different functions consisting of the logistic, hyperbolic tangent, Gompertz, error, and Gudermanian functions for updating outputs of continuous neurons. The five functions are tested on two systems with three units and 10 units considering two revenue models in which the first model considers payment for power delivered and the second model concerns payment for reserve allocated. In order to evaluate the real effectiveness and robustness of the HLN, comparisons with other methods such as particle swarm optimization (PSO), the cuckoo search algorithm (CSA) and differential evolution (DE) are also implemented on the same systems. High benefits and fast execution time from the HLN lead to a conclusion that the HLN should be applied for solving the OLD problem in a competitive electric market. Among the five applied functions, error function is considered to be the most effective one because it can support the HLN to find the highest benefit and reach the fastest convergence with the smallest number of iterations. Thus, it is suggested that error function should be used for updating outputs for continuous neurons of the HLN. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2018)

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21 pages, 5099 KiB

Open AccessArticle

A Multi-Objective Energy and Environmental Systems Planning Model: Management of Uncertainties and Risks for Shanxi Province, China

by Changyu Zhou, Guohe Huang and Jiapei Chen

Energies 2018, 11(10), 2723; https://doi.org/10.3390/en11102723 - 11 Oct 2018

Cited by 7 | Viewed by 2512

Abstract

In this study, a fuzzy chance-constrained fractional programming (FCFP) approach is developed to help tackle various uncertainties involved in electric power systems (EPSs) management. The FCFP approach is capable of solving ratio optimization decision problems in power systems associated with random and fuzzy [...] Read more.

In this study, a fuzzy chance-constrained fractional programming (FCFP) approach is developed to help tackle various uncertainties involved in electric power systems (EPSs) management. The FCFP approach is capable of solving ratio optimization decision problems in power systems associated with random and fuzzy information by chance-constrained programming (CCP) method, fuzzy measure programming, fractional programming (FP) into a general framework. It can tackle inexact information expressed as fuzzy set and probability distributions, comprehensively reflect the decision maker’s pessimistic and optimistic preferences, and balance dual objectives of system economy and sustainability. To demonstrate its applicability, FCFP approach is then applied to a case study of Shanxi Province, a typical coal-heavy electricity region in China. The results indicate that the FCFP approach reveals uncertain interactions among the decision maker’s preferences and various random variables. Reasonable solutions have been generated for Shanxi EPS management practices, which can provide strategies in mitigating pollutant emissions, reducing system costs, and promoting coalbed methane as an alternative energy source for coal-fired and plays an essential role in Shanxi’s municipal planning. The solutions will help decision makers generate alternatives in the event of the reducing coal-fired power generation and could be applicable in other coal-heavy electricity regions. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2018)

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23 pages, 3611 KiB

Open AccessArticle

Linearized Stochastic Scheduling of Interconnected Energy Hubs Considering Integrated Demand Response and Wind Uncertainty

by Yining Zhang, Yubin He, Mingyu Yan, Chuangxin Guo and Yi Ding

Energies 2018, 11(9), 2448; https://doi.org/10.3390/en11092448 - 14 Sep 2018

Cited by 30 | Viewed by 3455

Abstract

In the context of the Energy Internet, customers are supplied by energy hubs (EH), while the EHs are interconnected through an upper-level transmission system. In this paper, a stochastic scheduling model is proposed for the interconnected EHs considering integrated demand response (DR) and [...] Read more.

In the context of the Energy Internet, customers are supplied by energy hubs (EH), while the EHs are interconnected through an upper-level transmission system. In this paper, a stochastic scheduling model is proposed for the interconnected EHs considering integrated demand response (DR) and wind variation. The whole integrated energy system (IES) is linearly modeled for the first time. The output-input relationship within the energy hub is denoted as a linearized matrix, while the upper-level power and natural gas transmission systems are analyzed through piecewise linearization method. A novel sequential linearization method is further proposed to balance computational efficiency and approximation accuracy. Integrated demand response is introduced to smooth out demand curve, considering both internal DR achieved by the optimal energy conversion strategy within energy hubs, and external DR achieved by demand adjustment on the customer’s side. Distributed energy storage like natural gas and heat storage are considered to provide buffer for system operation. The proposed stochastic model is solved by scenario-based optimization with a backward scenario reduction strategy. Numerical tests on a three-hub and seventeen-hub interconnected system that validates the effectiveness of the proposed scheduling model and solution methodology. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2018)

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15 pages, 869 KiB

Open AccessArticle

Integrated Energy Planning with a High Share of Variable Renewable Energy Sources for a Caribbean Island

by Dominik Franjo Dominković, Greg Stark, Bri-Mathias Hodge and Allan Schrøder Pedersen

Energies 2018, 11(9), 2193; https://doi.org/10.3390/en11092193 - 22 Aug 2018

Cited by 33 | Viewed by 5300

Abstract

Although it can be complex to integrate variable renewable energy sources such as wind power and photovoltaics into an energy system, the potential benefits are large, as it can help reduce fuel imports, balance the trade, and mitigate the negative impacts in terms [...] Read more.

Although it can be complex to integrate variable renewable energy sources such as wind power and photovoltaics into an energy system, the potential benefits are large, as it can help reduce fuel imports, balance the trade, and mitigate the negative impacts in terms of climate change. In order to try to integrate a very large share of variable renewable energy sources into the energy system, an integrated energy planning approach was used, including ice storage in the cooling sector, a smart charging option in the transport sector, and an excess capacity of reverse osmosis technology that was utilised in order to provide flexibility to the energy system. A unit commitment and economic dispatch tool (PLEXOS) was used, and the model was run with both 5 min and 1 h time resolutions. The case study was carried out for a typical Caribbean island nation, based on data derived from measured data from Aruba. The results showed that 78.1% of the final electricity demand in 2020 was met by variable renewable energy sources, having 1.0% of curtailed energy in the energy system. The total economic cost of the modelled energy system was similar to the current energy system, dominated by the fossil fuel imports. The results are relevant for many populated islands and island nations. Full article

(This article belongs to the Special Issue Applied Energy System Modeling 2018)

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