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Planning, Modelling, Operation and Assessment of Renewable Energy Power Systems

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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 24220

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Special Issue Editors

Dr. Taskin Jamal

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Guest Editor

Department of Electrical and Electronic Engineering, Ahsanullah University of Science and Technology, Dhaka 1208, Bangladesh and School of Geography, Geology and the Environment, Keele University, Staffordshire ST5 5BG, UK
Interests: power system planning, design and operation; microgrid; solar PV systems; renewable energy integration into grid; power systems management; remote area electrification and energy access
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Prof. Dr. Josep M. Guerrero

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Center for Research on Microgrids, AAU Energy, 9220 Aalborg, Denmark
Interests: microgrids; space power systems; psychobiology; brain networks
Special Issues, Collections and Topics in MDPI journals

Dr. GM Shafiullah

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Guest Editor

Engineering and Energy, College of Science, Health, Engineering and Education, Murdoch University, Perth 6150, Australia
Interests: future electricity networks; microgrids; power systems reliability and stability analysis; renewable energy; and its enabling technologies; renewable energy integration into the grid-connected and off-grid electricity networks; energy efficiency and demand management; hydrogen economy; and sustainability in the energy sector
Special Issues, Collections and Topics in MDPI journals

Md. Nasimul Islam Maruf

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Guest Editor Assistant

Applied Storage Systems Group, Department Electrical Energy Storage, Fraunhofer Institute for Solar Energy Systems (Fraunhofer ISE), Heidenhofstraße 2, 79110 Freiburg, Germany
Interests: energy systems modelling, energy transition, energy storage, sustainable energy systems and smart grid

Special Issue Information

Dear Colleagues,

The earth is now 1.1°C warmer than it was at the start of the industrial revolution. In order to avoid critical warming (i.e., maximum 1.5°C increase), the world will need to mitigate fossil fuel generation by approximately 6% per year between 2020 and 2030. Renewable Energy Power Systems (REPSs) are becoming increasingly essential and receiving much attention as concerns about greenhouse gas emissions, the security of conventional energy supplies and the environmental safety of conventional energy production techniques continue to grow. Integrating renewables into modern-day power systems in various operational modes (microgrid, standalone, grid-connected and hybrid) pursues achieving energy efficiency goals while maintaining low-carbon operations and ensuring energy security. However, integrating renewables poses significant technical and non-technical challenges at both high and low voltage levels, which effectively limits renewable energy resources adoption. Power systems with substantial renewable energy penetration will have various topologies, control techniques and management strategies. The growing use of inverter-based renewable energy resources such as wind and solar photovoltaic, posessing variable output characteristics, has significant impacts on power system dynamics, raising concerns about reliability and resilience. Renewable energy-based power system planning, modelling, operation and control will need to evolve in order to address these challenging issues. Technologically cutting-edge solutions must be used in tandem with conventional network reinforcements. Applications include terrestrial (PV systems, windfarms, etc.), maritime (electric ships, seaport microgrids, offshore windfarms, etc.), aerospace (more electric aircraft, airport microgrids, etc.) and multi-planetary REPSs (lunar/mars base microgrids, satellite and space stations electric power systems). The challenges must be addressed effectively through the development of more efficient power system analysis, planning, operational approaches and performance evaluation mechanisms. This Special Issue aims to address technical and non-technical complexities in the development, management and operations of REPS in order to achieve net-zero emissions by optimal planning and investigation.

This Special Issue includes but is not limited to the following topics:

Review and feasibility studies, resource assessment, site evaluation, system design and case studies of REPS;
Techno-economic evaluation of REPS;
Short, intermediate and long-term energy forecasting mechanism and application;
Power system optimization, planning and control;
Operation and management of microgrid/smart grid;
Advanced control architecture of REPS;
System reliability and resiliency analysis and advanced condition monitoring;
Optimal management and integration of energy storage in REPS;
Grid modelling, simulation and data management with high shares of renewables;
Off-grid electrification challenges for REPS;
Life cycle assessment, policies, energy planning and performance analysis of REPS;
Internet of Things (IoT) technologies for REPS;
Industry 4.0 technologies supporting the REPS;
Modeling of 100% renewable energy systems.

We highly encourage papers on cutting-edge industry practise exemplars that may be leveraged to promote the deployment of renewable energy resources across power systems throughout the world.

Dr. Taskin Jamal
Prof. Dr. Josep M. Guerrero
Dr. GM Shafiullah
Md. Nasimul Islam Maruf
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

renewable energy integration
distributed energy resources
power system analysis, planning and design
power system performance evaluation
techno-economic analysis
power system modelling and optimization.

Published Papers (12 papers)

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Research

18 pages, 761 KiB

Open AccessArticle

Optimal Probabilistic Allocation of Photovoltaic Distributed Generation: Proposing a Scenario-Based Stochastic Programming Model

by Ali Reza Kheirkhah, Carlos Frederico Meschini Almeida, Nelson Kagan and Jonatas Boas Leite

Energies 2023, 16(21), 7261; https://doi.org/10.3390/en16217261 - 26 Oct 2023

Cited by 2 | Viewed by 791

Abstract

The recent developments in the design, planning, and operation of distribution systems indicate the need for a modern integrated infrastructure in which participants are managed through the perceptions of a utility company in an economic network (e.g., energy loss reduction, restoration, etc.). The penetration of distributed generation units in power systems are growing due to their significant influence on the key attributes of power systems. As a result, the placement, type, and size of distributed generations have an essential role in reducing power loss and lowering costs. Power loss minimization, investment and cost reduction, and voltage profile improvement combine to form a conceivable goal function for distributed generation allocation in a constrained optimization problem, and they require a complex procedure to control them in the most appropriate way while satisfying network constraints. Such a complex decision-making procedure can be solved by adjusting the dynamic optimal power flow problem to the associated network. The purpose of the present work is to handle the distributed generation allocation problem for photovoltaic units, attempting to reduce energy and investment costs while accounting for generation unpredictability as well as load fluctuation. The problem is analyzed under various scenarios of solar radiation through a stochastic programming technique because of the intense uncertainty of solar energy resources. The formulation of photovoltaic distributed generation allocation is represented as a mixed-integer second-order conic programming problem. The IEEE 33-bus and real-world 136-bus distribution systems are tested. The findings illustrate the efficacy of the proposed mathematical model and the role of appropriate distributed generation allocation. Full article

(This article belongs to the Special Issue Planning, Modelling, Operation and Assessment of Renewable Energy Power Systems)

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32 pages, 4614 KiB

Open AccessArticle

Techno-Economic and Carbon Emission Assessment of a Large-Scale Floating Solar PV System for Sustainable Energy Generation in Support of Malaysia’s Renewable Energy Roadmap

by Md. Imamul Islam, Mohd Shawal Jadin, Ahmed Al Mansur, Nor Azwan Mohamed Kamari, Taskin Jamal, Molla Shahadat Hossain Lipu, Mohd Nurulakla Mohd Azlan, Mahidur R. Sarker and A. S. M. Shihavuddin

Energies 2023, 16(10), 4034; https://doi.org/10.3390/en16104034 - 11 May 2023

Cited by 7 | Viewed by 3044

Abstract

Energy generation from renewable sources is a global trend due to the carbon emissions generated by fossil fuels, which cause serious harm to the ecosystem. As per the long-term goals of the ASEAN countries, the Malaysian government established a target of 31% renewable energy generation by 2025 to facilitate ongoing carbon emission reductions. To reach the goal, a large-scale solar auction is one of the most impactful initiatives among the four potential strategies taken by the government. To assist the Malaysian government’s large-scale solar policy as detailed in the national renewable energy roadmap, this article investigated the techno-economic and feasibility aspects of a 10 MW floating solar PV system at UMP Lake. The PVsyst 7.3 software was used to develop and compute energy production and loss estimation. The plant is anticipated to produce 17,960 MWh of energy annually at a levelized cost of energy of USD 0.052/kWh. The facility requires USD 8.94 million in capital costs that would be recovered within a payback period of 9.5 years from the date of operation. The plant is expected to reduce carbon emissions by 11,135.2 tons annually. The proposed facility would ensure optimal usage of UMP Lake and contribute to the Malaysian government’s efforts toward sustainable growth. Full article

(This article belongs to the Special Issue Planning, Modelling, Operation and Assessment of Renewable Energy Power Systems)

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20 pages, 1097 KiB

Open AccessArticle

Multi-Objective-Based Charging and Discharging Coordination of Plug-in Electric Vehicle Integrating Capacitor and OLTC

by Junaid Bin Fakhrul Islam, Mir Toufikur Rahman, Shameem Ahmad, Tofael Ahmed, G. M. Shafiullah, Hazlie Mokhlis, Mohamadariff Othman, Tengku Faiz Tengku Mohmed Noor Izam, Hasmaini Mohamad and Mohammad Taufiqul Arif

Energies 2023, 16(5), 2172; https://doi.org/10.3390/en16052172 - 23 Feb 2023

Cited by 1 | Viewed by 1477

Abstract

The integration of plug-in electric vehicles (PEVs) in residential distribution networks demands a significant amount of electrical load where random and uncoordinated charging affects the quality and performance of the distribution network. Random and uncoordinated charging may increase the peak demand and can increase stress on critical network assets such as line, transformer, and switching devices. Moreover, the charging of PEVs in a low network reduces the voltage of the system below the lower limit. On the other hand, using PEVs as storage in the V2G mode can improve the network condition. Therefore, it is critical to properly manage the charging and discharging operation of PEVs. This paper proposes a multi-objective-based charging and discharging coordination of PEVs with the operation of the capacitor and on-load tap changer (OLTC). With the proposed strategy, the distribution network is operated safely, and charging is ensured for all PEVs connected to the network. The main consideration of this research is to reduce the daily power loss, operational cost, and voltage deviation of the system. The metaheuristic optimization binary firefly algorithm (BFA) has been applied to coordinate PEV charging and discharging as well as capacitor and OLTC operation in the system. A modified IEEE 31 bus 23 kV distribution system is used to implement the proposed strategy. From the obtained results, it is found that the combined PEV charging and discharging coordination with capacitor and OLTC operation reduces the power loss and cost by 34.16% and 12.68%, respectively, with respect to uncoordinated charging and enhances the voltage condition of the network. Full article

(This article belongs to the Special Issue Planning, Modelling, Operation and Assessment of Renewable Energy Power Systems)

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23 pages, 3160 KiB

Open AccessArticle

Decarbonization Analysis for Thermal Generation and Regionally Integrated Large-Scale Renewables Based on Minutely Optimal Dispatch with a Kentucky Case Study

by Donovin D. Lewis, Aron Patrick, Evan S. Jones, Rosemary E. Alden, Abdullah Al Hadi, Malcolm D. McCulloch and Dan M. Ionel

Energies 2023, 16(4), 1999; https://doi.org/10.3390/en16041999 - 17 Feb 2023

Cited by 1 | Viewed by 2618

Abstract

Decarbonization of existing electricity generation portfolios with large-scale renewable resources, such as wind and solar photo-voltaic (PV) facilities, is important for a transition to a sustainable energy future. This paper proposes an ultra-fast optimization method for economic dispatch of firm thermal generation using high granularity, one minute resolution load, wind, and solar PV data to more accurately capture the effects of variable renewable energy (VRE). Load-generation imbalance and operational cost are minimized in a multi-objective clustered economic dispatch problem with various generation portfolios, realistic generator flexibility, and increasing levels of VRE integration. The economic feasibility of thermal dispatch scenarios is evaluated through a proposed method of levelized cost of energy (LCOE) for clustered generation portfolios. Effective renewable economics is applied to assess resource adequacy, annual carbon emissions, renewable capacity factor, over generation, and cost to build between thermal dispatch scenarios with incremental increases in VRE penetration. Solar PV and wind generation temporally complement one another in the region studied, and the combination of the two is beneficial to renewable energy integration. Furthermore, replacing older coal units with cleaner and agile natural gas units increases renewable hosting capacity and provides further pathways to decarbonization. Minute-based chronological simulations enable the assessment of renewable effectiveness related to weather-related variability and of complementary technologies, including energy storage for which a sizing procedure is proposed. The generally applicable methods are regionally exemplified for Kentucky, USA, including eight scenarios with four major year-long simulated case studies and 176 subcases using high performance computing (HPC) systems. Full article

(This article belongs to the Special Issue Planning, Modelling, Operation and Assessment of Renewable Energy Power Systems)

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13 pages, 1284 KiB

Open AccessArticle

Energy Efficiency in Modern Power Systems Utilizing Advanced Incremental Particle Swarm Optimization–Based OPF

by Muhammad Bachtiar Nappu, Ardiaty Arief and Willy Akbar Ajami

Energies 2023, 16(4), 1706; https://doi.org/10.3390/en16041706 - 08 Feb 2023

Cited by 6 | Viewed by 1321

Abstract

Since the power grid grows and the necessity for higher system efficiency is due to the increasing number of renewable energy penetrations, power system operators need a fast and efficient method of operating the power system. One of the main problems in a modern power system operation that needs to be resolved is optimal power flow (OPF). OPF is an efficient generator scheduling method to meet energy demands with the aim of minimizing the total production cost of power plants while maintaining system stability, security, and reliability. This paper proposes a new method to solve OPF by using incremental particle swarm optimization (IPSO). IPSO is a new algorithm of particle swarm optimization (PSO) that modifies the PSO structure by increasing the particle size, where each particle changes its position to determine its optimal position. The advantage of IPSO is that the population increases with each iteration so that the optimization process becomes faster. The results of the research on optimal power flow for energy generation costs, system voltage stability, and losses obtained by the IPSO method are superior to the conventional PSO method. Full article

(This article belongs to the Special Issue Planning, Modelling, Operation and Assessment of Renewable Energy Power Systems)

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18 pages, 3948 KiB

Open AccessArticle

Novel Hybrid Modified Modal Analysis and Continuation Power Flow Method for Unity Power Factor DER Placement

by Ardiaty Arief and Muhammad Bachtiar Nappu

Energies 2023, 16(4), 1698; https://doi.org/10.3390/en16041698 - 08 Feb 2023

Viewed by 1093

Abstract

Distributed energy resource (DER) has become an effective attempt in promoting use of renewable energy resources for electricity generation. The core intention of this study is to expand an approach for optimally placing several DER units to attain the most stable performance of the system and the greatest power losses decrease. The recommended technique is established on two analytical methods for analyzing voltage stability: the new modified modal analysis (MMA) and the continuation power flow (CPF) or MMA–CPF methods. The MMA evaluates voltage stability by considering incremental connection relating voltage and active power, which includes the eigenvalue and the related eigenvectors computed from the reduced modified Jacobian matrix. Furthermore, an active participation factor (APF) is computed from the eigenvectors of the reduced modified Jacobian matrix. The CPF method uses a predictor–corrector stepping pattern to reach the solution track and compute the tangent vector sensitivity (TVS). Both APF and TVS indicate each load bus sensitivity in the network. In addition, an objective function regarding losses decrease and eigenvalue is expressed to calculate the best bus position for DER allocation. The proposed MMA–CPF technique has been assessed on a 34-bus RDN and the outcomes demonstrate the effectiveness of the proposed scheme. Full article

(This article belongs to the Special Issue Planning, Modelling, Operation and Assessment of Renewable Energy Power Systems)

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34 pages, 7046 KiB

Open AccessArticle

Multi-Objective Optimization of a Solar Combined Power Generation and Multi-Cooling System Using CO₂ as a Refrigerant

by Rania Hammemi, Mouna Elakhdar, Bourhan Tashtoush and Ezzedine Nehdi

Energies 2023, 16(4), 1585; https://doi.org/10.3390/en16041585 - 04 Feb 2023

Cited by 3 | Viewed by 1677

Abstract

This paper proposes a new combined multi-cooling and power generation system (CMCP) driven by solar energy. Carbon dioxide is used as a refrigerant. A parabolic trough collector (PTC) is employed to collect solar radiation and convert it into thermal energy. The system includes a supercritical CO₂ power system for power production and an ejector refrigeration system with two ejectors to provide cooling at two different evaporating temperatures. The CMCP system is simulated hourly with weather conditions for Tunisia. The PTC mathematical model is used to calculate the heat transfer fluid outlet temperature and the performance of the CMCP system on a specific day of the year. A 1D model of an ejector with a constant area is adopted to evaluate the ejector performance. The system’s performance is evaluated by an energetic and exergetic analysis. The importance of the system’s components is determined by an exergoeconomic analysis. The system is modeled using MATLAB software. A genetic algorithm is used for multi-objective optimization to determine the best values and solutions for the system’s design parameters. The optimal energy and exergy efficiencies were found to be 13.7 percent and 37.55 percent, respectively, and the total product unit cost was 31.15 USD/GJ. Full article

(This article belongs to the Special Issue Planning, Modelling, Operation and Assessment of Renewable Energy Power Systems)

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21 pages, 4916 KiB

Open AccessArticle

Harmonic Source Location and Characterization Based on Permissible Current Limits by Using Deep Learning and Image Processing

by Ahmadreza Eslami, Michael Negnevitsky, Evan Franklin and Sarah Lyden

Energies 2022, 15(24), 9278; https://doi.org/10.3390/en15249278 - 07 Dec 2022

Viewed by 1517

Abstract

Identification of harmonic sources contributing to harmonic distortion, and characterization of harmonic current injected by them, are crucial tasks in harmonic analysis of modern power systems. In this paper, these tasks are addressed based on the permissible current limits recommended by IEEE 519 Standard, with a determination of whether or not injected harmonics are within these limits. If limits are violated, the extent of the violations are characterized to provide information about harmonic current levels in the power system and facilitate remedial actions if necessary. A novel feature extraction method is proposed, whereby each set of harmonic measurements in a power system are transformed into a unique RGB image. Harmonic State Estimation (HSE) is discretized as a classification problem. Classifiers based on deep learning have been developed to subsequently locate and characterize harmonic sources. The approach has been demonstrated effectively both on the IEEE 14-bus system, and on a real transmission network where harmonics have been measured. A comparative study indicates that the proposed technique outperforms state-of-the-art techniques for HSE, including Bayesian Learning (BL), Singular Value Decomposition (SVD) and hybrid Genetic Algorithm Least Square (GALS) method in terms of accuracy and limited number of monitors. Full article

(This article belongs to the Special Issue Planning, Modelling, Operation and Assessment of Renewable Energy Power Systems)

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16 pages, 3323 KiB

Open AccessArticle

General Modelling Method for the Active Distribution Network with Multiple Types of Renewable Distributed Generations

by Haidong Chen, Xueping Pan, Xiaorong Sun and Xiaomei Cheng

Energies 2022, 15(23), 8931; https://doi.org/10.3390/en15238931 - 25 Nov 2022

Viewed by 1170

Abstract

With a proliferation of diverse types of renewable distributed generation (DG) into the distribution network, an equivalent model of an active distribution network (ADN) is extremely important, since the detailed modeling of the whole ADN is much more complex and time consuming. However, different studies developed different model structures of ADNs, which are difficult to be applied in a power system simulation. At the same time, the DG’s low voltage ride through the (LVRT) control was not considered in the existing ADN model, which may lead to a large modelling error. In this paper, a general equivalent model is developed for the ADN with a significant amount of DGs, based on a two-step modelling method. Step one, motivated by the dynamic similarities between the doubly-fed induction generator (DFIG)-based wind turbines, direct drive permanent magnet synchronous generator (DDPMSG)-based wind turbines, and photovoltaic (PV) generation, a general model structure of a renewable DG is initially developed. Then, an aggregation method for the DG’s nonlinear subsystems of the low voltage ride through (LVRT) control and the converter’s current limits are presented. Step two, the ADN model is represented by a general renewable DG model paralleled with a composite load model, and the model is validated, based on an actual distribution network with different renewable DG penetrations and different disturbance degrees. The simulation results show that our model outperforms others with acceptable errors. Full article

(This article belongs to the Special Issue Planning, Modelling, Operation and Assessment of Renewable Energy Power Systems)

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26 pages, 1595 KiB

Open AccessArticle

Impact of Time Resolution on Curtailment Losses in Hybrid Wind-Solar PV Plants

by Antun Meglic and Ranko Goic

Energies 2022, 15(16), 5968; https://doi.org/10.3390/en15165968 - 17 Aug 2022

Cited by 3 | Viewed by 1441

Abstract

Curtailment losses for large-scale hybrid wind–solar photovoltaic (PV) plants with a single grid connection point are often calculated in 1 h time resolution, underestimating the actual curtailment losses due to the flattening of power peaks occurring in shorter time frames. This paper analyses the curtailment losses in hybrid wind–PV plants by utilising different time resolutions of wind and PV production while varying the grid cut-off power, wind/solar PV farm sizes, and shares of wind/PV capacity. Highly resolved 1 s measurements from the operational wind farm and pyranometer are used as an input to specialized wind and PV farm power production models that consider the smoothing effect. The results show that 15 min resolution is preferred over 1 h resolution for large-scale hybrid wind–PV plants if more accurate assessment of curtailment losses is required. Although 1 min resolution additionally increases the estimation accuracy over 15 min resolution, the improvement is not significant for wind and PV plants with capacity above approx. 10 MW/10 MWp. The resolutions shorter than 1 min do not additionally increase the estimation accuracy for large-scale wind and PV plants. More attention is required when estimating curtailment losses in wind/PV plants with capacity below approx. 10 MW/10 MWp, where higher underestimation can be expected if lower time resolutions are used. Full article

(This article belongs to the Special Issue Planning, Modelling, Operation and Assessment of Renewable Energy Power Systems)

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23 pages, 5610 KiB

Open AccessArticle

Virtual Net-Metering Option for Bangladesh: An Opportunity for Another Solar Boom like Solar Home System Program

by A. S. M. Mominul Hasan

Energies 2022, 15(13), 4616; https://doi.org/10.3390/en15134616 - 24 Jun 2022

Viewed by 3767

Abstract

This study explores the virtual net-metering (VNM) option for enabling inclusive investment opportunities in renewable energy for self-consumption in Bangladesh. It focuses on consumers, such as households and businesses in multi-family and multi-story buildings, who cannot participate in traditional net-metering policy due to technical and space constraints. The study adopted the classical socket parity method to identify suitable consumers for VNM. Then it determined the consumer benefits of using VNM by calculating the net present cost (NPC) and discounted payback period. The results reveal that several consumer categories can significantly save on electricity costs through VNM. For example, commercial consumers can save more than 50% of their electricity bills by investing in a VNM-enabled remote solar power plant with a discounted payback period of fewer than six years. The discussion articulates more comprehensive benefits of VNM. It addresses challenges for renewable energy development by identifying local opportunities. Therefore, this research can help initiate policy dialogues and create momentum for citizen investments in the energy transition. The proposed approach can also be used to analyze the economic feasibility and potential of VNM in other countries. Full article

(This article belongs to the Special Issue Planning, Modelling, Operation and Assessment of Renewable Energy Power Systems)

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26 pages, 2648 KiB

Open AccessArticle

Automated Detection of Electric Energy Consumption Load Profile Patterns

by Ignacio Benítez and José-Luis Díez

Energies 2022, 15(6), 2176; https://doi.org/10.3390/en15062176 - 16 Mar 2022

Cited by 1 | Viewed by 2242

Abstract

Load profiles of energy consumption from smart meters are becoming more and more available, and the amount of data to analyse is huge. In order to automate this analysis, the application of state-of-the-art data mining techniques for time series analysis is reviewed. In particular, the use of dynamic clustering techniques to obtain and visualise temporal patterns characterising the users of electrical energy is deeply studied. The performed review can be used as a guide for those interested in the automatic analysis and groups of behaviour detection within load profile databases. Additionally, a selection of dynamic clustering algorithms have been implemented and the performances compared using an available electric energy consumption load profile database. The results allow experts to easily evaluate how users consume energy, to assess trends and to predict future scenarios. Full article

(This article belongs to the Special Issue Planning, Modelling, Operation and Assessment of Renewable Energy Power Systems)

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