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A Step toward Sustainable Energy Management in Modern Electrical Power Systems Operation and Planning

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 6282

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Special Issue Editors

Dr. Ehsan Naderi

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Guest Editor

Department of Electrical Engineering, College of Engineering and Computer Science, Arkansas State University, Jonesboro, AR 72401, USA
Interests: modern power systems; smart microgrids; optimization; machine learning; cybersecurity
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Fernando Vladimir Cerna Nahuis

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Guest Editor

Department of Electrical Engineering, Federal University of Roraima, Boa Vista 69310-000, Brazil
Interests: efficient energy management of electricity distribution networks, microgrids, energy communities; sustainable cities; electromobility

Special Issue Information

Dear Colleagues,

Depletion of fossil fuels and global warming awareness are among the most important motivations for upgrading electrical power systems. Thus, current power systems need to be modified by implementing renewable energy distributed generation (DG) units (e.g., wind power and photovoltaic) to reduce supply infrastructure stress, power transmission loss, pollutant emissions, and energy costs. In this regard, smart grids (SGs) are recently introduced as a new platform to integrate: 1) a flexible energy generation in the form of virtual power plants and 2) a flexible energy consumption by encouraging end-use customers to use electricity when it is cheapest, not required (i.e., demand response).

This new platform should address the two following challenges: the non-dispatchable nature of renewable energy in DG units and the rapid growth of residential customers in the electricity distribution systems. Hence, SGs enable mutual communication between stakeholders (mainly producers and consumers) via intelligent computerized technology. One of the most important challenges of modern power system operation is intersection of information and communication technology (ICT) and physical equipment leading to a new framework referred to as cyber-physical power system (CPPS).

From the energy management point of view, such frameworks facilitate the task of automated system operation with less involvement of decision makers, which is, in fact, an essence of smarter grids in the future. Nevertheless, it can negatively affect the security systems due to vulnerability of cyber-physical power systems to cyberattacks, more specifically false data injection attacks. Toward this end, we are looking for solutions that result in efficient, reliable, secure energy management techniques for SGs to address the aforementioned issues.

Researchers from academia, industry, and government are invited to submit their original and unpublished work to this Special Issue. The topics of interest include but are not limited to the following:

Enhancing the performance of power grids in different stages such as generation, transmission, and distribution;
Providing promising operational schemes to maximize the insertion of renewable DG sources;
Analyzing the behaivior of SGs targeted by different types of cyber attacks (e.g., denial of service, false data injection, etc.);
Improving the accuracy of detection mechanisms (including prevention and planning, mitigation and response, and system recovery) against cyberattacks targeting power networks;
Distribution expansion planning considering DGs and storage systems;
Proposing efficient coordination schemes for DGs and energy storage systems in order to mitigate peak demand rebound in the power distribution networks;
Demand response strategies based to support the large-scale adoption DGs in electrical distribution networks.

Dr. Ehsan Naderi
Prof. Dr. Fernando Vladimir Cerna Nahuis
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. Sustainability 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 2400 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

energy management
storage systems
smart grids
microgrids
electricity markets
optimization techniques
cybersecurity
cyber–physical power systems
reliability

Published Papers (5 papers)

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Research

17 pages, 2784 KiB

Open AccessArticle

Quantitative Frequency Security Assessment of Modern Power System Considering All the Three Indicators in Primary Frequency Response

by Fei Tang, Junfeng Qi, Zhuo Liu, Yuhan Guo and Huipeng Deng

Sustainability 2023, 15(18), 13569; https://doi.org/10.3390/su151813569 - 11 Sep 2023

Viewed by 726

Abstract

The primary frequency response scale is deteriorating in the modern power system due to the high penetration of different power devices. Frequency security assessments are essential for the operation or stability-checking of the power system. Firstly, this paper establishes the Unified Transfer Function Structure (UTFS) of power systems with highly penetrated wind turbines. Based on the UTFS, this paper analyzes the three indicators of the primary frequency responses. Secondly, to better assess the security of the frequency, the secondary frequency drop (SFD) is avoided, with the frequency response parameters of the wind turbines calculated. Moreover, considering all three indicators of the primary frequency response, this paper proposes a frequency security margin index (FSMI). The FSMI divides the system stability margin into three levels, quantitively and linearly representing the frequency response capability of different power devices. Finally, to show the effectiveness and practicability of the FSMI, this paper establishes a simulation model with high wind energy penetration, including four machines and four zones in DigSILENT. Based on the FSMI, the frequency stability margins in different typical operating scenarios are divided into three zones: “Absolut secure”, “Secure” and “Relative secure”. The FSMI also shows the dominant frequency stability problem and the risk of system frequency instability for each zone. Considering the checking principles, the frequency stability margin is equivalently expanded by calculating the energy storage’s minimum frequency response capacity. Full article

(This article belongs to the Special Issue A Step toward Sustainable Energy Management in Modern Electrical Power Systems Operation and Planning)

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27 pages, 2487 KiB

Open AccessArticle

Developing an Integration of Smart-Inverter-Based Hosting-Capacity Enhancement in Dynamic Expansion Planning of PV-Penetrated LV Distribution Networks

by Masoud Hamedi, Hossein Shayeghi, Seyedjalal Seyedshenava, Amin Safari, Abdollah Younesi, Nicu Bizon and Vasile-Gabriel Iana

Sustainability 2023, 15(14), 11183; https://doi.org/10.3390/su151411183 - 18 Jul 2023

Cited by 2 | Viewed by 1089

Abstract

With the penetration of distributed energy resources (DERs), new network challenges arise that limit the hosting capacity of the network, which consequently makes the current expansion-planning models inadequate. Smart inverters as a promising tool can be utilized to enhance the hosting capacity. Therefore, in response to technical, economic, and environmental challenges, as well as government support for renewable resources, especially domestic solar resources located at the point of consumption, this paper is an endeavor to propose a smart-inverter-based low-voltage (LV) distribution expansion-planning model. The proposed model is capable of dynamic planning, where multiple periods are considered over the planning horizon. In this model, a distribution company (DISCO), as the owner of the network, intends to minimize the planning and operational costs. Optimal loading of transformers is considered, which is utilized to operate the transformers efficiently. Here, to model the problem, a mixed-integer nonlinear programming (MINLP) model is utilized. Using the GAMS software, the decision variables of the problem, such as the site and size of the installation of distribution transformers, and their service areas specified by the LV lines over the planning years, and the reactive power generation/absorption of the smart inverters over the years, seasons, and hours are determined. To tackle the operational challenges such as voltage control in the points of common coupling (PCC) and the limitations in the hosting capacity of the network for the maximized penetration level of PV cells, a smart-inverter model with voltage control capability in PCC points is integrated into the expansion-planning problem. Then, a two-stage procedure is proposed to integrate the reactive power exchange capability of smart inverters in the distribution expansion planning. Based on the simulations of a residential district with PV penetration, results show that by a 14.7% share of PV energy generation, the loss cost of LV feeders is reduced by 28.3%. Also, it is observed that by optimally making use of the reactive power absorption capability of the smart inverters, the hosting capacity of the network is increased by 50%. Full article

(This article belongs to the Special Issue A Step toward Sustainable Energy Management in Modern Electrical Power Systems Operation and Planning)

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16 pages, 3163 KiB

Open AccessArticle

Analysis of the Influencing Factors of Power Demand in Beijing Based on the LMDI Model

by Deguo Su, Beibei Tan, Anbing Zhang and Yikai Hou

Sustainability 2023, 15(10), 7913; https://doi.org/10.3390/su15107913 - 11 May 2023

Cited by 3 | Viewed by 1194

Abstract

Since the reform and opening-up, under the new economic situation and policy, the rapid growth of power demand in Beijing is threatening the sustainable development of China’s economy and environment. To recognize the driving factors of electricity consumption growth and offer policy implications, based on the data of electricity consumption, the Gross Domestic Product (GDP) and the resident population in Beijing from 1990 to 2021, this research used the Kaya-equation and logarithmic mean divisia index (LMDI) model to decompose the growth of power demand in Beijing into the quantitative contribution of each driving factor from the perspective of industrial electricity consumption and residential electricity consumption. The results of the decomposition analysis show that, as far as industrial electricity consumption is concerned, the contribution rates of economic growth, electricity consumption intensity and output value structure to industrial electricity growth are 234.26%, −109.01% and −25.25%, respectively, which shows that economic growth is the primary driving force promoting the growth of industrial electricity demand. Power consumption intensity is the main reason for restraining the growth of industrial power demand, the growth rate is sliding and the contribution of the industrial structure is relatively small; as far as residential power consumption is concerned, the contribution rates of per capita power consumption and population size to residential power growth are 68.13% and 31.87%, respectively, which indicates that per capita power consumption is the main factor promoting the growth of residential power demand, followed by the total population. The study results show that the consumption of electric power would increase if Beijing’s economy and urbanization keep developing, and optimizing the industry structure, improving the efficiency of electric energy utilization and adopting clean power energy are the main approaches to making Beijing’s consumption of electric power decrease. Full article

(This article belongs to the Special Issue A Step toward Sustainable Energy Management in Modern Electrical Power Systems Operation and Planning)

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17 pages, 2377 KiB

Open AccessArticle

Non-Linear Programming-Based Energy Management for a Wind Farm Coupled with Pumped Hydro Storage System

by Jannet Jamii, Mohamed Trabelsi, Majdi Mansouri, Mohamed Fouazi Mimouni and Wasfi Shatanawi

Sustainability 2022, 14(18), 11287; https://doi.org/10.3390/su141811287 - 8 Sep 2022

Cited by 7 | Viewed by 1408

Abstract

The large-scale integration of renewable energy sources (RESs) has become one of the most challenging topics in smart grids. Indeed, such an integration has been causing significant grid stability issues (voltage and frequency control) due to the dependency of RESs on meteorological conditions. To this end, their integration must be accompanied by alternative sources of energy to attenuate the power fluctuations. Energy storage systems (ESSs) can provide such flexibility by mitigating local peaks/drops in load demands/renewable power generation. Therefore, the development of energy management strategies (EMSs) has been attracting considerable attention in the management of the power generated from the RESs associated with that which is stored/provided by the ESSs. Then, the optimization of the EMS leads to substantial savings in operation and maintenance and to correct decisions for the future. This study presents an optimized EMS for a wind farm, coupled with a pumped hydro energy system (PHES). The proposed day-ahead EMS consists of two stages, namely the forecasting and the optimization stages. The forecasting module is responsible for predicting the wind power generation and load demand. A random forest (RF) method is used to perform the power forecasting after the extraction of the weather data features using a kernel principal component analysis (KPCA) technique. Then, a nonlinear programming (NLP)-based optimization technique is proposed to define the day-ahead optimal energy of the PHES. The purpose of the optimization is to maximize the profit cost in a day-ahead horizon, taking into consideration the system constraints. Full article

(This article belongs to the Special Issue A Step toward Sustainable Energy Management in Modern Electrical Power Systems Operation and Planning)

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20 pages, 3991 KiB

Open AccessArticle

Optimal Scheduling of Thermoelectric Coupling Energy System Considering Thermal Characteristics of DHN

by Guangdi Li, Qi Tang, Bo Hu and Min Ma

Sustainability 2022, 14(15), 9764; https://doi.org/10.3390/su14159764 - 8 Aug 2022

Viewed by 1213

Abstract

In a thermoelectric coupling energy system, renewable energy is often curtailed by the uncertainty of the power generation. Besides, the integration of renewable energy is restricted by the inflexible operation of combined heat and power units due to the strong coupling relationship between power generation and heating supply, especially in winter. Utilization of the district heating network, a heat storage feature, is a cost-effective measure to improve the overall system operational flexibility. In this paper, a new heat characteristic index is proposed in a district heating system, which is applied to measure the impact of the flexibility of combined heat and power units’ output. Furthermore, in order to increase the reliability of an electric power system, a probabilistic model of combined heat and power units’ spinning reserves capacity related to confidence level K is established. What is more, the two indexes K and thermal characteristic index have a coupled relationship. In addition, for model solving methodology, the discretized step transformation and constant mass flow and variables temperature method is adopted to transform the non-linear system model into linear programming form. Case studies are carried out to show the linkage between system costs, K and thermal characteristic index. The optimal result can achieve balance among the system reliability, flexibility and economy. Full article

(This article belongs to the Special Issue A Step toward Sustainable Energy Management in Modern Electrical Power Systems Operation and Planning)

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