Use Of Planning Research Articles

Uncertainty parameters of battery energy storage integrated grid and their modeling approaches: A review and future research directions

The continuously growing population and urban growth rates are responsible for the sharp rise in energy consumption, which leads to increased CO2 emissions and demand-supply imbalances. The power sector is switching to alternative energy sources, including renewable energy resources (RES) such as Photovoltaic (PV) and wind power (WP) and battery energy storage systems (BESS), among others, due to an increase in the use of fossil fuels and their shortage. Since the power generation of these resources is uncertain due to climatic fluctuations and the direct integration of these resources into the power grid is very complex due to the issues such as; voltage and frequency regulation, overloading of active transmission lines, and supply-demand disparity, the research on system uncertainties is receiving increasing attention. This study provides a comprehensive analysis of the several parameters of uncertainty, approaches for dealing with the uncertainty in battery energy storage (BES)-based RES integrated grid, and the advantages and disadvantages of each method. Moreover, various analytical and numerical approaches were developed for integrating RES and BESS into the power grid, including probabilistic methods, possibilistic methods, robust optimization-based techniques, and machine learning algorithms. The comparative analysis of these approaches highlights their relative strengths and weaknesses, providing a valuable resource for researchers and utility planners. Additionally, this review paper identifies several issues and challenges associated with the integration of RES and BESS into the power grid, such as power quality, economical effect, battery aging effect, and environmental effect. Furthermore, the paper suggests a few future research directions, including the development of novel models for analyzing uncertainty in power systems, coordination of uncertainty parameters, integration of BESS into RES and grid, power electronics integration, and environmental factor. Overall, this article's novel contributions include a comprehensive analysis of uncertainty parameters, a comparative analysis of uncertainty modeling approaches, an identification of critical issues and challenges, and the suggestion of future research directions to promote a sustainable and reliable power system. This article will aid in defining the requirements and specifications for novel models for analyzing uncertainty in power systems. The discussion and analysis will assist researchers and utility planners in selecting a suitable uncertainty modeling approach with significant penetrations of distributed RESs, which can lead to achieving a reliable and sustainable power system.

인천광역시의 기후적응 우선순위 선정 및 계획에서의 활용방안

인천광역시의 기후적응 우선순위 선정 및 계획에서의 활용방안

A Study on Utilization Plan for Metropolitan Support Account of Local Extinction Reaction Fund

A Study on Utilization Plan for Metropolitan Support Account of Local Extinction Reaction Fund

Predicting residential water and electricity usage profiles with a temporal histogram model

The temporal histogram model and synthesiser that is presented in this paper statistically models the unique usage behaviour of electricity or hot water usage for individual residential households. These can be used to model behaviour and do simulations for demand management and planning. The model takes into consideration both seasonal variations and weekday differences and the synthesiser autonomously generates hourly synthetic profiles. We use 1,200 household electricity profiles, each spanning over one year, and 77 hot water usages, each spanning at least one month for each season, to obtain the results. The results showed that the model can accurately characterise the usage behaviour for a household and accurately predict future usage. The model also has a novel capability to model the relationship between usages at different times of the day, which further increases its usefulness in city-wide utility planning. This reduced hourly prediction errors by 19.6% for electricity usage and 25.0% for hot water usage when the first twelve hours of a day are known. This model can be used as an effective tool for demand-side management strategies and providing insight into utility planning in cities.

Reporting England's progress towards the ambitions in the UK action plan for antimicrobial resistance: the English surveillance programme for antimicrobial utilisation and resistance (ESPAUR).

The plans for a new antimicrobial utilization and resistance national surveillance programme, alongside the development of quality measures and methods to monitor unintended outcomes of antimicrobial stewardship and both public and professional behaviour interventions were published in 2013. Since then, England has published an annual surveillance report including outlining progress against the ambitions of the UK national action plans on antimicrobial resistance (2013 to 2018 and 2019 to 2024). A decade later we provide a brief update on progress so far, with a focus on key highlights from the latest report published in November 2022. We also provide our recommendations for areas of focus as we move into the next decade. From an initial focus on antibiotic consumption and resistance, the report now includes surveillance data for antifungals, antivirals (including novel agents, such as those targeting SARS-CoV-2) and antimalarials. Evaluation of key stewardship interventions including professional and public engagement initiatives are also reported, as well as progress against NHS England's (NHSE's) improvement measures.

Past and future adverse response of terrestrial water storages to increased vegetation growth in drylands

The response of terrestrial water storages to dryland vegetation growth remains poorly understood. Using multiple proxies from satellite observations and model outputs, we show an overall increase (decrease) in vegetation growth (terrestrial water storages) across drylands globally during 1982–2016. Terrestrial water storages in greening drylands correlate negatively with vegetation growth, particularly for cropland-dominated regions, and such response is pronounced when the growth rate of vegetation productivity is high. Reduction in terrestrial water storage is dominated by precipitation and evapotranspiration variability rather by than runoff. We predict reduction in terrestrial water storage of 41–84% by 2100, accompanying expansion of drylands by 4.1–10.6%. Our findings, which indicate sustained adverse response of terrestrial water storage to vegetation growth in drylands, highlight the need for concerted planning for balanced ecological restoration, agricultural management, and water resource utilization that will affect 5.17 billion people, 64% of whom live in developing countries.

Estimation of biomass utilization potential in China and the impact on carbon peaking.

China has abundant agricultural and forestry waste resources that are crucial sources of energy for substituting fossil fuels and achieving the carbon peaking and carbon neutrality goals. These resources play an essential role in reducing carbon dioxide emissions and promoting sustainable development. This paper presents an estimation of the number of biomass resources that can be used for energy in 2020 by using parameters such as the grass-to-grain ratio coefficient and excretion coefficient. Moreover, the potential for conversion of biomass resources into biomass energy is evaluated by using parameters such as lower heating value and gas production coefficient. Finally, based on the whole life cycle theory, the potential of biomass energy utilization to reduce carbon dioxide emissions and its impact on carbon peaking is calculated. It was found that the total amount of fossil fuels that can be replaced by biomass energy is 256 million tons of standard coal. Utilizing biomass energy can reduce carbon dioxide emissions by approximately 520 million tons, with a peak impact of 4-6% on carbon peaking. The research results presented in this article can provide valuable data to support the promotion of green transformation in various regions. The findings can serve as a useful reference for formulating localized biomass utilization plans and designing effective emission reduction policies.

The development of Natuna Regency as a fishery industrial zone in the Indonesian border area

The implementation of infrastructure development in the marine and fisheries sector is faced with the challenge of realizing the integration between national policies through the potential, problems, or needs in the regions as outlined in society-based plans. The interest of the Indonesian government to develop Natuna Regency as a fishery industrial zone is related to potential resources that can still be optimized and has a strategic water as a border area, making it prone to illegal fishing cases by neighboring countries. Based on that, the purpose of this study is to examine the development of Natuna Regency as a fishery industrial zone. The analysis was carried out qualitatively with a case study approach and discussed descriptively. The parameters used to measure the readiness of Natuna Regency as a fishery industrial zone are: 1) government policy and governance; 2) fish resources utilization and spatial planning; 3) infrastructure; 4) community empowerment and business; 5) institutional; 6) technology. The result showed: 1) aspects of the development pillars that have been assessed as supporting Natuna Regency to become a fishery industrial zone; 2) the impact of fishery industrial development policies can increase economic activity in Natuna Regency; 3) the Natuna’s Regency appointment as a fishery industrial zone by the Indonesian government is the right policy.

Challenges of utilizing BIM in facilities management in Saudi Arabia

PurposeThis paper aims to present an assessment of the challenges of using building information modeling (BIM) in the facilities management (FM) practice in Saudi Arabia.Design/methodology/approachA review of the relevant literature was conducted, resulting in identifying 31 potential challenges to BIM utilization in FM, which were grouped into five main categories. These challenges were used to design a five-point Likert scale questionnaire survey to obtain the feedback of experts in the FM domain in Saudi Arabia. The professionals that participated in the survey consisted of facilities managers, maintenance managers and BIM experts. The results obtained were analyzed based on the Effect Index (EI) approach. The questionnaire also contained an open-ended section for more qualitative data.FindingsThe results of the EI revealed that the top most influential challenges include “integration of the building systems design with BIM”, “definition of handover requirements and integration requirements between FM and BIM” and “getting appropriate and accurate information”. The category with the highest EI was the “challenges pertaining to the execution of BIM in FM”.Practical implicationsThe paper outlines the critical challenges influencing the utilization of BIM in FM in Saudi Arabia and, as a result, could facilitate the development of implementation plans for BIM utilization. Thus, the study results have practical implications for stakeholders in the building industry.Originality/valueThe study contributes to the building industry through its discussion of the challenges of BIM utilization in FM and thus has the potential to increase the level of awareness of stakeholders in the industry.

Healthcare Utilization and Advance Care Planning among Older Adults Across Cognitive Levels.

This study examined the impact of advance care planning (ACP) on healthcare utilization among older adults with normal cognition and impaired cognition/dementia. Using datasets from the Health and Retirement Study, we conducted a cross-sectional study on 17,698 participants aged 51years and older. Our analyses included survey descriptive and logistic regression procedures. ACP measures included a living will and durable power of attorney for healthcare. Healthcare utilization was measured using the days spent in hospitals, hospice care, nursing homes, and home care. Of the participants, 77.8% had normal cognition, and 22% had impaired cognition/dementia. The proportion of impaired cognition/dementia was higher among racially minoritized participants, single/widowed participants, and those who lived alone and were less educated. The results showed that having an ACP was associated with longer stays in hospitals, nursing homes, and home healthcare in all participants.

Forecasting Regional Energy Consumption via Jellyfish Search-Optimized Convolutional-Based Deep Learning

The energy sector must achieve a delicate balance between energy supply and demand. Highly accurate energy consumption forecasts can help plant operators achieve this goal. In this study, various techniques from three artificial intelligence categories, namely, convolutional neural networks (CNNs), machine learning (ML), and time-series deep learning (DL), were applied to predict short-term regional energy consumption from a power company. An image conversion process was proposed to utilize the powerful image-processing capabilities of CNNs, in which numerical matrices of input values created by the sliding-window technique are encoded into two-dimensional grayscale images as input for CNN models. The proposed method outperformed conventional numerical input methods. Then, the best ML and time-series DL models were combined into ensemble models with ImageNet-winning CNN architectures based on the rationale of utilizing the strengths of each approach and compensating for their limitations. However, according to the numerical experiments for the regional energy consumption prediction, the ensemble models had lower performance than CNNs alone. Various leading models performing single-step or multistep forecasting and models that use seasonal or annual data were constructed. The performance of all the constructed models was evaluated, and the most efficient models were determined as proposed models. Finally, a nature-inspired optimization algorithm, Jellyfish Search (JS), was used to fine-tune the proposed models’ hyperparameters to minimize prediction error. The results revealed that the fine-tuning of hyperparameters via the JS algorithm significantly enhanced the precision of the CNN models, resulting in a mean absolute percentage error (MAPE) improvement range of 4.4% to 17.5% compared to the default models. The proposed models can help utilities plan daily power allocation and match supply and demand to maintain a stable power system.

Comparative study on landslide susceptibility mapping based on different ratios of training samples and testing samples by using RF and FR-RF models

Evaluation of landslide susceptibility is essential to planning of land and space utilization. For this purpose, the paper presents a case study from Fugu County, Shaanxi Province, China. Firstly, the geological environment and current state of landslides in Fugu County were investigated. Then, slope, aspect, terrain relief, curvature, lithology, land type, and normalized difference vegetation index (NDVI) were considered as the landslide susceptibility condition factors, and the correlation between these carried out by using Multicollinearity Analysis method. Next, landslide and non-landslide samples were divided into training samples and testing samples according to the sample ratios of 8/2, 7/3, 6/4, and 5/5, respectively. The landslide susceptibility mapping was carried out by using Random Forest (RF) model and Frequency Ratio coupled with Random Forest (FR-RF) model, respectively. Lastly, the landslide density (LD), landslide frequency ratio (LFR), the area under the curve (AUC) of the receiver operator, and other indicators were used to validate the rationality, accuracy, and performance of the landslide susceptibility maps produced from different models and ratios. The results indicated that all maps are reasonable, except the map when ratio is 5/5. For each map, regardless of ratios, the LD and LFR are the greatest in the zones classed as having a very high susceptibility, followed by those with a high, moderate, low, and very low classes.In the Random Forest (RF) model, when the training test set is not at the same time its in the area of extremely high sensitivity of LD and the size of the FR value respectively 7/3 (201.026) ​> ​8/2 (154.440) ​> ​6/4 (93.696) >5/5 (136.364) and 7/3 (4.806) ​> ​8/2 (3.692) ​> ​6/4 (3.260) ​> ​5/5 (2.240); in the Frequency Ratio coupled with Random Forest (FR-RF) model, Inall the training test sets the size of the proportion of LD and FR value respectively 7/3 (145.693) ​> ​6/4 (127.151) ​> ​5/5 (122.857) ​> ​8/2 (113.263) and 7/3 (3.334) ​> ​6/4 (3.073) ​> ​5/5 (2.811) ​> ​8/2 (2.592). What else, from the comparison of ROC curves, when ratio is 7/3, the accuracy of the two models is higher than that of other ratios. Similarly, the results of the ensemble model (A combination of two models with different learning abilities.) are not more reasonable than the results of the single model, which reflects that the combination of a weaker learner model (Frequency Ratio model here) with a stronger learner model (Random Forest model here) can diminish the performance of the stronger model.

Drinking Water Utility-Level Understanding of Climate Change Effects to System Reliability.

Climate change hazards, including increased temperatures, drought, sea level rise, extreme precipitation, wildfires, and changes in freeze-thaw cycles, are expected to degrade drinking water utility system infrastructure and decrease the reliability of water provision. To assess how drinking water utility manager perceptions of these risks affect utility planning, 60 semistructured interviews were conducted with utilities of various sizes, source water supplies, and United States geographical regions. This study analyzes these interviews (1) to evaluate which climate hazards are of primary concern to drinking water managers, (2) to develop a mental model framework for assessing utility-level understanding of climate change risks to system reliability, and (3) to examine the status of current water utility adaptation planning. The results show that concern and awareness of climate hazard risks vary geographically and are grounded in historical exposure; some participants do not believe climate change will influence their system's overall reliability. When considering climate change risks, utility managers tend to focus on effects to water supply and infrastructure, as opposed to changes in operations and maintenance, water quality, or business functions. Most surveyed utilities do not have comprehensive climate adaptation plans despite federal and professional recommendations. The range of beliefs and actions concerning climate adaptation planning indicates that utilities need directed guidance, and policymakers should consider including climate hazards and projections as part of required utility risk and resilience assessments.

Floodwater utilization potential assessment of China based on improved conceptual model and multi-reservoir basin assessment method

Floodwater resource utilization is an important way to alleviate the water resources shortage in China. The quantitative assessment of the floodwater utilization potential under the current engineering conditions is vital for implementation of floodwater resource utilization. However, the imperfect conceptual model of floodwater utilization potential, the limited availability of reservoir engineering data, and the lack of universal assessment method that directly considers the reservoirs regulation capacity pose a major challenge to assessment of floodwater utilization potential in China. This study improves the universality of the previous conceptual model of floodwater utilization potential by analyzing the differences and connections of floodwater resources potentials under different states of utilization. The floodwater utilization potential assessment method for river basin with multi-reservoir was also proposed based on our previous assessment method for single reservoir controlled basin. The assessment method was used to evaluate the floodwater utilization potential of the first- and second-level water resources regions in China based on the reanalyzed monthly runoff data (1902 ∼ 2014) and large and medium-sized reservoirs data (as of 2015). Results indicate that the annual average total floodwater utilization potential of China was calculated as 668.62 billion m3 under the current reservoir regulation capacity, accounting for 34.05% of the total floodwater water resources in China. The study demonstrated that the frequency curve of floodwater utilization potential can provide a better understanding of the states of floodwater utilization, and the assessment method. Strategies for long-term floodwater utilization and flood control planning in different regions of China were also provided to government in our study.

Deep Learning Method for Evaluating Photovoltaic Potential of Rural Land Use Types

Rooftop photovoltaic (PV) power generation uses building roofs to generate electricity by laying PV panels. Rural rooftops are less shaded and have a regular shape, which is favorable for laying PV panels. However, because of the relative lack of information on buildings in rural areas, there are fewer methods to assess the utilization potential of PV on rural buildings, and most studies focus on urban buildings. In addition, in rural areas, concentrated ground-mounted PV plants can be built on wastelands, hillsides, and farmlands. To facilitate the overall planning and synergistic layout of rural PV utilization, we propose a new workflow to identify different types of surfaces (including building roofs, wastelands, water surfaces, etc.) by applying a deep learning approach to count the PV potential of different surfaces in rural areas. This method can be used to estimate the spatial distribution of rural PV development potential from publicly available satellite images. In this paper, 10 km2 of land in Wuhan is used as an example. The results show that the total PV potential in the study area could reach 198.02 GWh/year, including 4.69 GWh/year for BIPV, 159.91 GWh/year for FSPV, and 33.43 GWh/year for LSPV. Considering the development cost of different land types, several timespans (such as short-, medium-, and long-term) of PV development plans for rural areas can be considered. The method and results provide tools and data for the assessment of PV potential in rural areas and can be used as a reference for the development of village master plans and PV development plans.

Traditional Uses, Active Ingredients, and Biological Activities of Paris polyphylla Smith: A Comprehensive Review of an Important Himalayan Medicinal Plant

Paris polyphylla Smith (family: Melanthiaceae), a high-value medicinal herb endemic to the Himalayan region, has drawn much attention recently due to its immense use in the traditional healthcare system since ancient times. In the present review, an extensive database on P. polyphylla was systematically searched from databases such as Medline/PubMed, Scopus, the Web of Science, and the online service E-library.ru and SCImago (https://www.scimagojr.com/). Information on species, ecology, distribution, trade, ethnopharmacology, pharmacology, biotechnology, and molecular biology was gathered from 1979 to 2023 using 116 research publications. Major steroidal saponins such as Paris saponin I, V, VI, VII, and H have been found substantially effective in anticancer activity, abnormal uterine bleeding, dysfunctional uterine bleeding, and menorrhagia. Traditional breeding and propagation techniques cannot keep up with the world’s growing demand for herbal drugs. Therefore, it is critically necessary to take conservation measures and develop novel techniques for growing and cultivating this economically significant and highly valuable therapeutic herb. The advanced biotechnological approaches like micropropagation and genetic analysis introduced long back are either rare or lacking in the case of P. polyphylla. It contains a wealth of information that will serve as a baseline data source for various stakeholders, researchers working on various research aspects, and policymakers to define appropriate utilization and conservation plans for a high-value commercial medicinal plant called P. polyphylla. The review provides an updated overview and critical assessment of secondary data regarding the past and recent applications and interventions of P. polyphylla.

Policy Intervention and Legislative Framework Relating to the Sustainability of Built Structures in India

If not coupled with effective urbanization and utmost planning for crucial and optimum resource utilization, sustainable development becomes a fiction. Rapid urbanization and industrialization have been a key source of concern for the environment's consistent deterioration. With the presence of evident impediments, there is already a conscious limit on industrial growth in place. However, urbanization cannot be fully stifled in order to foster green movement, and vice versa. Among the many efforts made by the Indian government to improve energy efficiency and the sustainability of the built environment, the desire to incorporate important market players, along with legislative incentives, has begun to make a difference. The primary actors have been divided over the choice of ratings since the introduction of GRIHA (Green Rating for Integrated Habitat Assessment), IGBC (Indian Green Building Council), and BEE (Bureau of Energy Efficiency), offering a bewildered outlook with the many regulatory indexes and perimeters. The policies/ratings/mechanisms in place in many states to maintain the energy efficiency of the built environment are incompatible, resulting in a significant margin of error. For efficient implementation of these policies, the involvement of adequately empowered local entities becomes critical. This cannot be done without first examining the influence of current regulations and frameworks on the energy usage and functioning of the built environment, which includes both residential and commercial structures.

Agricultural Water Footprint Studies for Sustainable Agricultural Water Management -A Review

Water footprint is defined as the amount of water consumed in production of any agricultural or industrial produce. It accounts the water consumed directly and indirectly for producing any industrial and agricultural product. Water footprint analysis helps in planning of the optimum utilization of water in any sector which subsequently leads to sustainable management of water resources. This review paper provides a review on the Water Footprint estimation methodology its merit and shortcomings, practical challenges with available data and resources for Indian context and worldwide. With increasing population and industrialization, availability of water and its judicious distribution is becoming challenging for the policy makers and strategist. Water foot print mapping of major crops will be helpful for development of new varieties which will be having higher yield with less water consumption. Traditional water consumption statistics, policies and awareness drives focuses on reducing water wastage and improving water use efficiency in domestic and industrial water use. Water footprint studies for various regions of India find that climate change and agricultural practices has significantly reduced the water consumption.

INVESTMENT PROSPECTS IN THE RECONSTRUCTION OF UKRAINE

INVESTMENT PROSPECTS IN THE RECONSTRUCTION OF UKRAINE

Juridical Review of Spatial Planning and Control of Space Utilization in the Situ Kayu Antap Area in the South Tangerang City Area in the Perspective of National Land Law

Juridical Review of Spatial Planning and Control of Space Utilization in the Situ Kayu Antap Area in the South Tangerang City Area in the Perspective of National Land Law