System Performance Indicators Research Articles

Geographic Information System Design for Irrigation System Performance Index Main Network

Irrigation plays an important factor in supporting agricultural land productivity to improve agricultural production. This is achieved by maintaining a sustainable irrigation system through an effective and efficient irrigation system. One method to asses is by using the Irrigation System Performance Index (IKSI). This study designs an information system for IKSI in the main network system. The assessment of IKSI follows PERMEN PU NO.32/2007, with parameters such as physical infrastructure assessment, crop productivity, supporting facilities, personnel organization, documentation, and P3A. The purpose of this system is to determine the operation and maintenance (O&M) strategies and non-physical management strategies. The Main Network SIG IKSI design includes functionalities such as (i) a data folder system, (ii) an imaging system, (iii) GIS, and (iv) an evaluator of physical and non physical irrigation systems. The results of the program in the Antirogo irrigation area show an IKSI the main network value for physical infrastructure of 85,0% and non physical strategies (crop productivity, supporting facilities, personnel organization, documentation, and P3A) of 70,0% until 80,0%. The results shows that the physical infrastructure needs to be carried out regularly and non-physical strategies need to be maintained and improved. Keywords: Association of Farmer Water Users, Geographic Information System, Irrigation System Performance Index, Irrigation, PAKSI.

Analisis Kinerja Sistem Presensi Elektronik Dalam Pelaksanaan Kebijakan TPP Dengan Metode IT Balanced Scorecard

The Additional Employee Income (TPP) initiative within the Wakatobi Government has been active since 2020, following the enactment of Wakatobi Regent Regulation Number 5 of 2022. Nonetheless, challenges confront the Electronic Presence System in Wakatobi. Issues encompass delays and inaccuracies in attendance data, system constraints in addressing additional factors impacting employee productivity, and concerns regarding potential manipulation or improprieties. Various studies delve into these matters. Nia Afdila et al.'s work explores the impact of e-attendance and supplementary employee earnings on performance at the North Sumatra Province TPH Service. Alfrian Carmen et al. conduct an IT Balanced Scorecard analysis to gauge IT performance at the Ambon City Dukcapil Service, while Cristian SM investigates electronic attendance's role in establishing single salaries for ASN at the Public Relations, Protocol, and Cooperation Bureau of the Riau Province Regional Secretariat. Assessing the Electronic Presence System's performance in TPP policy implementation through the IT Balanced Scorecard method is crucial for comprehending potential and constraints within the TPP framework. This qualitative research adopts the IT Balanced Scorecard Method, focusing on four primary perspectives: Corporate Contribution, Customer Orientation, Operational Excellence, and Future Orientation. Data acquisition involves interviews, observations, and documentation of relevant personnel. Performance assessments reveal one adequate perspective, two insufficient perspectives, and one deficient perspective, underscoring insufficient attention to Electronic Attendance System performance indicators by BKPSDM Wakatobi.

Trends and inequalities in health system satisfaction: results from the latest nationally representative surveys in Qatar

BackgroundHealth system satisfaction is an important but understudied indicator of health system performance. It has far-reaching implications for sustainability but has been widely understudied particularly for non-European settings. Qatar represents a growing international experience of rapid development requiring steadfast system funding and reorganisation. After decades of unprecedented immigration and nearly free health care, Qatar sought to expand the system by 2016, reorganise it by 2022, and accelerate private funding and health system outcomes by 2030.AimThe aim of this study is to conduct a comprehensive assessment of health system satisfaction in Qatar, in anticipation of the 2024–2030 health reforms, with a particular emphasis on detailed policy attribution and the formulation of recommendations. The overarching aim of this study is to contribute to the limited body of international literature on health system satisfaction, particularly in non-European contexts, with a focus on specific populations such as migrants, labourers, and labour camp residents.MethodsWe analysed the levels of, and individual inequalities in, health system satisfaction in Qatar between 2012 and 2014. Descriptive statistics were employed to assess satisfaction levels, while inequalities were examined using logit analysis. The satisfaction variables encompass the key aspects of health system provision and management, whereas the individual variables are focused on their attributability to Qatar’s specific health policy context, including regionally distinct socio-economic groups.FindingsHealth system satisfaction levels in Qatar were relatively high in both 2012 and 2014, particularly regarding service provision, though they did not reach exceptionally high levels. Both satisfaction dimensions—provision and management—improved in 2014, with management showing more rapid progress. However, males, Qatari citizens, individuals with chronic disease, labourers, and residents of the largest labour camps were less likely to express satisfaction with the system.ConclusionQatar’s satisfaction trends and inequalities between 2012 and 2014 emphasise the significance of both dedicated efforts and effective organisational structures in maintaining high levels of health system satisfaction during periods of rapid development. To ensure continued satisfaction, performance, and sustainability throughout the 2024–2030 reforms, it is essential to address unresolved organisational constraints before eroding dedicated efforts through increased private health funding.

Mapping of Health System Performance Indicators to the WHO HSPA Framework.

Healthcare systems worldwide face escalating costs and demographic changes, necessitating effective evaluation tools to understand their underlying challenges. Switzerland's high-quality yet costly healthcare system underscores the need for robust assessment methods. Existing international rankings often lack transparency and comparability, highlighting the value of structured frameworks like the Health System Performance Assessment (HSPA) by the World Health Organization (WHO). This framework evaluates healthcare systems across multiple dimensions including governance, resource generation, financing, and service delivery. This paper aims to integrate Swiss healthcare indicators from the Swiss Health Observatory (Obsan) into the HSPA framework, addressing the central research question: How can these indicators be mapped to the HSPA framework, and what insights does this integration provide? Our methodology includes selecting and categorizing Obsan indicators, manually mapping them to HSPA sub-functions, and validating these mappings using word embeddings and cosine similarity. An R Shiny application was developed for interactive visualization. Results demonstrate accurate indicator assignment, enabling intuitive visualization and enhancing data structuring.

Regional-scale evaluation of tertiary irrigation system in Muda Irrigation Scheme from space

A tertiary irrigation system is essential for efficient water management in large-scale irrigation scheme and requires regular evaluation to understand their effectiveness. The current water balance method for tertiary irrigation system evaluation requires extensive data, making continuous monitoring over vast areas unfeasible. A better approach using geospatial data from the Google Earth Engine (GEE) is introduces to evaluate the efficiency of tertiary irrigation systems on a regional scale, aiding water management strategies. This study aims to (1) define the rice cultivation boundary for accurate data collection and (2) quantitatively evaluate irrigation system performance using specific indicators. Remote sensing evapotranspiration (RS-ET) and yield derived from Normalized Difference Vegetation Index (NDVI) were collected within rice cultivation boundary across 60 irrigation blocks, including 14 blocks equipped with tertiary irrigation system in Region II of the Muda Irrigation Scheme. Three irrigation system performance indicators (equity, adequacy, and water productivity) were used as a key metric in over four rice-growing seasons to evaluate tertiary irrigation system. Results reveal that tertiary irrigation system performance varies with the current three-phase water management strategy. Equity performance was highest during the off-season, particularly in phase 1 (2–8 %). Adequacy was moderate across all phases and seasons (median: 0.6–0.67), while water productivity showed consistent strength in phases 1 and 3, with fluctuations in phase 2, across seasons. This study underscores the cost-effectiveness and efficiency of using geospatial data from space for continuous regional-scale monitoring, highlighting areas for improvement in the current water management strategy.

System of performance indicators of the ESG–concept: state and prospects for assessment

In the world community, the concept of sustainable development has firmly established itself as a priority trend of globalization through the transformation of key development vectors into the format of the ESG–concept, within which the performance of enterprises is expressed by indicators characterizing care for the environment, personnel, transparency and efficiency of social activities. The main emphasis is on the formation of anti-corruption activities, ensuring the transparency of enterprise reporting, information openness, the use of modern management tools within the framework of the Industry 5.0 concept, eliminating gender, social and other conflicts, comprehensively ensuring a good image of the organization. In these conditions, the creation of international ratings of compliance of enterprise policies with the ESG–agenda is being updated. At the same time, there is a lack of a unified methodology for assessing the performance indicators of the ESG–concept, in the form of a unified reporting form for enterprises. The purpose of the study is to develop ESG–monitoring based on systematization of indicators in priority areas of activity and calculation of the integral ESG–indicator. The scientific novelty lies in the development of an ESG–monitoring model, which is a decomposition diagram of the organization of ESG–monitoring of enterprises in IDF0 notation as part of the implementation of the state strategy for transplantation of sustainable development goals, including the formation of a list of indicators, the development of a unified methodology for their calculation, the development of a unified form of statistical reporting, and monitoring with current frequency. The proposed toolkit is a promising mechanism for government regulation, by ranking and comparing enterprises according to the level of compliance with the ESG–concept, to create an accurate investment impulse in the field of transplantation of sustainable development goals and ensuring the homeostasis of economic systems in conditions of uncertainty and instability of the external environment.

Digitalization of logistics processes at a manufacturing enterprise: An effect analysis

Subject. This article discusses the implementation of digitalization tools at a manufacturing enterprise. Objectives. The article aims to determine the effects of using QR codes within the framework of the strategic goals of the enterprise, taking into account their multifaceted nature. Methods. For the study, we used the general scientific methods and methods of strategic analysis. Results. Based on the consideration of the possible effects of the implementation of the project of marking products with QR codes at a particular manufacturing enterprise, the article substantiates the importance of digital solutions as tools for achieving strategic goals. It also presents the author-developed system of key performance indicators for the implementation of QR codes. Relevance. Further research is related to the development of tools for managing change and resistance in the implementation of digital solutions. The results obtained can be used as a benchmark in the development and implementation of digitalization projects at enterprises in various industries.

Health care utilization and costs among coordinated care patients in Southeastern Ontario: A difference-in-differences study of a double propensity score-matched cohort.

Coordinated care plans (CCPs) for high-cost health care system users aim to improve system-level performance. We evaluated health care resource use and costs among CCP patients (enrollees) versus a control group that did not receive coordinated care (comparators) in Southeastern Ontario. A difference-in-differences analysis of a quasi-experimental, double propensity score-matched and adjusted cohort was conducted. Linked population-based administrative data were used to measure health care utilization and costs and to identify comparators for two enrollee groups who began CCPs between April 1, 2013, and March 31, 2019. Enrollees were recruited from hospitals in Quinte or community care centres in Rural Hastings/Thousand Islands, and were 1:1 propensity score matched to comparators. Difference-in-differences estimates were calculated using generalized estimating equations for hospitalization rates, homecare visits, primary care visits, other health care resources and total costs. A total of 558 enrollees in Quinte and 538 in Rural Hastings/Thousand Islands were identified and matched to comparators. Difference-in-differences estimates were significant in both enrollee groups for number of homecare visits ([IRR 1.72; 95% CI (1.44, 2.06)] and [IRR 1.73; 95% CI (1.45, 2.06)], respectively). Number of primary care visits were 1.76 times greater for Rural Hastings/Thousand Islands enrollees versus comparators [IRR 1.76; 95% CI (1.32, 2.35)]; total costs increased by 23% ([IRR 1.23; 95% CI (1.09,1.39)]. Homecare use significantly increased for enrollees versus comparators, indicating specific priority areas of Ontario CCPs were met. However, no reductions were shown for other health system performance indicators. We also showed increased 7-day primary care follow-up visits for community care centre-recruited patients, but not for hospital-recruited patients. Decision-makers may wish to target patients who are less advanced in their chronic disease trajectory.

A multi-case study exploring the effect of interventions on food safety culture maturity

In each food business, a food safety culture (FSC) with a certain maturity level prevails. Previous research has demonstrated that the maturity level of the prevailing FSC can be assessed, but empirical proof of FSC maturity improvement remains limited especially in food processing companies. This study aimed to zoom in on the food safety culture improvement trajectory of four food processing case studies, focusing on human-organizational dimensions of food safety culture. First, a pre-assessment of the maturity of the prevailing food safety culture was executed in each case company (assessment time 1) by application of a validated mixed-methods methodology which includes three different tools (the food safety climate questionnaire, management interview, and on-site evidence collection visits). Based on this pre-assessment, underdeveloped dimensions or gaps in the prevailing food safety culture were identified to find improvement needs. In each of the 4 included distinct case companies, an intervention was implemented. In the first case company, case 1, a food safety key performance indicator (KPI) system was implemented as the intervention, with shared monitoring and shared responsibilities for KPI improvement. Coincidentally, case company 2 and case company 4 selected the same intervention. Case 2, as well as case 4, decided to implement structured group discussions with operators to collect input for collaborative action point selection, aiming for their active involvement in food safety. In case 3, a food safety culture check system was implemented for systematic reward and recognition. After intervention implementation, the post-assessment was conducted (assessment time 2), applying the exact same methodology as the pre-assessment. To investigate the extent of improvement, comparison of the pre- and post-assessment in each of the four cases was first done descriptively by comparing the means. Next, data collected via the food safety climate questionnaire was compared statistically via Mann-Whitney U tests. Analyses showed a substantial objective and subjective (employees’ perceptions) improvement of the targeted food safety culture gaps in companies 1 and 2, demonstrating that food safety culture improvement was achievable through a science-based and cocreated intervention process and implementation plan compliance. In cases 3 and 4, marginal improvements and unchanged scores were revealed. Comparison of cases’ trajectory characteristics and resulting success rates demonstrated that senior management involvement was essential for interventional success, as well as implementing culture interventions on an organizational or group level, instead of only including selected employees.

A Survey System for Artificial Intelligence-Based Painting Using Generative Adversarial Network Techniques

The purpose of this paper is to construct an evaluation system for AI painting software based on generative adversarial network (GAN) technology, which optimizes the performance of the related software in terms of functionality, ease of use, system performance, and safety. The results of the questionnaires are statistically analyzed. In addition, an exploratory factor analysis was conducted to extract the data of the study, which were ultimately used to calculate the weight and importance of each index using the fuzzy hierarchical analysis method. This study constructed an evaluation system for AI painting software based on GAN technology, including 16 indicators of functionality, 16 indicators of ease of use, 7 indicators of system performance, and 8 indicators of safety, respectively, whose alpha coefficients were 0.882, 0.962, 0.932, 0.932, and 0.932, respectively. In addition, the accumulated explanatory variances of their coefficients were 84.405%, 84.897%, 84.013%, 72.606%, 73.013%, and 72.606%, respectively. It is clear that the items included in each of the indicators are homogeneous, with a high degree of internal consistency. This paper suggests that the development of AI painting software focusing on functionality, ease of use, system performance, and safety can enhance the market competitiveness of the software.

Survey of Reliability Challenges and Assessment in Power Grids with High Penetration of Inverter-Based Resources

Decarbonization is driving power systems toward more decentralized, self-governing models. While these technologies improve efficiency, planning, operations, and reduce the carbon footprint, they also introduce new challenges. In modern grids, particularly with the integration of power electronic devices and high penetration of Renewable Energy Sources (RES) and Inverter-Based Resources (IBRs), traditional reliability concepts may no longer ensure adequate performance due to systemic restructuring. This shift necessitates new or significantly modified reliability indices to capture the characteristics of the evolving power system. Ensuring converter reliability is essential for effective planning, which requires precise, component-to-system-level modeling, as different converters impact system performance indicators. However, the existing literature in this field faces a significant limitation, as most studies focus on a singular perspective. Some examine reliability at the device-level, others at the component-level, while broader reviews in power systems often emphasize system-level analysis. In this paper, we aim to bridge these gaps by comprehensively reviewing the interconnections between these levels and analyzing the mutual influence of power converter and system reliability. A key point to highlight is that, with the rapid evolution of modern power grids, decision-makers must adopt a multi-level approach that incorporates insights from all levels to enable more accurate and realistic planning and operational strategies. Our ultimate goal is to provide an in-depth investigation of studies addressing the unique challenges posed by modern power grids. Finally, we will highlight the gaps in the literature and suggest directions for future research.

Analisis Indeks Kinerja Jaringan Saluran Irigasi Studi Kasus Irigasi Sungai Siulak Deras Kabupaten Kerinci

The Siulak Deras Irrigation canal network is the main source of water distribution in several areas. The Siulak Deras Irrigation Area in Kerinci Regency was built in 1993 with water flow regulation and complete Siulak Deras Irrigation network facilities including the Technical irrigation group. As time goes by, the service function of the irrigation network experiences a decline in performance, so that operation and maintenance of the irrigation network is an activity that is really needed to make the irrigation network remain optimal and maintain its performance. In this regard, an assessment of the Performance Index of the irrigation system in the Siulak Deras Irrigation Area needs to be carried out to determine the value of aspects or components that are not yet optimal in this irrigation area so that special treatment can be immediately carried out or improved. The assessment is carried out by starting an inventory of the condition and function of the physical infrastructure of the irrigation network, planting productivity results, supporting facilities, organization, documentation and institutional P3A to determine the performance value and recommendations for handling it. The results of the irrigation network system performance index in the Siulak Deras irrigation area for the Left Irrigation Channel section are 69.59%, which means that the irrigation system performance is close to good performance, namely 70%, but still needs to be improved and needs attention. With a physical infrastructure value of 29.32%, planting productivity 14.21%, supporting facilities 6.15%, personnel organization 10.94%, documentation 2.46%, and P3A institutions 6.50%. Based on the performance index value obtained, and the total performance score in the form of a percentage, it is necessary to specifically maintain and repair physical facilities and infrastructure at several points that are damaged, facilitate supporting facilities for OP officers so that officers can act quickly and precisely in carrying out activities, and paying more attention to P3A so that it can always contribute to maintaining and utilizing the Siulak Deras irrigation network properly and optimally in the future.

A dynamic framework for contractors to measure the performance of highway maintenance based on grey theory

Highway maintenance performance measurement is the key to implementing performance-based contracting (PBC). However, contractors have struggled with accurately understanding client intent and translating performance goals into measurable indicators. To make PBC successfully applied, this study proposes a dynamic performance measurement framework of highway routine maintenance based on grey theory. A performance indicator system is established based on the organizational structure of highway assets and the bill of quantities in the real world. In addition, a statistical analysis using the data about maintenance cost and highway condition score has been conducted to ascertain the weights and thresholds assigned to various indicators. As a result, the performance indicators, their corresponding weights, and thresholds can be flexibly adjusted to accommodate diverse periods and areas. Then, the grey theory has been employed to evaluate the comprehensive performance level of service within a region. This framework is experimented with using the data of three maintenance areas in Shaanxi Province, China: Qiaogouwan, Huaziping, and Ansai. At the end of the process, comparison and sensitivity analysis are conducted. The results demonstrate the model’s reasonability and robustness, providing valuable tools for contractors to assess the performance of highway maintenance in meeting client specifications.

Comparative Analysis of Environmental Sustainability and Performance Indices of Different Gas Turbine Inlet Cooling Systems

Comparative Analysis of Environmental Sustainability and Performance Indices of Different Gas Turbine Inlet Cooling Systems

Prediction of key performance indicators of multi-effect vacuum membrane distillation systems integrated with PVT and Organic Rankin Cycle

The study presented a numerical simulation conducted using MATLAB® to analyze the performance of a poly-generation system. This system comprises solar collectors, a Photovoltaic-Thermal (PVT) system, an Organic Rankine Cycle (ORC), and a multi-effects vacuum membrane distillation (V-MEMD) system. The study investigates the impact of changes in operating conditions of the water stream on the performance of the V-MEMD system. The optimal performance values observed include a water flux of up to 13 kg/ m2·h, a GOR of 5.5, a SEEC of 49 kWh/ m3, and a STEC of 145 kWh/ m3, with each parameter reaching its optimum at different operational settings. The paper explores the impact of different working fluids in the ORC system on water and power generation. It also discusses recent research on combined PVT and ORC systems in Riyadh, Saudi Arabia, considering the region's specific meteorological conditions. The findings reveal that the highest electricity generation occurs in June, with the ORC system producing 18,540 kWh when R123 is used and the PVT system generating 13,536 kWh. The cumulative electricity output for the year reaches 266,564 kWh. Moreover, the V-MEMD system produces 1333 m3 of water over the year, with the highest water yield of 178 m3 observed in June.

Development of a pig wean-quality score using machine-learning algorithms to characterize and classify groups with high mortality risk under field conditions

Mortality during the post-weaning phase is a critical indicator of swine production system performance, influenced by a complex interaction of multiple factors of the epidemiological triad. This study leveraged retrospective data from 1723 groups of pigs marketed within a US swine production system to develop a Wean-Quality Score (WQS) using machine learning techniques. The study evaluated three machine learning models, Random Forest, Support Vector Machine, and Gradient Boosting Machine, to classify groups having high or low 60-day mortality, where high mortality groups represented 25 % of the groups among the study population with the highest mortality values (n=431; 60-day mortality=9.98 %), and the remaining 75 % of the groups were of low mortality (n=1292; 60-day mortality=2.75 %). The best-performing model, Random Forest (RF), outperformed the other ML models in terms of accuracy (0.90), sensitivity (0.84), and specificity (0.92) metrics, and was then selected for further analysis, which consisted of creating the WQS and ranking the most important factors for classifying groups as high or low mortality. The most important factors ranked through the RF model to classify groups with high mortality were pre-weaning mortality, weaning age, average parity of litters in sow farms, and PRRS status. Additionally, stocking conditions such as stocking density and time to fill the barn were important predictors of high mortality. The WQS was developed and correlated (r = 0.74) with the actual 60-day mortality of the groups, offering a valuable tool for assessing post-weaning survivability in swine production systems before weaning. This study highlights the potential of machine learning and comprehensive data utilization to improve the assessment and management of weaned pig quality in commercial swine production, which producers can utilize to identify and intervene in groups, according to the WQS.

Application of Online Flow Cytometry for Early Biofouling Detection in Reverse Osmosis Membrane Systems.

Biofouling poses a significant challenge to reverse osmosis (RO) membrane systems, necessitating timely detection for effective control. This study evaluated the efficacy of flow cytometry (FCM) for early biofilm detection in comparison to conventional system performance indicators. Feed channel pressure drop and total cell concentration in the Membrane Fouling Simulator (MFS) flowcell cross-flow outlet water were monitored over time as early biofouling indicators. The results demonstrated the potential of increased bacterial cell concentration in cross-flow outlet water as a reliable indicator of biofouling development on the membrane. Water outlet monitoring enabled faster biofouling detection compared to feed channel pressure drop. Membrane autopsy confirmed biofilm presence prior to the pressure drop increase, highlighting the advantage of early detection in implementing corrective measures. Timely intervention reduces operational costs and energy consumption in membrane-based processes.

Measurement of safety state of cross-jointed segmental lining based on system performance index

The correlation between convergence deformation and the safety state of a cross-jointed segmental lining is investigated and clarified. The limitations of convergence deformation as a measuring scale is explored also. Firstly, an analytical algorithm (known as the relative stiffness method, RSM) is developed and verified for tracing the mechanical response of a cross-jointed segmental lining in failure history. Then, an explicit mapping relationship between convergence deformation and the causal factors is established using the RSM. Finally, the root causes of the limitations in using convergence deformation as a scale to evaluate tunnel safety state are discussed, and an alternative quantity, the system performance index (SPI), is proposed. It shows that: (1) The convergence deformation consists of three components induced by segment bending, elastic joint rotation, and joint stiffness attenuating, respectively. The deformation induced by attenuating joint stiffness is dependent on the failure index of segment joints and provides crucial information about the load-bearing state of the segment joints; (2) The components of elastic joint rotation and joint stiffness attenuating are significantly affected by the contact stiffness of the segment joint interface, including the physical and mechanical properties of the packing material. The magnitudes of convergence deformation and its components are not suitable for use as a quantitative scale to evaluate the safety state of the lining due to their inherent drawbacks; (3) The proposed dimensionless variable SPI can eliminate the influence of packing material on the safety state of the segment lining and reflect the comprehensive influence of the failure indexes of the segment joints.

Experimental development of a method of short and medium-term photovoltaic generation forecasting using multivariate statistics and mathematical modeling

Uncertainties in photovoltaic solar energy production can make it challenging to dispatch energy into the electricity grid. Although photovoltaic generation storage solves this problem, a forecasting of the photovoltaic solar energy produced is necessary to control the energy injected into the grid. This article aims to develop the probabilistic methodology Reduced-Rank Regression (RRR) for forecasting photovoltaic generation in the short and medium terms. The RRR methodology forecasting uses the generation data of a grid-connected photovoltaic system. The proposed RRR model is simple, easy to access and apply, and does not use irradiance data. The model developed uses the multivariate statistical analysis technique. A advantage is that with a correlation with the performance indices of photovoltaic solar energy systems, the proposed method can be applied in any geographical location on the planet and with different photovoltaic solar energy systems. The application of the RRR methodology requires two searches/inputs. The first input is weather forecast data obtained from a weather forecasting platform, and the second is actual historical data on photovoltaic generation at the site where the method was developed. The proposed method was compared with the persistence method. Using a horizon of 1–10 h, the average monthly root mean square error for the RRR ranged from 7.3 % to 50.1 %. For the persistence method, the average monthly root mean square error ranged from 15.1 % to 65.0 %. Therefore, with the horizon of 24 h, the average monthly root mean square error for the RRR ranged from 4.5 % to 43.2 %. For the persistence method, the average monthly root mean square error ranged from 11.5 % to 75.0 %. We show experimentally that our method is competitive with the state-of-the-art in terms of obtaining photovoltaic generation forecasting without using solar radiation data.

Optimizing domestic energy management with a wild Mice colony-inspired algorithm: Enhancing efficiency and coordination in smart grids through dynamic distributed energy storage

Energy management (EM) is a critical strategy that spans the production and consumption of electricity, enhancing the stability of the electricity network. Smart grid technology significantly improves the electrical system's energy efficiency (EE), facilitating a transformation from a conventional power grid (PG) to a smart PG. This paper presents a key strategy for modeling the EE of the smart grid tailored to domestic demand, establishing smart coordination between domestic demand, energy production, and storage to reduce energy waste and costs. Our model integrates various energy sources, including renewable energy (RE), photovoltaic (PV) systems, wind power, and an energy storage system (ESS), interconnected with the PG. The model's structure ensures the coordinated flow of electricity in a residential house through an optimal control method (OCM). To develop a robust closed-loop control model, we employ Demand Response (DR) schemes within the Real-Time Electricity Pricing (RTEP) framework. We construct a dynamic model of the ESS to compute the System Performance Index (SPI), corresponding to energy costs. To enhance our model, we introduce a Dynamic Distributed Energy Storage Strategy (DDESS). Additionally, we introduce a novel optimization algorithm inspired by the behavioral patterns of wild mice, called the Wild Mice Colony (WMC). By analyzing the targeted and advantageous behaviors of wild mice in colonies, we propose that these behaviors can serve as a model for addressing complex, uncertain problems. This strategy is highly advantageous, capable of reducing total energy consumption (EC) from the main grid by over 100 % of the load demand, optimizing the energy system, and ensuring synchronization. The performance of DDESS optimizes energy flow (EF) during the repayment plan, leading to minimized EC costs from the PG.