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Dynamic economic and emission dispatch (DEED) aims to optimally set the active power generation with constraints in a power system, which should target minimum operation cost and at the same time minimize the pollution in terms of emission when the load dynamically changes hour to hour. The purpose of this study is to achieve optimal economic and emission dispatch of an electrical system with a renewable generation mix, consisting of 3-unit thermal, 2-unit wind and 2-unit solar generators for dynamic load variation in a day. An improved version of a simple, easy to understand and popular optimization algorithm particle swarm optimization (PSO) referred to as a constriction factor-based particle swarm optimization (CFBPSO) algorithm is deployed to get optimal solution as compared to PSO, modified PSO and red deer algorithm (RDA).

Different model with and without wind and solar power generating systems; with valve point effect is analyzed. The thermal generating system (TGs) are the major green house gaseous emission producers on earth. To take up this ecological issue in addition to economic operation cost, the wind and solar energy sources are integrated with the thermal system in a phased manner for electrical power generation and optimized for dynamic load variation. This DEED being a multi-objective optimization (MO) has contradictory objectives of fuel cost and emission. To get the finest combination of the two objectives and to get a non-dominated solution the fuzzy decision-making (FDM) method is used herein, the MO problem is solved by a single objective function, including min-max price penalty factor on emission in the total cost to treat as cost. Further, the weight factor accumulation (WFA) technique normalizes the pair of objectives into a single objective by giving each objective a weightage. The weightage is decided by the FDM approach in a systematic manner from a set of non-dominated solutions. Here, the CFBPSO algorithm is applied to lessen the total generation cost and emission of the thermal power meeting the load dynamically.

The efficacy of the contribution of stochastic wind and solar power generation with the TGs in the dropping of net fuel cost and emission in a day for dynamic load vis-à-vis the case with TGs is established.

Cost and emission are conflicting objectives and can be handled carefully by weight factors and penalty factors to find out the best solution.

The proposed methodology and its strategy are very useful for thermal power plants incorporating diverse sources of generations. As the execution time is very less, practical implementation can be possible.

As the cheaper generation schedule is obtained with respect to time, cost and emission are minimized, a huge revenue can be saved over the passage of time, and therefore it has a societal impact.

In this work, the WFA with the FDM method is used to facilitate CFBPSO to decipher this DEED multi-objective problem. The results reveal the competence of the projected proposal to satisfy the dynamic load demand and to diminish the combined cost in contrast to the PSO algorithm, modified PSO algorithm and a newly developed meta-heuristic algorithm RDA in a similar system.

The purpose of this study is to examine the socio-economic inequalities that exist in the use of unhygienic menstrual practices in India and its states, as well as to identify the contribution of various socio-economic factors that leads to these inequalities.

Data from the National Family Health Survey-5 (2019–21) for 240,285 menstruating women aged 15–24 years is used to examine the above objectives. The concentration index for unhygienic menstrual practices is calculated to measure the socio-economic inequalities, which are then decomposed into their determining factors.

The state of Punjab experiencing the highest level of economic inequality, followed by Telangana and Haryana. The results from decomposition analysis suggest that rural residence (13%), illiteracy (7%), poor economic status (53%), not reading newspaper (12%) and not watching TV (14%) contribute 99% to the total socio-economic inequality in using unhygienic menstrual practices in India. The contribution of economic status to total inequalities is more in all the states except for Kerala and Mizoram, where caste and residence play an important role.

This paper signifies the role of economic inequality in the use of unhygienic menstrual practices in India as well as the contribution of various socio-economic factors contributing towards these inequalities. The results from decomposition analysis suggest the need for unique health intervention strategies for different states following the evidence of major contributions to total inequalities in the use of unhygienic menstrual practices.

The wind turbine (WT) is a complex system subjected to wind disturbances. Because the aerodynamics is nonlinear, the control is thus challenging. For the variation of wind speed when rated power is delivered at rated wind speed, the power is limited to the rate by the pitching of the blades of the turbine. This paper aims to address pitch control with the WT benchmark model. The possible use of appropriate adaptive controller design that modifies the control action automatically identifying any change in system parameters is explored.

To deal with pitch control problem when wind speed exceeds the rated wind speed of the WT, six digital self-tuning controller (STC) with different structures such as proportional integral (PI), proportional derivative (PD), Dahlin’s, pole placement, deadbeat and Takahashi has been taken herein. The system model is identified as a second-order autoregressive exogenous (ARX) model by three techniques for comparison: recursive least square method (RLS), RLS with exponential forgetting and RLS with adaptive directional forgetting identification methods. A comparative study of three identification methods, six adaptive controllers with the conventional PI controller and sliding mode controller (SMC), are shown.

As per the results, the best improvement in control of the output power by pitching in full load region of benchmark model is achieved by self-tuning PD controller based on RLS with adaptive directional forgetting method. The adaptive control design has a future in WT control applications.

A comparative study of identification methods, six adaptive controllers with the conventional PI controller and SMC, are shown here. As per the results, the best improvement in control of the output power by pitching in the full load region of the benchmark model has been achieved by self-tuning PD controller. The best identification method or the system is RLS with an adaptive directional forgetting method. Instead of a step input response design for the controllers, the controller design has been carried out for the stochastic wind and the performance is adjudged by the normalized sum of square tracking error (NSSE) index. The validation of the proposed self-tuning PD controller has been shown in comparison to the conventional controller with Monte-Carlo analysis to handle model parameter alteration and erroneous measurement issues.

This paper aims to explore the outcomes of an analysis on day by day task – journey planning conduct of senior citizens by using a modern dynamic model and a family unit travel overview, gathered in Bhubaneswar, Odisha, of India in 2018. The task-journey planning display assumes an unique time–space-constrained planning development.

The main commitment of this paper is to reveal day by day task – journey planning conduct through a comprehensive dynamic framework. Numerous behavioural subtleties are revealed by the subsequent empirical model. These incorporate the role that income plays in directing outside time consumption decisions of senior citizens. Senior citizens in the most elevated and least salary classes will in general have minor varieties in time consumption decisions than those in middle pay classifications. Generally speaking, the time consumption decisions become progressively steady with expanding age, demonstrating that more task durations and lower task recurrence become progressively predominant with increasing age.

Day by day task-type and area decisions reveal a reasonable irregular utility-amplifying level headed conduct of senior residents. Unmistakably expanding spatial availability to different task areas is an urgent factor in characterizing every day outside task interest of senior residents. It is likewise evident that the assorted variety of outside task-type decisions decreases with rise in age and senior citizens are major touchy to auto journey hour than to travel or non-mechanized journey hour.

The fundamental constraint to the dynamic structure is that the mode decision model was viewed as exogenic to the demonstrating framework. The essential purpose behind this supposition that was that senior citizens in the Bhubaneswar are overwhelmingly customers of the local car. Coordination of the mode decision display part inside this structure would deliver a full task-based journey request model that could catch trip age, starting times, outing circulation and mode decision using a solitary demonstrating framework.

The purpose of this paper is to present a unique model for the production–recycling–reuse of aluminium refreshment cans. It is presumed that disposed-off 250-ml aluminium cans are collected from the retail outlet. The cans are thereafter arranged into non-tainted and tainted categories.

The current model considers all the factors, i.e. producing, recycling and remanufacturing, whereas the previous models provide emphasis only one factor. Six procedures were considered in the improvement of the mathematical model.

In this paper, a recycling–reuse model that remanufactures non-tainted aluminium beverage cans and uses regrind from damaged non-tainted aluminium beverage cans mixed with parent aluminium material in the production of new cans was developed and analysed to reduce the amount of aluminium beverage cans that are disposed off in a scrapyard. The model is assumed to have no shortcomings, and the different percentages regarding the classes of cans are taken to be deterministic.

The model incorporates several unique aspects, including accounting for the cost of land use and associated environmental damage through the calculation of a present value that is charged to the manufacturer.

Agricultural aggregation schemes provide numerous farmer-facing benefits, including reduced transportation costs and improved access to higher-demand urban markets. However, whether aggregation schemes also have positive food security dimensions for consumers dependent on peri-urban and local markets in developing country contexts is currently unknown. This paper aims to narrow this knowledge gap by exploring the actors, governance structures and physical infrastructures of the horticultural value chain of Bihar, India, to identify barriers to using aggregation to improve the distribution of fruits and vegetables to more local market environments.

This study uses mixed methods. Quantitative analysis of market transaction data explores the development of aggregation supply pathways over space and time. In turn, semi-structured interviews with value chain actors uncover the interactions and decision-making processes with implications for equitable fruit and vegetable delivery.

Whilst aggregation successfully generates multiple producer-facing benefits, the supply pathways tend to cluster around urban export-oriented hubs, owing to the presence of high-capacity traders, large consumer bases and traditional power dynamics. Various barriers across the wider enabling environment must be overcome to unlock the potential for aggregation to increase local fruit and vegetable delivery, including informal governance structures, cold storage gaps and underdeveloped transport infrastructures.

To the best of the authors’ knowledge, this study is the first critical analysis of horticultural aggregation through a consumer-sensitive lens. The policy-relevant lessons are pertinent to the equitable and sustainable development of horticultural systems both in Bihar and in similar low- and middle-income settings.