Investment and Resource Use Pattern followed by Dairy Farmers in Haryana

Dairy sector plays a critical role in growth of rural India by providing livelihoodopportunities to millions of people. The present study was conducted in Zone-I and ZoneII of the Haryana state. District Kaithal and Karnal were selected from Zone I whereasSirsa and Hisar districts represented Zone II to study the investment and resource usepattern followed by the dairy farmers. To achieve the objective the primary data from the200 sampled dairy farms (divided into three categories i.e. small, medium and large herdsize of milch animals) were collected through survey method. The study revealed that thetotal investment per milch animal per day in small, medium and large herd size group wasRs.175.50, 178.40 and 181.80, respectively, in Zone-I and Rs.170.08, 174.30 and 175.86,respectively, in Zone-II. From total investment, major proportion was covered byinvestment on feed and fodder, followed by concentrates and labours in both the Zones. Itmay be suggested that providing feed concentrates and high yielding seeds of green foddercrops at cheaper rates and credit facility should be strengthened.

Risks of investing in the agricultural sector of Ukraine's economy in the context of modernization of the industry

Investment is an important element in modernizing agriculture. However, the studied industry is characterized by features that lead to risky activities. The purpose of the article is to study the problem of investing in the agricultural sector of Ukraine's economy and determine the degree of risks of this process in the context of modernization. Studies show that investment is a necessary part of modernizing the agricultural sector of the economy. The specifics of investment in the agricultural sector of the economy, primarily due to the characteristics of the industry, ie depends on a variety of climatic, social, economic, financial and other factors. A key component of the investment process is to identify effective sources of funding. The analysis shows that 90% of the total investment in agriculture in Ukraine is the own funds of enterprises and organizations. In second place - loans in the form of loans and other loans (8.6%). Investment resources of the state and local budgets are extremely low – 0, 3 and 0.1%, respectively. All risk factors of the industry can be divided into internal and external. Agriculture is an important sector of the economy, on the development of which depends the food security of the population. Economic analysis of the industry has shown the need for its modernization. One of the directions of modernization of agricultural production is the intensification of investment activity, which is at a low level of development due to the riskiness of the industry.

Research on Distribution Network Reliability Investment Estimation Method Based on Sequence Linearization Correlation Analysis

This paper presents an estimation method of distribution network reliability planning Investment Based on sequence linearization correlation analysis. Firstly, the planning business index closely related to reliability are selected, and the control objectives of reliability index are decomposed into the promotion objectives of each planning business index through sequence linearization correlation analysis. Then, the typical engineering construction scenarios corresponding to each planning business index are constructed, and the investment required to achieve the corresponding promotion objectives of business index is estimated according to the typical scenarios, Finally, the total investment of reliability planning is obtained. The example shows that the method can be applied to the actual distribution network with complex grid conditions and various planning schemes, and can provide powerful guidance for power supply enterprises to improve the efficiency of capital use

Improving Thermoeconomic and Environmental Performance of District Heating via Demand Pooling and Upscaling

This study evaluates the effects of pooling heat demands in a district for the purpose of upscaling heat production units by means of energy, exergy, economic, exergoeconomic, and environmental indicators, as well as the sensitivity to investment and fuel costs. The following production systems to satisfy the heat demands (domestic hot water production and space heating) of a mixed district composed of office (80%), residential (15%), and commercial (5%) buildings are considered: gas- and biomass-fired boilers, electric boilers and heat pumps (grid-powered or photovoltaic -powered), and solar thermal collectors. For comparison, three system sizing approaches are examined: at building scale, at sector scale (residential, office, and commerce), or at district scale. For the configurations studied, the upscaling benefits were up to 5% higher efficiency (energy and exergy), there was lower levelized cost of heat for all systems (between 20% and 54%), up to 55% lower exergy destruction costs, and up to 5% greater CO2 mitigations. In conclusion, upscaling and demand pooling tend to improve specific efficiencies, reduce specific costs, reduce total investment through the peak power sizing method, and mitigate temporal mismatch in solar-driven systems. Possible drawbacks are additional heat losses due to the distribution network and reduced performance in heat pumps due to the higher temperatures required. Nevertheless, the advantages outweigh the drawbacks in most cases.

Research on Substation Project Cost Prediction Based on Sparrow Search Algorithm Optimized BP Neural Network

The prediction of power grid engineering cost is the basis of fine management of power grid engineering, and accurate prediction of substation engineering cost can effectively ensure the fine operation of engineering funds. With the continuous expansion of the engineering system, the influencing factors and data dimensions of substation project investment are gradually diversified and complex, which further increases the uncertainty and complexity of substation project cost. Based on the concept of substation engineering data space, this paper investigates the influencing factors and constructs the static total investment intelligent prediction model of substation engineering. The emerging swarm intelligence algorithm, sparrow search algorithm (SSA), is used to optimize the parameters of the BP neural network to improve the prediction accuracy and convergence speed of neural network. In order to test the validity of the model, an example analysis is carried out based on the data of a provincial substation project. It was found that the SSA-BP can effectively improve the prediction accuracy and provide new methods and approaches for practical application and research.

Study of saving and investment pattern on sample farms households

The saving and investment pattern of different forms sample group was studied during 2014-16 and it was observed that large farm holders were able to save higher income than small farmers while lowest income group had negative savings. In respect of investment on different fixed assets, irrigation was on first priority, followed by purchase of milch animals, farms buildings and investment in land and its improvement. Investment on working capital amongst different cash inputs, hired human labourer accounted highest share (29.44 per cent), followed by manure & fertilizers (22.33 per cent), hired power tractor (16.96 per cent), irrigation (13.61 per cent) and seeds (13.50 per cent) to total cash inputs. Marginal farmers could not invest for nonfarm physical capital because of no savings with them. Small and large farmers groups invested in all the items in which it was highest in working capital (61.28 to 61.84 per cent), followed by investment in fixed capital (14.41 to 16.84 per cent), financial capital (12-14 per cent) and non-farm capital (7-12 per cent). The highest investment was made on working capital (69.02 per cent) by sample farmers. Current income was found to be the main source of finance in all income groups which accounted for 49.70 to 94.79 per cent share of the total investment followed by savings which shared for 40.10 to 49.12 per cent in total investment.

Double-objective optimization-based firefly algorithm of a stand-alone photovoltaic/water pumping system for water supply in rural and remote areas: a case study

A techno-economic study of a stand-alone PV water pumping system for water supply is done in this paper. An optimal design of the system is realized thanks to a double-objective optimization based on a proposed operational strategy of the system and on firefly algorithm (FA). The two objective functions simulated simultaneously using FA are: the function defining the cost of water (COW) and the function which defines the loss of water supply probability (LWSP). The system is designed to supply water to around 328 households in Cameroon, each composed by an average of six (06) persons. For different LWSP, the double-objective simulation determines the optimal configurations of the system with their related cost. The optimal and reliable (LWSP of 0%) system configuration obtained is composed by a number of 7 PV modules, a reservoir volume of 98.4 m3 with 2 days autonomy, a total dynamic head of 40 m, and a pump power of around 1 kW. The related COW corresponding to this configuration is 0.1185 $/m3, and the total investment cost is 27,506 $. The sensitivity analysis of the system revealed that the PV size, the volume of reservoir storage, and the efficiency of the pump influence the system both technically and economically, whereas the total dynamic head only influences the system economically. The validation of the optimized system has been done by comparison with manufacturer datasheets. It is demonstrated in this paper that the techno-economic analysis of energy systems based on multi-objective optimization using firefly algorithm is a powerful tool for decision-making.

Research on possible sulfuric acid (H2SO4) production using sulfur/sulfur-containing feedstocks from Dung Quat refinery

This paper analyses the possibility for H2SO4 production using sulfur/sulfur-containing feedstocks from Dung Quat Refinery in terms of market, technology and economic efficiency. Domestic production of H2SO4 currently does not meet the domestic demand, the shortfall must therefore be compensated by imports. It is forecast that the domestic market will lack about 464 thousand tons of H2SO4 by 2025. The H2SO4 production project with a capacity of 200 thousand tons per year is proposed to go into operation in 2025. In the case of indirect production of H2SO4 from H2S rich gas through the intermediate sulfur product, the project has an estimated total investment cost of USD 143.2 million, its IRR will be around 3.2%, its [email protected]% will be USD 55.1 million and the total payback period will be 14 years and 4 months. In case of using H2S rich gas directly as feedstock, the project has an estimated total investment cost of USD 102.4 million, its IRR will be around 16.3%, its [email protected]% will be USD 15.7 million and the total payback period will be 5 years and 5 months.

PERFORMANCE OF INVESTMENT MANAGEMENT: A STUDY ON SOCIAL ISLAMI BANK LIMITED (SIBL)

This study attempts to understand the level of efficiency of investment management of social Islami bank limited (SIBL). In this regards, different aspects (i.e., amount, ratio, profit and growth) of deposit, investment, investment modes and procedures are scrutinized thoroughly. To conduct the study, secondary data sources have been primarily used. Some information was also collected from officials over the phone. The study was based on five consecutive years i.e., 2015 to 2019.The major findings are that the ratio of investment deposit also remains as high as 90%. The bank invests more in Murabaha, Bai-Muazzal, HPSM and Quard. The ratio of classified investment to total investment increased 8.20% till 2017 and decrease to 6.63% up to 2019 whereas the ratio of unclassified investment decrease to 89.09% till 2017 and increase to 91.71% up to 2019. There has an increase of sub-standard and doubtful investments till 2017 and a decrease up to 2019. But in case of bad or loss investment, an upward trend has been observed till 2018 and had a negligible decrease in 2019. The last part of the analysis shows that the overall profit growth of investment fluctuated over years but remains positive i.e., 11.39%. In conclusion, the bank is moderately efficient in investment management.

General Insurance Subsector Financial Performance in 2020/2021: Does the Covid-19 Pandemic Matter?

This paper is aimed at analyzing the impact of the covid-19 pandemic on the performance of general insurance subsector in Indonesia. Secondary data obtained from the Indonesia Financial Service Authority which include annual growth rate (year on year) of total asset, technical reserve, investment, equity, and net premium income for the periods between April 2019, 2020 and 2021 to March 2019, 2020 and 2021 were used in this study. Using the dependent sample t-test, it is revealed that the impacts of the covid-19 pandemic on the performance of general insurance subsector were varied. The growth rates of the total asset, total investment, and net premium income of general insurance subsector significantly decreased during the covid-19 pandemic. The decline of these variables was influenced by the covid-19 pandemic. In the meantime, the growth rate of technical reserve and equity were not significantly influenced by the covid-19 pandemic. The growth rate of these variables decreases; however, the degree of decreases was not statistically significant. Findings of the study indicate that further study is required to examine in more detail the factors that potentially affect the performance of the general insurance subsector in relation to the covid-19 pandemic.