• Energy Research
• 2021-2025close
• 13. Climate action close
• 12. Responsible consumption close
• 8. Economic growth close
• KG close

Widespread low-rise residential buildings with a seismically resistant concrete frame and brick infill walls have lower microclimate levels in cold seasons due to low temperatures on the inner wall corner surfaces.These temperatures are lower if there is a corner column. For Bishkek, this temperature is 4.6 °C lower than that for permissible microclimate, even when the external wall has the required 70 mm of mineral wool slab insulation. It is caused by the negative effect of the wall corner thermal bridge. This effect is determined by ArchiCAD 20 software packages by visualizing the temperature distribution in the cross-section of the corner, which needs an additional thermal insulation layer of 40 mm. Using the LiraSAPR 2013 software package, the authors reduced the square cross-section dimensions of the column by 40 mm to allow for that additional thermal insulation layer. The optimal width of this layer is determined for different options for the meeting angle of two external walls from 70° to 180°. For a typical 90° angle, an acceptable width is 860 mm. With this insulation, it is possible to achieve the required temperature at the corner. The authors eliminated the negative thermal effect of the corner by rounding it with cement-sand plaster. Using the isotherms, it was determined that the rounding radius of 300 mm allowed for equal temperatures on the corner and inner surface of the external walls. The achieved results show that the microclimate formed as in a room without external wall corners.

Road transport accounts for around 12% of global greenhouse gas (GHG) emissions. As many high-income countries are moving to decarbonise their road vehicle fleets, Kyrgyzstan – with rapid growth in passenger car ownership – is seeing a significant increase in transport-related GHG emissions and air pollution in urban areas. Whilst a transition to electric vehicles (EVs) is a key part of Kyrgyzstan’s Nationally Determined Contribution to the Paris Agreement, the potential for successful EV deployment in the region is under-researched. To fill this research gap, this paper presents an assessment of the potential for EV deployment in Kyrgyzstan. Firstly, we present an investigation of the policy and institutional landscape relating to transport and the promotion of EVs in Kyrgyzstan. Secondly, based on research of 50,000 car sales and interviews with 23 key stakeholders in the country, we present analysis of the existing Kyrgyz vehicle fleet. Thirdly, using information ascertained from the interviews and desk-based research, we conduct a Total Cost of Ownership assessment of EVs versus internal combustion engine vehicles (ICEVs) in the Kyrgyz context. We find that under the current conditions, EVs can have a lower total cost of ownership against similar ICEVs in Kyrgyzstan. However, it is evident that this is not typically the case: the analysis in this paper suggests that cost-competitiveness between EVs and ICEVs is more likely for larger and higher-powered vehicles, for which the ICEV version has a higher retail price. Finally, combining analysis of these results and analysis of the current conditions in Kyrgyzstan, trajectories for EV adoption in geographically and economically similar nations, and data from expert stakeholder interviews, we propose a set of policy recommendations to accelerate EV uptake in Kyrgyzstan.

Renewable energy technologies play a crucial role in solving global energy and environmental issues, and the pace of the energy transition directly depends on improving their efficiency. Presently, the development and implementation of renewable energy systems are ensured mainly through state funding, the possibilities of which are limited. The potential of attracting private investments depends directly on their impact on companies’ profitability indicators, and the uncertainty regarding the return on investments is one of the main barriers affecting investors’ decision-making. Based on a vector autoregressive model for analysing the stationary time series, the paper explores the impact of long-term investments and research and development costs in renewable energy technologies on the financial performance of ten of the largest companies operating in this field. The study’s results showed that investments and spending on research and development positively affect such companies’ profitability indicators as earnings before interest, taxes, depreciation and amortisation, earnings before interest and tax, net income, and return on investment. The obtained results can be used to substantiate the economic effectiveness of investments in developing and improving renewable energy technologies when forming the companies’ financial policies to support them.

Climate change and other global change drivers threaten plant diversity in mountains worldwide. A widely documented response to such environmental modifications is for plant species to change their elevational ranges. Range shifts are often idiosyncratic and difficult to generalize, partly due to variation in sampling methods. There is thus a need for a standardized monitoring strategy that can be applied across mountain regions to assess distribution changes and community turnover of native and non-native plant species over space and time. Here, we present a conceptually intuitive and standardized protocol developed by the Mountain Invasion Research Network (MIREN) to systematically quantify global patterns of native and non-native species distributions along elevation gradients and shifts arising from interactive effects of climate change and human disturbance. Usually repeated every five years, surveys consist of 20 sample sites located at equal elevation increments along three replicate roads per sampling region. At each site, three plots extend from the side of a mountain road into surrounding natural vegetation. The protocol has been successfully used in 18 regions worldwide from 2007 to present. Analyses of one point in time already generated some salient results, and revealed region-specific elevational patterns of native plant species richness, but a globally consistent elevational decline in non-native species richness. Non-native plants were also more abundant directly adjacent to road edges, suggesting that disturbed roadsides serve as a vector for invasions into mountains. From the upcoming analyses of time series even more exciting results especially about range shifts can be expected. Implementing the protocol in more mountain regions globally would help to generate a more complete picture of how global change alters species distributions. This would inform conservation policy in mountain ecosystems, where some conservation policies remain poorly implemented.

Energy generation is currently evolving into a smart distribution system that incorporates several green energy resources at a distributed level, ensuring that clean energy is generated without releasing harmful gases, that operational procedures are consistent, and that energy management and supervision arrangements are improved. This paper proposes a multi-agent system-based microgrid energy management and proper control in distributed systems. For the complexity of energy management in distributed systems, a multi-agent system-based decentralized control architecture was developed. The proposed technique is based on several smart agents, each agent is based on the microgrid data for energy management and frequency control. The proposed energy management system based on the multi-agent system was tested by simulation under renewable resource fluctuations and seasonal load demand. The simulation results show that the proposed energy management system proved to be more resilient and high-performance controls than conventional centralized energy control systems.

Abstract Tajikistan and Kyrgyzstan are the two countries in Central Asia that have a huge reserve of hydro resources of the region. It is important to recognize the significance of the part played by the micro-hydropower plants (HPP) in the electric power generation in Tajikistan and Kyrgyzstan from the point of view of sustainable economic development. After all, the construction of micro-HPPs in mountainous areas will reliably ensure the development of small and medium-sized enterprises in the field of agriculture and livestock, industry, tourism, improve the social conditions of the population, as well as ensure the production of “green” hydrogen, which will contribute to the development of an environmentally friendly transport system in the regions. Micro HPPs gained recognition as a good alternative to traditional power generation for many developing countries around the world. This study presents a structural model and methodology of choice of a feasible type of micro HPP using the developed algorithm for calculation of hydro turbines’ characteristics based on the hydrological characteristics of small and shallow watercourses located in Central Asian countries, such as Kyrgyzstan and Tajikistan. Based on this model, the software “Calculation and choosing the type of hydro turbines for micro HPPs” has been developed. Depending on the load, a consumer can choose one of the suggested types of micro-hydroelectric power plants to meet his requirements. When choosing the type of micro-hydroelectric power station, a consumer should also take into account the factor of the seasonality of the water level, the constancy and speed of the water, and the volume of river water, since in some places the water freezes in winter.

Internet of Things (IoT) has attracted tremendous research attention in the recent past fromindustry and academia. IoT is quite helpful in uplifting living standards by transforming conventional technology into smart systems. Greenhouse production is considered as an ultimate solution for rising global food demands with the growing population. Greenhouse provides a year-round production facility for fresh vegetables with around 50% increased production rate in comparison to open-air cultivation. However, energy consumption and labor cost in greenhouses account for more than 50% of the cost of greenhouse production. In this paper, we have proposed a novel optimization scheme that aims to achieve a trade-off between energy consumption and desired climate setting in greenhouse i.e. temperature, $${\mathrm{CO}}_2$$ level, and humidity. For performance evaluation of the proposed system, we have developed an ad-hoc emulator of the greenhouse environment. For the proposed model validation and experimental analysis, we have used 15 days of external environmental data collected in Jeju, South Korea. Proposed optimization scheme results are compared with a baseline scheme. Comparative analysis of experimental results shows that our proposed model maintains desired indoor environment for maximizing crop production with 26.56% reduced energy consumption than the baseline scheme. Furthermore proposed model achieve a 27.76% cost reduction when compared to the baseline scheme. Better optimization results of the proposed scheme give us the confidence to further investigate its effectiveness in a real environment for achieving improved energy efficiency.