Adaptive ensemble models for medium-term forecasting of water inflow when planning electricity generation under climate change

Matrenin, Pavel; Safaraliev, Murodbek; Dmitriev, Stepan A.; Kokin, Sergey; Eshchanov, Bahtiyor; Rusina, Anastasia G.

doi:10.1016/j.egyr.2021.11.112

Cited by 20 publications

(10 citation statements)

References 12 publications

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“…For instance, hydropower resources are utilized in the hydropower plants (HPP) on small mountain rivers (in total 11 units) and alternative sources which include one solar power plant (SPP) in conjunction with an energy storage device. The key feature of the electrical energy balance under these conditions is the unpredictability of energy generation by the above-indicated generation sources [44][45][46][47].…”

Section: The Study Object-gorno-badakhshan Autonomous Oblastmentioning

confidence: 99%

“…However, during certain periods there is a shortage of provided electricity leading to the search for alternative energy sources, where one of the suitable is wind energy. For instance, from mid-autumn to mid-spring the water level in the rivers drops that creating a possibility to use wind energy, and in summer it would be advisable to accumulate excess energy further to export in case of a need or storage [47][48][49].…”

Section: The Study Object-gorno-badakhshan Autonomous Oblastmentioning

confidence: 99%

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Short-Term Prediction of the Wind Speed Based on a Learning Process Control Algorithm in Isolated Power Systems

et al. 2023

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Predicting the variability of wind energy resources at different time scales is extremely important for effective energy management. The need to obtain the most accurate forecast of wind speed due to its high degree of volatility is particularly acute since this can significantly improve the planning of wind energy production, reduce costs and improve the use of resources. In this study, a method for predicting the speed of wind flow in an isolated power system of the Gorno-Badakhshan Autonomous Oblast (GBAO), based on the use of a neural network with a learning process control algorithm, is proposed. Predicting is performed for four seasons of the year, based on hourly retrospective meteorological data of wind speed observations. The obtained wind speed average error forecasting ranged from 20–28% for a day ahead. The prediction results serve as a basis for optimizing the energy consumption of individual generating consumers to minimize their financial and technical costs. In addition, this study takes into account the possibility of exporting electricity to a neighboring country as an additional income line for the isolated GBAO power system during periods of excess energy from hydropower plants (March–September), which is a systematic vision of solving the problem of improving energy efficiency in the conditions of autonomous power supply.

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Section: The Study Object-gorno-badakhshan Autonomous Oblastmentioning

confidence: 99%

Section: The Study Object-gorno-badakhshan Autonomous Oblastmentioning

confidence: 99%

Short-Term Prediction of the Wind Speed Based on a Learning Process Control Algorithm in Isolated Power Systems

et al. 2023

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“…The main factors delaying the use of energy resources are as follows: assessment of the impact of hydropower construction on the environment, the complex nature of the use of watercourse water resources and the energy market in Central Asia. It should be noted that small and even medium-sized Pamir rivers are either insufficiently or not studied at all in terms of energy potential [17,33,34].…”

Section: An Assessment Of Energy Resources Of the Pamir Region Of Rep...mentioning

confidence: 99%

“…As a result, the HPP cannot cover the maximum loads of the daily schedule during morning and evening peaks. In winter, when the maximum demand for electricity is observed in all regions of the Pamirs, the SHPPs that do not have large-capacity reservoirs provide almost minimal power [17,33,34].…”

Section: General Characteristics Of the Pamir Power Systemmentioning

confidence: 99%

Optimal Management of Energy Consumption in an Autonomous Power System Considering Alternative Energy Sources

et al. 2022

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This work aims to analyze and manage the optimal power consumption of the autonomous power system within the Pamir region of Republic of Tajikistan, based on renewable energy sources. The task is solved through linear programming methods, production rules and mathematical modeling of power consumption modes by generating consumers. It is assumed that power consumers in the considered region have an opportunity to independently cover energy shortage by installing additional generating energy sources. The objective function is to minimize the financial expenses for own power consumption, and to maximize them from both the export and redistribution of power flows. In this study, the optimal ratio of power generation by alternative sources from daily power consumption for winter was established to be hydroelectric power plants (94.8%), wind power plant (3.8%), solar photovoltaic power plant (0.5%) and energy storage (0.8%); while it is not required in summer due to the ability to ensure the balance of energy by hydroelectric power plants. As a result, each generating consumer can independently minimize their power consumption and maximize profit from the energy exchange with other consumers, depending on the selected energy sources, thus becoming a good example of carbon-free energy usage at the micro- and mini-grid level.

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“…The territory of this region, as well as almost the entire territory of the country, is a mountainous area. Power energy production is mainly carried out based on RESs, i.e., hydropower plants [29][30][31][32]. Pamir Energy is engaged in power supply for consumers in the GBAR, consisting of eight districts.…”

Section: The Real-life Object Of Researchmentioning

confidence: 99%

A Novel Approach of Synchronization of Microgrid with a Power System of Limited Capacity

et al. 2021

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Currently, active networks called microgrids are formed on the basis of local power supply systems with a small share of distributed generation. Microgrids operating in an island mode, in some cases, have the ability to transfer electricity excess to an external network leading to a synchronization requirement; thus, the optimization task in terms of the system’s synchronization must be considered. This paper proposes a method for obtaining synchronization between microgrids and power systems of limited capacity based on a passive synchronization algorithm, allowing us to connect a microgrid to an external power system with a minimum impact moment on the shaft of the generating equipment. The algorithm application was demonstrated by considering a real-life object in Tajikistan. The simulation was carried out on RastrWin3. The obtained results show that the microgrid generator is connected to an external power system at an angle of 0.3° and a power surge of 29 kW, unlike the classical synchronization algorithm with an angle of 6.8° and a power surge of 154 kW (a reduction of the shock moment by more than five times). The proposed synchronization method allows us to reduce the resource consumption of the generating equipment and increase the reliability and efficiency of the functioning units of the examined power system.

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Adaptive ensemble models for medium-term forecasting of water inflow when planning electricity generation under climate change

Cited by 20 publications

References 12 publications

Short-Term Prediction of the Wind Speed Based on a Learning Process Control Algorithm in Isolated Power Systems

Short-Term Prediction of the Wind Speed Based on a Learning Process Control Algorithm in Isolated Power Systems

Optimal Management of Energy Consumption in an Autonomous Power System Considering Alternative Energy Sources

A Novel Approach of Synchronization of Microgrid with a Power System of Limited Capacity

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