scholarly journals The Investment Justification Estimate and Techno-economic and Ecological Aspects Analysis of the University Campus Microgrid

2019 ◽  
Vol 23 (1) ◽  
pp. 26
Author(s):  
Nemanja Savic ◽  
Vladimir Katic ◽  
Boris Dumnic ◽  
Dragan Milicevic ◽  
Zoltan Corba ◽  
...  

The paper presents the plan and design of the idea of the microgrid at the Faculty of Technical Sciences in Novi Sad (FTN NS) in the university campus, which is based on the application of several different distributed energy sources. The main distributed energy sources used and planned for the distributed electricity generation in the microgrid “FTN NS” are the photovoltaic power plant with a nominal output of 9.6 kW, a photovoltaic power plant with a nominal output power of 16.3 kW, a wind power plant with a nominal output power of 2 kW, a cogeneration plant for combined heat and power production of the nominal output power of 10 kWe + 17.5 kWt, two electric vehicles of 4 kW and 2.5 kW power, and battery energy storage system with a total capacity of 36 kWh. The paper describes the main technical characteristics, the estimation of electricity generation and the estimation of the amount of non-polluted gaseous greenhouse effect for each distributed source of energy. In order to verify the justification of the application of the proposed microgrid concept, a detailed techno-economic and ecological analysis of the aspects of the application of distributed energy sources in the microgrid “FTN NS” was carried out in the paper.

Energies ◽  
2019 ◽  
Vol 12 (10) ◽  
pp. 1942 ◽  
Author(s):  
Andrzej Tomczewski ◽  
Leszek Kasprzyk ◽  
Zbigniew Nadolny

The paper presents issues of optimisation of a wind power plant–energy storage system (WPP-ESS) arrangement operating in a specific geographical location. An algorithm was developed to minimise the unit discounted cost of electricity generation in a system containing a wind power plant and flywheel energy storage. In order to carry out the task, population heuristics of the genetic algorithm were used with modifications introduced by the author (taking into account the coefficient of variation of the generation in the quasi-static term of the penalty and the selection method). The set of inequality restrictions related to the technical parameters of turbines and energy storage and the parameters of energy storage management has been taken into account with the application of the Powell–Skolnick penalty function (Michalewicz modification). The results of sample optimisation calculations for two wind power plants of 2 MW were presented. The effects achieved in the process of optimisation were described—especially the influence of the parameters of the energy storage management system on the unit cost of electricity generation. The use of a system with higher unit costs of energy generation compared to independently operating wind turbines was justified in the context of improving the conditions of compatibility with the power system—the strategy belongs to a power firming group.


2021 ◽  
Vol 2021 (1) ◽  
pp. 38-44
Author(s):  
I.M. Buratynskyi ◽  

The peculiarity of the operation of solar photovoltaic power plants is the dependence of the generation power on weather conditions, which leads to the maximum production of electrical energy at noon hours of the day. Due to a decrease in electricity consumption, insufficient unloading capacity of pumped storage power plants in the integrated energy system of Ukraine and the specifics of electricity production at solar photovoltaic power plants, dispatching restrictions on the level of generation power are already taking place. To transfer volumes of electrical energy in the world, electrical energy storage systems are used, which operate based on lithium-ion storage batteries. Such systems have a number of advantages over other battery energy systems, which allows their implementation in almost any power generation facility. With the help of energy storage systems, it is possible to make a profit through the purchase of electric energy during a period of low prices and its release during a period of high prices, allowing consumers to save money on its payment. In this paper, we simulate the use of a battery energy storage system for storing electrical energy to transfer excess electrical energy from a solar photovoltaic power plant. To conduct a study and identify excess capacity of a solar photovoltaic power plant, the daily schedule of electrical load is equalized to the capacity of a separate power plant Because of the study, the optimal time for charging and discharging the battery was determined, from which it can be seen that the need to transfer excess electricity to a solar photovoltaic power plant occurs at lunchtime, and their discharge at the peak is the graph of the electrical load of the power system. The aggregate operation of a solar power plant with a total installed capacity of photovoltaic power at the level of 10 MW (DC) and a battery energy storage system for accumulating electric energy with a capacity of 3.75 MWh was simulated. For the study day, the required capacity of a battery system for accumulating electric energy at the level of 1.58 MW was determined. Using the methodology of the levelized cost of electricity and storage, a technical and economic assessment of the transfer of excess capacity of a solar photovoltaic power plant using a battery system for storing electrical energy was carried out. When calculating the cost of storage, the cost of the transferred electrical energy from the solar power plant was taken into account. From the results of technical and economic calculations, it can be seen that, in terms of the cost of equipment, as of 2020, the cost of supplying excess electrical energy from the battery energy storage system is growing when compared with the supply from a solar photovoltaic power plant. Taking into account some forecast assumptions, the cost of electricity supply from the battery energy storage system was calculated for the mode of transferring excess capacity of a solar photovoltaic power plant for 2025 and 2030 years. Keywords: modeling, power system, load demand curve, solar photovoltaic power plant, electric energy storage system, cost


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