Temat: optimal energy management - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: A multiperiodal management method at user level for storage systems using artificial neural network forecasts
Autorzy:: Belli, G.
Brusco, G.
Burgio, A.
Menniti, D.
Pinnarelli, A.
Sorrentino, N.
Vizza, P.
Powiązania:: https://bibliotekanauki.pl/articles/136188.pdf
Data publikacji:: 2016
Wydawca:: EEEIC International Barbara Leonowicz Szabłowska
Tematy:: Storage management
multi-pediod scheduling
prosumer
optimal energy management
Opis:: The increase of renewable non-programmable production and the necessity to locally self-consume the produced energy led to utilize ever more storage systems. To correctly utilize storage systems, an opportune management method has to be utilized. This paper implements a multi-period management method for storage systems, using different management strategies. The method aims to minimize the total absorbed and supplied energy or the peak power exchanged with the grid. The results show the effectiveness of the method in diminishing the energy exchanged with the grid and also the possibility to optimize the performance of the storage systems.
Źródło:: Transactions on Environment and Electrical Engineering; 2016, 1, 4; 29-36
2450-5730
Pojawia się w:: Transactions on Environment and Electrical Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Short-term optimal energy management in stand-alone microgrid with battery energy storage
Autorzy:: Paliwal, N. K.
Singh, A. K.
Singh, N. K.
Powiązania:: https://bibliotekanauki.pl/articles/140998.pdf
Data publikacji:: 2018
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: artificial bee colony
battery energy storage
clean energy sources
optimal energy management
stand-alone microgrid
Opis:: The optimal energy management (OEM) in a stand-alone microgrid (SMG) is a challenging job because of uncertain and intermittent behavior of clean energy sources (CESs) such as a photovoltaic (PV), wind turbine (WT). This paper presents the effective role of battery energy storage (BES) in optimal scheduling of generation sources to fulfill the load demand in an SMG under the intermittency of theWT and PV power. The OEM is performed by minimizing the operational cost of the SMG for the chosen moderate weather profile using an artificial bee colony algorithm (ABC) in four different cases, i.e. without the BES and with the BES having a various level of initial capacity. The results show the efficient role of the BES in keeping the reliability of the SMG with the reduction in carbon-emissions and uncertainty of the CES power. Also, prove that the ABC provides better cost values compared to particle swarm optimization (PSO) and a genetic algorithm (GA). Further, the robustness of system reliability using the BES is tested for the mean data of the considered weather profile.
Źródło:: Archives of Electrical Engineering; 2018, 67, 3; 499--513
1427-4221
2300-2506
Pojawia się w:: Archives of Electrical Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Comparative calculation of the fuel-optimal operating strategy for diesel hybrid railway vehicles
Autorzy:: Leska, M.
Aschemann, H.
Melzer, M.
Meinert, M.
Powiązania:: https://bibliotekanauki.pl/articles/330621.pdf
Data publikacji:: 2017
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: hybrid railway vehicle
fuel optimal energy management
dynamic programming
sensitivity optimisation
pojazd szynowy
pojazd hybrydowy
gospodarka energetyczna
programowanie dynamiczne
Opis:: In contrast to road-based traffic, the track as well as the corresponding duty cycle for railways are known beforehand, which represents a great advantage during the development of operating strategies for hybrid vehicles. Hence the benefits of hybrid vehicles regarding the fuel consumption can be exploited by means of an off-line optimisation. In this article, the fuel-optimal operating strategy is calculated for one specified track using two hybrid railway vehicles with different kinds of energy storage systems: on the one hand, a lithium-ion battery (high-energy storage) and, on the other, a double layer capacitor (high-power storage). For this purpose, control-oriented simulation models are developed for each architecture addressing the main effects contributing to the longitudinal dynamics of the power train. Based on these simulation models, the fuel-optimal operating strategy is calculated by two different approaches: Bellman’s dynamic programming, a well-known approach in this field, and an innovative sensitivity-based optimisation.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2017, 27, 2; 323-336
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Optimal Management of a Virtual Power Plant
Autorzy:: Jigoria-Oprea, D.
Vuc, G.
Litcanu, M.
Powiązania:: https://bibliotekanauki.pl/articles/136214.pdf
Data publikacji:: 2016
Wydawca:: EEEIC International Barbara Leonowicz Szabłowska
Tematy:: energy market
optimal management
renewable energy sources
virtual power plant
Opis:: Deregulation of energy market led to the development of flexible and efficient framework for energy trading by energy companies in a competitive environment. Both deregulation and the concern towards environment issues increased the number of small and medium renewable power plants distributed in the network. The variability of renewable energy sources and the lack of their central monitoring led to new challenges concerning power system operation. The idea of aggregation for distributed energy sources led to the concept of virtual power plant, which determines a better control of production units but also a better visibility for the system operator. In this paper, the authors propose an optimal management solution which can offer a virtual power plant the capability to sell complete services, both for production and demand side management, by decreasing the necessary reserve for balance.
Źródło:: Transactions on Environment and Electrical Engineering; 2016, 1, 3; 106-111
2450-5730
Pojawia się w:: Transactions on Environment and Electrical Engineering
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Smart control of energy storage system in residential photovoltaic systems for economic and technical efficiency
Autorzy:: Kaczorowska, Dominika
Rezmer, Jacek
Janik, Przemysław
Sikorski, Tomasz
Powiązania:: https://bibliotekanauki.pl/articles/2202548.pdf
Data publikacji:: 2023
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: economic efficiency
energy storage system ESS
microgrid management
optimal power flow
OPF
particle swarm optimisation PSO
Opis:: In recent years, due to the increasing number of renewable energy sources, which are characterised by the stochastic nature of the generated power, interest in energy storage has increased. Commercial installations use simple deterministic methods with low economic efficiency. Hence, there is a need for intelligent algorithms that combine technical and economic aspects. Methods based on computational intelligence (CI) could be a solution. The paper presents an algorithm for optimising power flow in microgrids by using computational intelligence methods. This approach ensures technical and economic efficiency by combining multiple aspects in a single objective function with minimal numerical complexity. It is scalable to any industrial or residential microgrid system. The method uses load and generation forecasts at any time horizon and resolution and the actual specifications of the energy storage systems, ensuring that technological constraints are maintained. The paper presents selected calculation results for a typical residential microgrid supplied with a photovoltaic system. The results of the proposed algorithm are compared with the outcomes provided by a deterministic management system. The computational intelligence method allows the objective function to be adjusted to find the optimal balance of economic and technical effects. Initially, the authors tested the invented algorithm for technical effects, minimising the power exchanged with the distribution system. The application of the algorithm resulted in financial losses, €12.78 for the deterministic algorithm and €8.68 for the algorithm using computational intelligence. Thus, in the next step, a control favouring economic goals was checked using the CI algorithm. The case where charging the storage system from the grid was disabled resulted in a financial benefit of €10.02, whereas when the storage system was allowed to charge from the grid, €437.69. Despite the financial benefits, the application of the algorithm resulted in up to 1560 discharge cycles. Thus, a new unconventional case was considered in which technical and economic objectives were combined, leading to an optimum benefit of €255.17 with 560 discharge cycles per year. Further research of the algorithm will focus on the development of a fitness function coupled to the power system model.
Źródło:: Archives of Electrical Engineering; 2023, 72, 1; 81--102
1427-4221
2300-2506
Pojawia się w:: Archives of Electrical Engineering
Dostawca treści:: Biblioteka Nauki

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