Bi-level fuzzy stochastic expectation modelling and optimization for energy storage systems planning in virtual power plants

One of the recent trends that concern renewable energy sources and energy storage systems is the concept of virtual power plants (VPP). The majority of research now focuses on analyzing case studies of VPP in different issues. This article presents the investigation that is based on a real VPP. That VPP operates in Poland and consists of hydropower plants (HPP), as well as energy storage systems (ESS). For specific analysis, cluster analysis, as a representative technique of data mining, was selected for power quality (PQ) issues. The used data represents 26 weeks of PQ multipoint synchronic measurements for 5 related to VPP points. The investigation discusses different input databases for cluster analysis. Moreover, as an extension to using classical PQ parameters as an input, the application of the global index was proposed. This enables the reduction of the size of the input database with maintaining the data features for cluster analysis. Moreover, the problem of the optimal number of cluster selection is discussed. Finally, the assessment of clustering results was performed to assess the VPP impact on PQ level.

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A CVaR-Robust Risk Aversion Scheduling Model for Virtual Power Plants Connected with Wind-Photovoltaic-Hydropower-Energy Storage Systems, Conventional Gas Turbines and Incentive-Based Demand Responses

Energies ◽

10.3390/en11112903 ◽

2018 ◽

Vol 11 (11) ◽

pp. 2903 ◽

Cited By ~ 3

Author(s):

Liwei Ju ◽

Peng Li ◽

Qinliang Tan ◽

Zhongfu Tan ◽

GejiriFu De

Keyword(s):

Energy Storage ◽

Risk Aversion ◽

Decision Maker ◽

Gas Turbines ◽

Power Plants ◽

Storage Systems ◽

Economic Benefits ◽

Virtual Power ◽

Energy Storage Systems ◽

Scheduling Model

To make full use of distributed energy resources to meet load demand, this study aggregated wind power plants (WPPs), photovoltaic power generation (PV), small hydropower stations (SHSs), energy storage systems (ESSs), conventional gas turbines (CGTs) and incentive-based demand responses (IBDRs) into a virtual power plant (VPP) with price-based demand response (PBDR). Firstly, a basic scheduling model for the VPP was proposed in this study with the objective of the maximum operation revenue. Secondly, a risk aversion model for the VPP was constructed based on the conditional value at risk (CVaR) method and robust optimization theory considering the operating risk from WPP and PV. Thirdly, a solution methodology was constructed and three cases were considered for comparative analyses. Finally, an independent micro-grid on an industrial park in East China was utilized for an example analysis. The results show the following: (1) the proposed risk aversion scheduling model could cope with the uncertainty risk via a reasonable confidence degree β and robust coefficient Γ. When Γ ≤ 0.85 or Γ ≥ 0.95, a small uncertainty brought great risk, indicating that the risk attitude of the decision maker will affect the scheduling scheme of the VPP, and the decision maker belongs to the risk extreme aversion type. When Γ ∈ (0.85, 0.95), the decision-making scheme was in a stable state, the growth of β lead to the increase of CVaR, but the magnitude was not large. When the prediction error e was higher, the value of CVaR increased more when Γ increased by the same magnitude, which indicates that a lower prediction accuracy will amplify the uncertainty risk. (2) when the capacity ratio of (WPP, PV): ESS was higher than 1.5:1 and the peak-to-valley price gap was higher than 3:1, the values of revenue, VaR, and CVaR changed slower, indicating that both ESS and PBDR can improve the operating revenue, but the capacity scale of ESS and the peak-valley price gap need to be set properly, considering both economic benefits and operating risks. Therefore, the proposed risk aversion model could maximize the utilization of clean energy to obtain higher economic benefits while rationally controlling risks and provide reliable decision support for developing optimal operation plans for the VPP.

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Sizing and Management of Energy Storage Systems in Large-Scale Power Plants Using Price Control and Artificial Intelligence

Energies ◽

10.3390/en14113296 ◽

2021 ◽

Vol 14 (11) ◽

pp. 3296

Author(s):

Carlos García-Santacruz ◽

Luis Galván ◽

Juan M. Carrasco ◽

Eduardo Galván

Keyword(s):

Energy Storage ◽

Power Plants ◽

Large Scale ◽

Storage Systems ◽

Renewable Energy Sources ◽

Ancillary Services ◽

Energy Sources ◽

Energy Storage Systems ◽

Electric System ◽

Fundamental Part

Energy storage systems are expected to play a fundamental part in the integration of increasing renewable energy sources into the electric system. They are already used in power plants for different purposes, such as absorbing the effect of intermittent energy sources or providing ancillary services. For this reason, it is imperative to research managing and sizing methods that make power plants with storage viable and profitable projects. In this paper, a managing method is presented, where particle swarm optimisation is used to reach maximum profits. This method is compared to expert systems, proving that the former achieves better results, while respecting similar rules. The paper further presents a sizing method which uses the previous one to make the power plant as profitable as possible. Finally, both methods are tested through simulations to show their potential.

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USE OF PHOTOELECTRIC MODULES WITH DOUBLE-SIDED RECEIVING SURFACE FOR SMALL GENERATION UNITS

Construction and industrial safety ◽

10.37279/2413-1873-2021-20-93-100 ◽

2021 ◽

pp. 93-100

Author(s):

V. V. Kuvshinov ◽

E. A. Bekirov ◽

E. V. Guseva

Keyword(s):

Solar Cells ◽

Energy Storage ◽

Solar Energy ◽

Power Plants ◽

Storage Systems ◽

Renewable Energy Sources ◽

Experimental Studies ◽

Electrical Energy ◽

Photovoltaic Systems ◽

Energy Storage Systems

In the presented work, the possibility of using photovoltaic silicon panels with a double-sided arrangement of solar cells on the front and back sides is presented. With a lack of space for placing solar panels, these types of modules can significantly increase the generation of electrical energy. Equipping photovoltaic systems with rechargeable batteries contributes to a more rational consumption of electrical energy, while energy storage systems significantly increase the efficiency of solar generating systems. The proposed designs are intended to increase the power characteristics of solar energy converters in the winter months, in the presence of snow or when using reflective surfaces on road surfaces. The results of the experimental studies have shown a significant efficiency of the proposed designs, as well as an increase in the total generation of electrical energy. With the development of the global technical potential and a significant increase in the production of power plants for solar energy, a new opportunity has emerged to use combined solar plants for photovoltaic conversion of the flux of incident solar radiation. At the Department of Renewable Energy Sources and Electrical Systems and Networks at Sevastopol State University, at the site of the Institute of Nuclear Energy and Industry, a photovoltaic installation was developed and studied, consisting of two side silicon solar cells and energy storage systems. The article presents the results of experimental and theoretical studies, presents diagrams, drawings and graphs of various characteristics of the FSM-110D photovoltaic panel and storage batteries. The research results show the increased efficiency of the proposed installation, as well as a good possibility of using the presented photovoltaic systems to provide them with autonomous and individual consumers living in the Crimean region and the city of Sevastopol.

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A Thermodynamic Model of a High Temperature Hybrid Compressed Air Energy Storage System for Grid Storage

Volume 2: ASME 2016 Energy Storage Forum ◽

10.1115/es2016-59431 ◽

2016 ◽

Cited By ~ 4

Author(s):

Sammy Houssainy ◽

Reza Baghaei Lakeh ◽

H. Pirouz Kavehpour

Keyword(s):

Global Warming ◽

Energy Storage ◽

Power Plants ◽

Storage Systems ◽

Renewable Energy Sources ◽

Storage System ◽

Energy Storage System ◽

Compressed Air ◽

Compressed Air Energy Storage ◽

Energy Storage Systems

Human activity is overloading our atmosphere with carbon dioxide and other global warming emissions. These emissions trap heat, increase the planet’s temperature, and create significant health, environmental, and climate issues. Electricity production accounts for more than one-third of U.S. global warming emissions, with the majority generated by coal-fired power plants. These plants produce approximately 25 percent of total U.S. global warming emissions. In contrast, most renewable energy sources produce little to no global warming emissions. Unfortunately, generated electricity from renewable sources rarely provides immediate response to electrical demands, as the sources of generation do not deliver a regular supply easily adjustable to consumption needs. This has led to the emergence of storage as a crucial element in the management of energy, allowing energy to be released into the grid during peak hours and meet electrical demands. Compressed air energy storage can potentially allow renewable energy sources to meet electricity demands as reliably as coal-fired power plants. Most compressed air energy storage systems run at very high pressures, which possess inherent problems such as equipment failure, high cost, and inefficiency. This research aims to illustrate the potential of compressed air energy storage systems by illustrating two different discharge configurations and outlining key variables, which have a major impact on the performance of the storage system. Storage efficiency is a key factor to making renewable sources an independent form of sustainable energy. In this paper, a comprehensive thermodynamic analysis of a compressed air energy storage system is presented. Specifically, a detailed study of the first law of thermodynamics of the entire system is presented followed by a thorough analysis of the second law of thermodynamics of the complete system. Details of both discharge and charge cycles of the storage system are presented. The first and second law based efficiencies of the system are also presented along with parametric studies, which demonstrates the effects of various thermodynamic cycle variables on the total round-trip efficiency of compressed air energy storage systems.

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Energy storage systems: power grid and energy market use cases

Archives of Electrical Engineering ◽

10.1515/aee-2016-0036 ◽

2016 ◽

Vol 65 (3) ◽

pp. 495-511 ◽

Cited By ~ 14

Author(s):

Przemysław Komarnicki

Keyword(s):

Energy Storage ◽

Smart Grids ◽

Power Plants ◽

Storage Systems ◽

Power Grid ◽

Energy Storage Systems ◽

Large Growth ◽

Operating Strategies ◽

Pumped Storage ◽

Storage Technologies

Abstract Current power grid and market development, characterized by large growth of distributed energy sources in recent years, especially in Europa, are according energy storage systems an increasingly larger field of implementation. Existing storage technologies, e.g. pumped-storage power plants, have to be upgraded and extended by new but not yet commercially viable technologies (e.g. batteries or adiabatic compressed air energy storage) that meet expected demands. Optimal sizing of storage systems and technically and economically optimal operating strategies are the major challenges to the integration of such systems in the future smart grid. This paper surveys firstly the literature on the latest niche applications. Then, potential new use case and operating scenarios for energy storage systems in smart grids, which have been field tested, are presented and discussed and subsequently assessed technically and economically.

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