scholarly journals Simulation of distributed energy storage in the residential sector and potential integration of gas based renewable energy technologies using Modelica

2015 ◽  
Author(s):  
Praseeth Prabhakaran ◽  
Wolfgang Koeppel ◽  
Frank Graf
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Distributed Energy ◽  
Renewable Energy Technologies ◽  
Residential Sector ◽  
Energy Technologies ◽  
Distributed Energy Storage ◽  
Potential Integration

scholarly journals Investigation of behavior of BESS with PV using MATLAB/Simulink

2021 ◽  
Vol 9 (10) ◽  
pp. 1726-1730
Author(s):  
Yash Gupta
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Storage System ◽  
Energy Storage System ◽  
Solar Photovoltaic ◽  
Distributed Energy ◽  
Distributed Energy Storage ◽  
Wide Range ◽  
Renewable Energy Generation ◽  
Distribution Grids

Abstract: As renewable energy penetration rises, integrating it will become a major issue that will necessitate new generating support infrastructure; an energy storage system is one answer to this problem. Battery technologies, in particular, have a wide range of energy and power output capabilities, making them perfect for integration. In many regions where renewable energy generation systems will be implemented, distributed energy storage on distribution grids may be required. When the sun is not shining or the weather is cloudy, an energy storage system is required for solar photovoltaic systems. For PV applications, a battery is used as an energy storage system. Keywords: Energy storage system, Battery, Simulink and modelling.

Distributed Energy Storage Control for Optimal Adoption of Solar Energy in Residential Networks

2012 ◽  
Author(s):  
Reza Arghandeh ◽  
Robert Broadwater
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Real Time ◽  
Storage Systems ◽  
Energy Resources ◽  
Solar Irradiation ◽  
Renewable Energy Resources ◽  
Distributed Energy ◽  
Energy Storage Systems ◽  
Distributed Energy Storage

Environmental concerns, global warming and fossil fuel prices are creating a shift in the expectations of consumers and industries to move toward renewable energy resources. However, the inability to control the output of renewable resources, like wind and solar, results in operational challenges in power systems. The operational challenges of renewable resources can be met by energy storage systems. The energy storage systems scheduling can be used to control the effect of intermittent renewable energy resources. Furthermore, energy storage systems can be used for ancillary services, peak reduction, and mitigating contingencies in the distribution and transmission networks [1]. Distributed photovoltaic (DPV) rooftop panels are considered as renewable energy resources in this paper. Depending on the DPV size and solar irradiation, DPV adoption can create problems for the distribution network. In addition, utility companies have to pay different prices for electricity during different times of the day due to the dynamic electricity market. Therefore, the DPV adoption can be controlled with the help of real-time electricity price and the load profile. Facing these challenges, this paper presents an operational optimization algorithm for a Distributed Energy Storage (DES) system. The DES system presents a fleet of batteries connected to distribution transformers. The DES can be used for withholding DPV power before it is bid into the market. Withholding DPV generation represents a gaming method to realize higher revenues due to the time varying cost of electricity. Energy storage systems may be used to control DPV power variation and thus help distribution network operations [2]. The objective of this paper is to present a DES optimal economic control system to improve the DPV adoption in power distribution networks. The control system decisions depend on the load profiles, and the real-time Locational Marginal Price (LMP). Economic operation of the DES is a complex problem because of the time dependency of the battery capacity (where sufficient energy reserves must be maintained in case of power loss), the solar irradiation uncertainty, and the real-time electricity price variability. The mathematical approach used is the Discrete Ascent Optimal Programming (DAOP) algorithm. An advantage of DAOP is its assurance of convergence after a finite number of computational iterations.

Concept and Application of Distributed Compressed Air Energy Storage Systems Integrated in Utility Networks

2013 ◽  
Author(s):  
Miroslav P. Petrov ◽  
Reza Arghandeh ◽  
Robert Broadwater
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Compressed Air ◽  
Small Scale ◽  
Compressed Air Energy Storage ◽  
Distributed Energy ◽  
Local Networks ◽  
Distributed Energy Storage

Distributed energy storage has been recognized as a valuable and often indispensable complement to small-scale power generation based on renewable energy sources. Small-scale energy storage positioned at the demand side would open the possibility for enhanced predictability of power output and easier integration of small-scale intermittent generators into functioning electricity markets, as well as offering inherent peak shaving abilities for mitigating contingencies and blackouts, for reducing transmission losses in local networks, profit optimization and generally allowing tighter utility control on renewable energy generation. Distributed energy storage at affordable costs and of low environmental footprint is a necessary prerequisite for the wider deployment of renewable energy and its deeper penetration into local networks. Thermodynamic energy storage in the form of compressed air is an alternative to electrochemical energy storage in batteries and has been evaluated in various studies and tested commercially on a large scale. Distributed compressed air energy storage (DCAES) systems in combination with renewable energy generators installed at residential homes, public or commercial buildings are a viable alternative to large-scale energy storage, moreover promising lower specific investment than batteries if a mass-market is established. Flexible control methods can be applied to DCAES units, resulting in a complex system running either independently for home power supply, or as a unified and centrally controlled utility-scale energy storage entity. This study aims at conceptualizing the plausible distributed compressed-air energy storage units, examining the feasibility for their practical implementation and analyzing their behavior, as well as devising the possible control strategies for optimal utilization of grid-integrated renewable energy sources at small scales. Results show that overall energy storage efficiency of around 70% can be achieved with comparatively simple solutions, offering less technical challenges and lower specific costs than comparable electrical battery systems. Furthermore, smart load management for improving the dispatchability can bring additional benefits by profit optimization and decrease the payback time substantially.

Modeling of a Low Cost Thermal Energy Storage System to Enhance Generation From Small Hydropower Systems

2017 ◽  
Author(s):  
Peggy P. Ip ◽  
Sammy Houssainy ◽  
H. Pirouz Kavehpour
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Storage Systems ◽  
Low Cost ◽  
Storage System ◽  
Energy Storage System ◽  
Energy Costs ◽  
Distributed Energy ◽  
Small Hydropower ◽  
Distributed Energy Storage

Undeveloped small hydropower generation sites are abundant throughout the water conveyance infrastructure and natural rivers in the United States. Due to its small scale, micro-hydro development requires substantial upfront capital costs, maintenance and operation costs for customized engineering and construction. The significant investments required for developing small hydropower are inhibiting for utilities, residential and commercial users to adopt. An inexpensive energy storage system and a well-designed power controls system can be integrated with small hydropower sites to increase its cost-effectiveness and reliability. This paper introduces the concept of storing low-power generated from small hydro turbines during long off-peak periods and dispatching at high-power as grid-quality electricity during peak periods. The use of an ultra-low cost thermal energy storage (ULCTES) system is examined. Boosting the power output for small hydro generation allows commercial users to avoid significant demand charges during operation, making small hydro an attractive cost saving strategy and therefore breaking down the cost barrier. The ULCTES operates much like a bulk power production unit and a peaker plant, in which it is capable of dispatching constant power over a long period during peak periods when conventional sources are unavailable. Improvements in system reliability and economic value are evaluated using microgrid optimization software HOMER Energy. In particular, two cases are studied with variations in types of end users and energy management goals. Energy costs savings, demand charges savings and renewable energy penetration are determined. Distributed energy storage systems are shown to reduce energy costs and increase the renewable energy penetration for commercial users. With ULCTES, microgrids have the flexibility to manage fluctuating renewable energy generation as well as respond to rapidly changing loads on a daily basis. A larger hydroelectricity system is shown to be more feasible with distributed energy storage systems for isolated users without any connection to the grid.

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