Operating Cost Analysis of Microgrid Including Renewable Energy Sources and a Battery Under Dynamic Pricing

This paper proposes a novel dynamic pricing scheme for demand response with individualized tariffs by consumption profile, aiming to benefit both customers and utility. The proposed method is based on the genetic algorithm, and a novel operator called mutagenic agent is proposed to improve algorithm performance. The demand response model is set by using price elasticity theory, and simulations are conducted based on elasticity, demand, and photovoltaic generation data from Brazil. Results are evaluated considering the integration effects of renewable energy sources and compared with other two pricing strategies currently adopted by Brazilian utilities: flat tariff and time-of-use tariff. Simulation results show the proposed dynamic tariff brings benefits to both utilities and consumers. It reduces the peak load and average cost of electricity and increases utility profit and load factor without the undesirable rebound effect.

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Cost Analysis of Electricity Generation from Different Sources

10.46610/joares.2021.v07i03.001 ◽

2021 ◽

Vol 7 (3) ◽

Author(s):

Al- Amin ◽

Al- Amin

Keyword(s):

Renewable Energy ◽

Cost Analysis ◽

Wind Energy ◽

Geothermal Energy ◽

Energy Supply ◽

Electricity Generation ◽

Renewable Energy Sources ◽

Energy Sources ◽

Total Cost ◽

Different Sources

This paper discusses and analyzes the economics for total cost investment to produce electricity from different sources like Geothermal Energy, Wind Energy, Hydro, Nuclear, Solar, etc. Renewable energy is the focus of this study since it is both affordable and a superior solution than non-renewable energy. The world's nonrenewable energy supply is running out, and prices are rising rapidly. As a result, the use of renewable energy sources is steadily growing. The total installed cost of different sources from 2007-2019 is driven clearly in this paper. An overall discussion on electricity generation is also included in this paper.

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Optimal Operation of Biomass Gasifier Based Hybrid Energy System

ISRN Renewable Energy ◽

10.5402/2011/395695 ◽

2011 ◽

Vol 2011 ◽

pp. 1-7 ◽

Cited By ~ 4

Author(s):

P. Balamurugan ◽

S. Kumaravel ◽

S. Ashok

Keyword(s):

Renewable Energy ◽

Optimal Allocation ◽

Renewable Energy Sources ◽

Operating Cost ◽

Energy System ◽

Optimal Operation ◽

Energy Sources ◽

Hybrid Energy System ◽

Hybrid Energy ◽

Typical Day

The focus of the world on renewable energy sources is growing rapidly due to its availability and environment friendliness. However, the renewable energy influenced by natural conditions is being intermittent, it is difficult to accomplish stable energy supply only by one kind of renewable energy source. In order to achieve reliability, it is necessary to integrate two or more energy sources together in an optimal way as hybrid energy system. Optimal allocation of sources, unpredictable load demand, intermittent behaviors of sources, and charging and discharging of storage devices are the major challenges in operating a hybrid energy system. A new controller algorithm is developed and implemented in controller hardware to overcome the above issues. The controller is incorporated in biomass gasifier-based hybrid energy system in a university campus at south India. A case study is carried out in real-time at the site for a typical day. From the experimentation, it is estimated that the annual savings in the operating cost are Rs 375,459.00 ($8475.4) for the optimal allocation of the sources by the controller.

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Dynamic pricing based on a cloud computing framework to support the integration of renewable energy sources

The Journal of Engineering ◽

10.1049/joe.2014.0239 ◽

2014 ◽

Vol 2014 (12) ◽

pp. 680-687

Author(s):

Rajeev Thankappan Nair ◽

Ashok Sankar

Keyword(s):

Cloud Computing ◽

Renewable Energy ◽

Dynamic Pricing ◽

Renewable Energy Sources ◽

Energy Sources ◽

Computing Framework

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Aplicación de Costos de Incertidumbre Analíticos de Energía Solar, Eólica y Vehículos Eléctricos en el Despacho Óptimo de Potencia

Ingeniería ◽

10.14483/23448393.11673 ◽

2017 ◽

Vol 22 (3) ◽

pp. 324 ◽

Cited By ~ 3

Author(s):

Juan Arévalo ◽

Fabian Santos ◽

Sergio Rivera

Keyword(s):

Renewable Energy ◽

Electric Vehicles ◽

Reactive Power ◽

Renewable Energy Sources ◽

Economic Dispatch ◽

Operating Cost ◽

Solar Irradiation ◽

Primary Sources ◽

Energy Sources ◽

Unit Commitment Problem

Context: Currently, renewable energy sources are playing an important role in counteracting the environmental impact of traditional energy sources. For this reason, system operators must have analytical tools that allow them to incorporate these new forms of energy. In electrical power systems, when incorporating renewable resources such as photovoltaic solar generation, wind power generation or electric vehicles, uncertainty is introduced due to the stochasticity of primary resources.Method: Uncertainty costs are proposed that incorporate the injected power variability of the main sources of renewable energy (solar and wind) and the consumed power (electric vehicles). Variability is considered by the probability distributions of the primary sources of renewable energy (solar irradiation and wind speed).Results: The main result of this research is the application of analytical costs of uncertainty. In this way it is possible to modify the cost function of a traditional economic dispatch. Additionally, it is proposed to solve the problem with a heuristic optimization method of economic dispatch of active-reactive power. Finally, a comparison is made with the operating cost of the system without the incorporation of renewable energies.Conclusions: The proposed model in this article is a potential decision-making tool that power system operators may consider in the operation of the system. The tool is capable of considering the uncertainties of the primary sources of renewable energy. The probability distribution of the primary source forecast is assumed to be known. An opportunity in order to extend the model is to study its applicability to dynamic time horizons, contemplating the constraints of the unit commitment problem

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Integrating the flexibility of the average Serbian consumer as a virtual storage option into the planning of energy systems

Thermal Science ◽

10.2298/tsci1403743b ◽

2014 ◽

Vol 18 (3) ◽

pp. 743-754 ◽

Cited By ~ 3

Author(s):

Ilija Batas-Bjelic ◽

Ivan Skokljev ◽

Tomislav Puksec ◽

Goran Krajacic ◽

Neven Duic

Keyword(s):

Renewable Energy ◽

Dynamic Pricing ◽

Cost Minimization ◽

Renewable Energy Sources ◽

Supply And Demand ◽

Energy Sources ◽

Virtual Storage ◽

Transmission Grid ◽

Variable Renewable Energy Sources ◽

Micro Grid

With the integration of more variable renewable energy, the need for storage is growing. Rather than utility scale storage, smart grid technology (not restricted, but mainly involving bidirectional communication between the supply and demand side and dynamic pricing) enables flexible consumption to be a virtual storage alternative for moderation of the production of variable renewable energy sources on the micro grid level. A study, motivated with energy loss allocation, electric demand and the legal framework that is characteristic for the average Serbian household, was performed using the HOMER software tool. The decision to shift or build deferrable load rather than sell on site generated energy from variable renewable energy sources to the grid was based on the consumer's net present cost minimization. Based on decreasing the grid sales hours of the micro grid system to the transmission grid from 3,498 to 2,009, it was shown that the demand response could be included in long-term planning of the virtual storage option. Demand responsive actions that could be interpreted as storage investment costs were quantified to 1?2 per year in this article.

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