Optimized Hybrid Wind-Diesel Energy System with Feasibility Analysis

Esmaeilnamazi

Technol Econ Smart Grids Sustain Energy

et al. 2019

Due to the growing use of Renewable Energy Sources (RES) in many countries, the need for an accurate and detailed analysis from the technical and economic view point seems to be necessary. Power Quality (PQ) can also be another considerable matter that needs to be carefully evaluated. In this regards, in this article, an analytical and detailed approach is presented to evaluate the technical and economic performance of the strategy for PQ changes. In addition, an optimization-based PQ change strategy is presented to provide a distinct PQ in integrated grids with renewable generations. The proposed strategy is based on the assessment of financial losses due to changes in the quality of power and the cost estimation of various reduction approaches and repayment solutions. This approach presents various customer requirements and various levels of PQ in the power grid. In order to evaluate the performance of the proposed method, the effectiveness of the presented model has been utilised in an actual case study, and the results have been obtained and analysed. The results of the simulation provide both technical and financial advantages to obtain optimal change strategy.

Section: Economic Assessment Of Mitigation Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Role of Renewable Energy Sources in Evaluating Technical and Economic Efficiency of Power Quality

Esmaeilnamazi

Technol Econ Smart Grids Sustain Energy

et al. 2019

Env Prog and Sustain Energy

“…where I is the current (A), t is the time (t) required in discharging, n Cons is the number of moles of methanol consumed in the system, and F is Faraday's constant (96,485 C). On the other hand, Faradaic efficiency can be calculated by the ratio of the number of electrons (n) released per methanol consumed (n cons ) to the theoretical value which is equal to 6 according to reactions (1)(2)(3).…”

Section: Analytical Proceduresmentioning

confidence: 99%

“…It is a must to prevent toxic emissions, greenhouse gasses, and other different harmful gases from the atmosphere. 1,2 Therefore, avoiding fossil originated fuels is a must thus, there is a need for sustainable, renewable energy generation solutions. There are studies on different energy production systems in literature.…”

Section: Introductionmentioning

confidence: 99%

Experimental evaluation of the efficiency performance of the DMFC

Ciğeroğlu

Kazan

2020

This study represents the experimental assessment of the faradaic, fuel, and energetic efficiency of active direct methanol fuel cell (DMFC). The experimental system was equipped with several sensors, HPLC and UV spectroscopy to make on-line and off-line measurements of different components. A polarization study was conducted and an experimental plan was applied to collect the process data during 3-hour runs. Finally, stoichiometric and various efficiency calculations were performed based on the system and the process data. The results showed that the cell performance was better at higher operating temperatures (70.8 mW cm −2 @75 C). Faradaic efficiency and fuel efficiency were better at low temperatures and estimated as 55.8% and 59.6% at 55 C, respectively. Energetic efficiency was better at higher temperatures due to the faster anode kinetics and was found as 12.3% at 75 C. The efficiencies were strongly dependent on methanol concentration. Methanol crossover was increased with increasing methanol concentration; hence the efficiencies were decreased.

“…The cost and utility modeling allows for studying transaction prices and quantities of buyers and sellers in markets, such as electricity and agriculture. Particularly, microeconomics models and concepts have immense possibilities for applications in the energy sector [6,7], particularly in the smart grids [8], which are characterized by the information flow, along with the electric energy, and thus allow for regulating and trading electricity in the smart grid network [9][10][11][12][13][14]. In the electricity market, the cost function is used to model the cost of generating, transmitting, and distributing the electricity to end-consumers [15].…”

Section: Introductionmentioning

confidence: 99%

Formalization of Cost and Utility in Microeconomics

et al. 2020

Cost and utility modeling of economics agents based on the differential theory is fundamental to the analysis of the microeconomics models. In particular, the first and second-order derivative tests are used to specify the desired properties of the cost and utility models. Traditionally, paper-and-pencil proof methods and computer-based tools are used to investigate the mathematical properties of these models. However, these techniques do not provide an accurate analysis due to their inability to exhaustively specify and verify the mathematical properties of the cost and utility models. Additionally, these techniques cannot accurately model and analyze pure continuous behaviors of the economic agents due to the utilization of computer arithmetic. On the other hand, an accurate analysis is direly needed in many safety and cost-critical microeconomics applications, such as agriculture and smart grids. To overcome the issues pertaining to the above-mentioned techniques, in this paper, we propose a theorem proving based methodology to formally analyze and specify the mathematical properties of functions used in microeconomics modeling. The proposed methodology is primarily based on a formalization of the derivative tests and root analysis of the polynomial functions, within the sound core of the HOL-Light theorem prover. We also provide a formalization of the first-order condition, which is used to analyze the maximum of the profit function in a higher-order-logic theorem prover. We then present the formal analysis of the utility, cost and first-order condition based on the polynomial functions. To illustrate the usefulness of proposed formalization, the proposed formalization is used to formally analyze and verify the quadratic cost and utility functions, which have been used in an optimal power flow problem and demand response (DR) program, respectively.