A dual mode wind turbine operation with hybrid energy storage system for electricity generation at constant voltage in an islanded microgrid

Self Cite

Summary A novel scheme of operating two mechanically driven energy storage, namely gravity energy storage system (GESS), alternatively using one wind turbine (WT) has been proposed in this article for uninterrupted energy generation in areas with limited or no grid connectivity. However, considering its lower land requirement and nature of uninterrupted energy supply, this system can also be easily implemented in grid connected scenarios. The proposed system consisting of a WT, two GESSs, one DC motor and one inverter, describe a simplified operation of alternatively charging of two GESSs, from a single WT, using two mode changer spring and suspended weight assemblies. Mechanical power of the WT has been directly utilized to charge GESSs, omitting the requirement of WT alternator, consequently lowering the maintenance requirement. This also results in decreasing the overall loss of renewable energy and completely eliminating the reactive power requirement of the WT. The output of the system is remains unaffected from regular or general wind speed variation, thus provides a stable energy output. Operation of the proposed system is quite different from existing WTs as in most of the cases electrical energy directly gets generated from WT. The main essence of this system is its simplicity, robustness and ability to generate uninterrupted electrical energy at stable voltage. It also does not require any electrochemical battery, thus offers low maintenance expenditure. This article documents the mathematical modelling of the proposed system and performance evaluation through simulation using real wind speed data.

“…The charging section of the proposed WT‐driven dual GESS is divided into several parts as shown in Figures 1 and 2: The WT (without WT generator and converter) and mechanical transmission (

η = 0.8

Section: The Wind Turbine Driven Dual Gravity Energy Storage System D...mentioning

confidence: 99%

“…The output

^{'} {P_{Trans}^{O}}^{'}

produced from the mechanical transmission system is limited by its efficiency

^{'} η_{Trans} = {0.8}^{'}

. This is mathematically expressed as 24

P_{Trans}^{O} = η_{Trans} P_{WT}^{Shaft} .

…”

Section: Mathematical Design Of Proposed Systemmentioning

confidence: 99%

Operation of two mechanically driven gravity energy storage systems using one wind turbine for uninterrupted energy supply in an isolated microgrid

Dhar

Chakraborty

2022

Self Cite

“…The electrochemical reactions of both the half cells are given below 28

Anode : {VO}_{2}^{+} + e^{-} + 2 {normalH}^{+} \begin{matrix} italicdch \\ ⇌ \\ italicch \end{matrix} {VO}^{2 +} + {normalH}_{2} O

Cathode : V^{2 +} \begin{matrix} italicdch \\ ⇌ \\ italicch \end{matrix} V^{3 +} + e^{-}

State‐of‐charge (SOC) is an important parameter for any battery. The SOC of VRFB can be calculated for any given interval using the following Equations 29

{italicSOC}_{italicdch}^{n} = {italicSOC}^{((), n goodbreak- 1)} - \frac{P_{italicVRFB}^{n} T}{η_{italicVRFB}^{italicdch} E_{italicVRFB}^{italicrated}}

{italicSOC}_{italicch}^{n} = {italicSOC}^{((), n goodbreak- 1)} - \frac{P_{italicVRFB}^{n} η_{italicVRFB}^{italicch} T}{E_{VRFB}^{rated}}

…”

Section: Mathematical Modeling Of Gpmb Solar Pv and Vrfbmentioning

confidence: 99%

“…Based on the load demand depicted in Tables 2–5, the hourly load demand of the building (UG + G + 38 floors with 6 flats in each floor) for summer and winter periods has been evaluated and shown in Figure 2. The load designed in this article also follows the Indian load pattern 29,30 …”

Section: System Load Descriptionmentioning

confidence: 99%

Solar PV driven hybrid gravity power module—Vanadium redox flow battery energy storage for an energy efficient multi‐storied building

Mondal

Mandal

Datta

2022

Summary This article presents an innovative perspective of using a gravity energy storage system namely gravity power module (GPM) around a multi‐storied building. Two number of GPMs have been vertically fixed around the walls of a multi‐storied building and have not been placed underground following the traditional way. The grid‐connected proposed hybrid system consisting of solar PV, GPMs and vanadium redox flow battery is focused to supply the maximum possible amount of an essential load of a high‐riser, through renewable energy. All of the storage systems are charged through solar PV. Whereas, the grid is used, to procure energy for the unmet load demand and sell the excess renewable energy. Results simulated for each month following seasonal load variation show that net energy supplied by the hybrid system is 99% of the full load demand of essential equipment of the building for the month of February and 90% to 91% for the month of January, November and December. During all the months, the supply of gravity energy storage is restricted to supply within the 18th to 24th hour to reduce the peak demand of the grid. The gravity energy storage is also considered as the primary storage system during those intervals. The yearly average of energy supply from the renewable resource in the proposed system toward the building load is found to be 47.77%. While considering the renewable energy sale toward the grid along the load supply of the building the yearly average of renewable energy penetration becomes 48.89%.

“…3 Today, a major portion of global energy demand is met by fossil fuels, 4 a reliance that has resulted in global warming and other environmental impacts across the world. 5 With the emergence of devastating effects of global warming in recent decades, the world has shown more interest in replacing fossil fuels with renewable energies wherever possible. 6 Climate change is the most important threat that humans is faced due to the widespread utilization of conventional energy resources, and sustainable energy sources are recommended by researchers to deal with climate change.…”

Section: Introductionmentioning

confidence: 99%

Determining the appropriate location for renewable hydrogen development using multi‐criteria decision‐making approaches

Almutairi

2021

Due to population growth and industrial development in the Kingdom of Saudi Arabia (KSA), energy demand has increased. On the other hand, the consumption of fossil fuels has led to adverse environmental effects. This has led to government investment in clean energy. In many sectors of this country, there is good potential for using wind energy. Production of hydrogen from wind farms is a method for reducing energy swings, and it may also be utilized as a fuel in Saudi Arabia's businesses. As a result, the purpose of this research is to discover the best location for hydrogen generation from wind energy utilizing Multi-Criteria Decision-Making (MCDM) techniques. The criteria were weighted using the Step-wise Weight Assessment Ratio Analysis (SWARA) approach. The most important criteria were determined to be "average wind speed," "number of refineries in the region," and "wind power density" with values of 0.2780, 0.2570, and 0.1570, sequentially. Then, the Weighted Aggregated Sum Product Assessment (WASPAS) approach was used to rank the locations. Finally, three other techniques, namely the Evaluation based on Distance from Average Solution (EDAS), the COmplex PRoportional ASsessment (COPRAS), and the Weighted Sum Model (WSM) were used to validate the results. Saudi Arabia's Eastern Province was recognized as the best position for hydrogen expansion in the country. The Eastern Province, with a rated capacity of 900 kW, was anticipated to produce 1863 MWh of energy and 30.16 tons of hydrogen every year. Highlights• Wind potential in Saudi Arabia was evaluated for hydrogen production.• Location planning was analyzed to rank locations.List of Symbols and Abbreviations: COPRAS, the complex proportional assessment; EDAS, the evaluation based on distance from average solution; MCDM, multi-criteria decision-making; SWARA, the stepwise weight assessment ratio analysis; WASPAS, the weighted aggregated sum product assessment; WPM, the weighted product model; WSM, the weighted sum model; c, scale parameter; C F , the capacity factor; E WT , the annual wind power generation; ec el , the power needed for electrolysis; f v ð Þ, the distribution function of Weibull probability; h 1 , height of measuring wind speed; h 2 , height of wind turbine tower; i, the alternatives for decision making problem; j, the criteria for decision making problem; k, shape parameter; M hydrogen , the amount of hydrogen production; q j , the local weight of criterion j; S j , the relative value of criterion j; w j , the final weight of criterion j; x ij , the performance of alternative i in terms of criterion j; x ij , the normalized performance of alternative i in terms of criterion j; v, average wind speed; v 1 , wind speed at the height of measurement (h 1 ); v 2 , wind speed at the height of measurement (h 2 ); v i , the cut-in speed; v r , the nominal speed; v 0 , the cut-out speed; WPS i , the generalized criterion of weighted aggregation of additive and multiplicative methods for alternative i; η conv , the rectifier performance; Γ, gamma funct...