Load Requirements Research Articles

Digital three-stage recursive-separable image processing filter with variable sizes of scanning multielement aperture

Objectives. The main aim of digital image processing is to increase clarity while maintaining image quality and eliminate noise. However, the amount of information contained in digital image files is growing year after year. This circumstance negatively affects processing time, critical for systems with high load requirements on the computing platform. In this regard, the use of digital filters which enable a reduction to the processing time of incoming data is important. In order to resolve this issue, adaptive filters with different sizes of multielement processing aperture are being developed to improve image clarity and preserve image details. Filters with adaptive properties are able to change their parameters during data processing, and provide maximum performance as the aperture size increases. The aim of the work is to develop a type of recursively separable digital filter with variable sizes of a scanning multielement aperture which allows the number of computational operations to be reduced while maintaining the efficiency of filtering input data (images).Methods. The work used recursive-separable methods and algorithms to construct digital filters.Results. An algorithm for the recursive-separable implementation of a digital filter is described, and the final view of the processing aperture and its three-dimensional appearance are presented. In order to evaluate the performance of the filter, a comparison of the developed algorithm with the classical two-dimensional convolution algorithm was carried out. The experiment was performed using images of various sizes and consisted of determining the time spent on the process of processing the test image. The study established that the processing time of a test image using the developed filter is on average 5 times less than the time taken by the classical two-dimensional convolution algorithm. The optimal coefficients for magnifying the central element and raising the positive part of the aperture of a digital filter were determined, enabling the efficiency of its use to be enabled.Conclusions. The studies show the effectiveness of using the developed recursive-separable two-dimensional filter to improve image clarity and reduce the time spent on processing.

A Bayesian-interference approach to quantify degradation parameters in a water-cooled variable speed screw compressor chiller

Abstract Variable-speed screw chillers can provide effective capacity modulations in commercial buildings to reduce energy consumption, match the load requirements, and contribute to lower equivalent carbon emissions. However, variable-speed operation can also yield to degradation phenomena inside the compressor. Assessing the real-time health status of chillers and detecting anomalies are important aspects to ensure long-term operation and improve reliability. To this end, an automated accelerated life test (ALT) procedure was developed and applied to a 513 kW (145.9 RT) water-cooled variable-speed screw chiller in a laboratory test facility to experimental assess performance degradation over time. After every 1,000 operating hours of ALT, steady-state performance tests at 30%, 50%, 75% and 100% load were conducted according to AHRI Standard 550/590. Additional operating conditions were included while conducting the tests to provide a more complete assessment of the degradation trends compared to the initially measured baseline. The experimental data set was then used to quantify the performance degradation based on the impact on the screw compressor operation. A Bayesian-inference identification approach has been developed to identify changes of sensitive parameters that statistically provide evidence for the likelihood of a performance degradation of the compressor. The information was used to implement the parameters in a dynamic model which was used to perform studies to predict the degradations of a chiller. The outcomes of this study help to improve the maintenance schedule of a compressor and even the whole chiller so that the system can be operated more economically and unplanned downtime can be minimized.

Stability Study of Single‐Layer Spherical Shell Roof Under Nonuniformly Distributed Snow Load

ABSTRACTAfter snowfall, the snow load distribution on building roofs is generally nonuniform, and most cases of large‐span structural collapse are related to nonuniform load. The existing regulations provide limited snow distribution coefficients for different roofs, and with the diversification of building forms, they can no longer meet the current calculation requirements for roof snow loads. This article conducts numerical simulations of wind‐induced snow drift on a spherical shell roof, which rise‐span ratio is 1/5. It is found that the friction velocity of the roof is distributed in a band shape and is higher in the windward direction, whereas the friction velocity on the leeward side is lower, which increases the possibility of snow accumulation. Based on this, a simplified snow load distribution model is proposed to improve the economic efficiency of the project. Based on the above research, the stability analysis of K6 single‐layer Kevitt mesh shell was carried out using ABAQUS finite element software. The results show that under uniformly distributed load conditions, the buckling modes of the structure are symmetrical, whereas under nonuniform snow load conditions, the first mode deforms more on the side with higher load, and the position of structural deformation is closer to the edge; when the snow cover range is the same, the larger the extreme snow load, the more unfavorable it is for structural stability; when the extreme snow load is the same, the smaller the snow coverage, the more unfavorable the initial defect is for structural stability.

Technical and economic simulation of a hybrid renewable energy power system design for industrial application

Countries in Africa rank the highest in low energy accessibility and air pollution globally. Presenting the urgent need to explore renewable energy sources to tackle the power challenge and reduce the carbon footprint for a greener atmosphere. A novel hybrid wind and solar renewable energy power system (HREPS) coupled to a battery that is capable of powering industrial appliances in the Basse district of The Gambia has been proposed. The HREPS size was estimated automatically with the PVsyst software taking into account the PV power and battery capacity based on the load profile and loss of load probability, with all the necessary meteorological, technical, and economic factors. The optimal size was possible with 20 photovoltaic modules (250 W) and 1 Wind generator (1 KW) compatible with the annual load requirement of about 2555 MWh. These results suggested that the HREPS is reliable for the user’s load demand in all the tested meteorological conditions of the study area. When the HREPS is linked to any other renewable source, it shows the potential of gaining about 8395 kWh annually in the battery. The continuous operation of the hybrid system for 21 years presents a net gain of > 400% for the standalone systems with a projected gain of > 600% when linked to a small smart grid system. Since high taxes may scuttle these gains, it is recommended that the Government encourage investment in renewable energy power systems by subsidizing the taxes on the purchase of items to make them more affordable.

A Single-Input Multi-Output Inverter with Voltage Boosting for Multi-Load Wireless Power Transfer Systems

Multi-load wireless power transfer systems generally require the configuration of multiple transmitting coils. Using traditional single-output inverters will increase the number of inverters, leading to increased system costs and complex structures. Therefore, this paper proposes a single-input multi-output inverter that can drive multiple transmitting coils simultaneously. Compared with traditional single-output inverters and existing multi-output inverters, the proposed inverter utilizes a topology improvement design and an efficient expansion method. By adding only one inductor, one capacitor, and a small number of power switches, it can generate multiple controllable and stable outputs while ensuring output gain, which is expected to simplify the system structure and improve system performance. This paper first introduces the topology evolution process and operating principle of the proposed inverter. Secondly, a mathematical model is established to analyze its operating characteristics, and its parameter design is carried out. Meanwhile, a comparison with existing multi-output inverters is conducted. Then, the resonant compensation networks are analyzed and selected to match the requirements of different loads. Finally, a simulation model of the proposed inverter is constructed, and an experimental setup is set up. The feasibility and superiority of the proposed inverter are verified through simulation and experiments.

Power Quality Improvement for Hybrid Microgrid Integrated with Renewable Energy Sources

Given the present energy crisis and depletion of fossil fuel reserves, there is a pressing need to enhance the integration of Renewable Energy Sources (RES) into the power system. This research focuses on designing and managing a Hybrid Microgrid (HMG) in fluctuating RES. The Direct Current (DC) sub-grid comprises a Wind Turbine (WT), a solar Photovoltaic (PV) array equipped with a Perturb-and-Observation (P&O) Maximum Power Point Tracking (MPPT) method, a boost conversion, and a Battery Energy Storage System (B-ESS) connected to DC demands. The Alternative Current (AC) sub-grid comprises a Permanent Magnet Synchronous Generator (PMSG) WT and a Fuel Cell (FC) integrated with an inverter circuit synced with the grid to fulfill its load requirements. A reversible Interlinking Conversion (IC) connects the AC and DC sub-grid, enabling efficient power interchange across the two grids. The IC's control technique allows it to function as an active energy filter and exchange operator. The IC's active energy filtering function ensures that the power supply of the microgrid complies with the criteria set by IEEE 519. It does this by offering reactive power assistance and decreasing the harmonic levels to below 5%. The suggested method enables the HMG to function in grid-connected and islanded states. During grid-connected operation, power is transferred across the DC and AC sub-grids, ensuring that all load requirements are fulfilled. In the islanded method, a diesel generator provides power to the AC sub-grid to fulfill the needs of essential loads, while the B-ESS sustains the DC microgrid. The suggested model is constructed and simulated with MATLAB, and its outcomes are examined.

Sustainable Energy Solutions for Rural Electrification (A Comprehensive Study of Microgrid and Distributed Generation Systems)

Providing power to the people of Afghanistan is a major problem, especially in rural areas where access is severely restricted. Relying on the National Grid is not viable because 75% of people live in these regions and just 9% of people have access to energy. A Micro-Grid system is suggested in this paper as a practical and affordable way to provide rural villages with electricity. The Sayyidabad area of Wardak province's Khwaja Kotgay acts as a case study for assessing the technical feasibility of this Micro-Grid. In addition to having access to local resources, such as biogas produced from the waste of 150 cattle, the region enjoys 220 to 250 sunny days per year. Each day, about 50 cubic meters of biogas are produced. Biogas and solar energy will work together to generate electricity at night. A carefully planned network, consisting of three sections, will distribute the electricity generated to homes. The components of each segment will be determined by the load requirements of each family. The goal of this initiative is to provide dependable and sustainable electricity to rural areas, thus empowering them. At the end of the research, the researchers will present useful results and important recommendations.

Ensembled snake optimiser to solve multiobjective mixed energy generation scheduling

This paper presents Ensembled Snake Optimiser (ESO), to optimise the scheduling of mixed energy generation from coordinated thermal, hydro, pumped-storage hydro, and solar units. It tackles operational constraints while minimising non-convex and non-linear objectives. To reduce the pollutants emitted and operating cost of thermal and solar units, the mixed energy generation scheduling problem uses committed hydro, thermal, and solar units to generate power, pumped-storage hydro units to maintain water levels, and hydro units to maximise available water volume. Utilising the water volume and actively exceeding the power-generating limit are the primary obstacles to satisfy the load requirement. The heuristics are utilised to satisfy the load demand and water volume constraints. The binary-optimistic approach commits solar units. The snake optimisation algorithm tends to get trapped in the local minima while solving complex engineering optimisation problems, which leads to sluggish convergence behaviour. A local search, simplex search, and extended opposition-based learning are investigated to improve its exploitation aspect, convergence behaviour, and procure good solutions. Three electric power systems are undertaken for the simulation studies. ESO gives better results. The significant cost savings for integrated energy scheduling are ranging from 10–15%. The rapid convergence behaviour and whisker box plots justify ESO’s robustness.

Reliability assessment of distribution networks with distributed generation considering different types of user loads

Abstract This paper meticulously evaluates the reliability of distribution networks integrated with distributed generation (DG), considering various user classifications. Initially, we delve into the daily load profiles of residential, commercial, and industrial sectors, establishing a nuanced time-series load model that encapsulates the distinct characteristics of these customer segments. Subsequently, we formulate a model for the harmonious operation of energy storage systems, tailored to the interplay between DG output and load requirements. Utilizing the sequential Monte Carlo simulation algorithm, we compute the reliability metrics for the IEEE RBTSBUS6 feeder system, revealing that DG integration significantly enhances distribution network reliability. Notably, identical DG output yields varied impacts on the reliability of distinct customer sectors, underscoring the need for tailored strategies in DG deployment.

The combustion biased dual cross-limited control strategy for industrial boiler furnaces

Abstract The combustion process in boilers is a crucial aspect of industrial boiler operation, and the quality of this process is closely related to the industrial boiler’s operational efficiency and pollutant emissions. This paper focuses on furnace combustion control within the industrial boiler control system and proposes an improved variable bias control method to address the issues associated with over-oxygen and oxygen-deficient combustion, which are prevalent in current double-closed-loop cascade proportional control technologies. First, the working principle of the variable bias double cross-limit combustion process is analyzed, and the variable bias cross-limit combustion control system is designed. Second, by introducing a bias variable, the paper addresses the problem that fixed bias parameters in the double cross-limit control system cannot accommodate the variable loading and rapid response requirements. Finally, the range of bias coefficients is estimated using the trial-and-error method. Experimental results demonstrate that the variable bias double cross-limit control strategy resolves the issues of oxygen deficiency and over-oxygen combustion, along with the slow response speed of conventional combustion control modes, enhances fuel heat utilization efficiency, and reduces pollutant and harmful gas emissions.

Feasibility and optimal sizing analysis of hybrid PV/Wind powered seawater desalination system: A case study of four ports, Egypt

This research aims to investigate A novel and complete system consists of hybrid renewable energy farm with high-energy-consuming seawater desalination in fourth locations in Egypt. This paper proposes fuzzy-based multi-criteria decision-making model for optimal sizing of a hybrid PV/Wind/Storage system to power the reverse osmosis (RO) desalination process in order to increase freshwater availability and meet the electric load requirement in selected area. Firstly, according to collected data and cost of electricity (COE) for various renewable energy resources, specific procedures to determining the optimal system design and optimal sizing (solar cell, wind turbine parameter and storage system units) are presented for selected site. The optimization based on finding the minimum net present cost (NPC) feeds the load demand and maintains the system's reliability. Secondly, the fuzzy analytic hierarchy process (FAHP) is implemented to select the optimal system considering ten performance criteria. The results show that the feasible design consists of 16 × 100-kWwind turbines, 4127-kW photovoltaic array, 153 PH245 storages and 710-kW converter. The feasible design has the optimal economic values among all criteria with least NPC, COE, and payback-period (PBP) of $9,08,046, 0.091$/kWh and 1.1 yr, respectively. Besides, it has a 100 % renewable energy system (RES).In contrast to recent studies that concentrated on incorporating renewable energy sources into desalination systems at specific Egyptian location. This approach is applied to different case studies with diverse renewable energy resources in multiple locations across Egypt, thus providing valuable insights for decision-makers tackling electricity and water shortages throughout Egypt. This research fills a gap in the optimization of hybrid renewable energy systems (HRES) by taking into account a variety of sustainability criteria, including technological feasibility, cost-effectiveness, emissions reduction, and socio-political considerations, in contrast to other studies that concentrated on single aims. Additionally, the research presents fuzzy logic and fuzzy-AHP and fuzzy-VIKOR decision-making techniques, enabling a comprehensive assessment of system design alternatives while taking uncertainties into consideration. In general, this study makes a significant addition to the field of renewable energy integration and gives decision-makers a framework for choosing the best answers to Egypt's water and electricity problems.

Artificial Neural Network-Based Hybrid Controller for Electric Vehicle Applications

Power management among different energy sources of electric vehicles (EV) is one of the complex issues during the transition from one to another. A specific control is modeled based on the current and speed range of the electric motor named as Measurement of Parameter-Based Controller (MPBC), which will play a key role during transition of energy sources as per the load requirement. Two bidirectional converters are utilized to control the pulse signals generated by the traditional controllers which are connected at the battery and Supercapacitors (SCap) ends, which are treated as passive sources of the system. The Controller's artificial neural network (ANN), fuzzy logic (FLC), and proportional-integral (PI) are utilized to generate the pulse signal to the switches present in the converters by load. Further, specific controller MPBC is combined with three controllers ANN/FLC/PI individually and obtained three separate hybrid controllers as per the proposed control technique. The MPBC+PI/FLC/ANN controller-based MATLAB/Simulink model was designed, and applied to the electric motor individually at different load conditions. This model considered three different power delivery states from the PV array and assessed the motor's performance under different load scenarios. Compare the three hybrid controllers' final results to find out which one is more effective than the others.

Power Quality Enrichment and Power Management using an Adaptive Control Scheme in Microgrid System

This article proposes an ANFIS-based control scheme for improved power quality and power management that will provide optimal and sustainable energy in a grid-connected renewable energy system. The system consists of a wind energy conversion system (WECS), a photo voltaic system (PVS), and a battery energy storage system (BESS). To increase the PVS's and WECS output powers, a unique control approach is suggested in this paper. The adaptive Neuro-Fuzzy Inference System (ANFIS) controller is incorporated into the proposed controller to generate three-phase reference current signals for harmonic elimination in the system during system dynamic conditions. The proposed control technique can work under voltage quality problems such as voltage sag, voltage swell, neutral currents, and reactive power. Renewable energy sources (PV and Wind) are interfaced to improve the DC-link overall performance by minimizing short-term and long-term voltage problems. The proposed controller regulates the energy flows between the renewable energy sources to the end users with a unity power factor. A supervisory control scheme is implemented for optimal power management in the system. Based on the load requirement, and how the renewable, battery, and grid sources are sharing the power, a detailed analysis is given in the paper. Simulation results from the MATLAB/Simulink platform under several test conditions at the grid side and load side illustrate the efficacy of the proposed control mechanisms in the environment of power optimization and energy management. The comparative analysis is performed to show the efficacy of the proposed system. Finally, the proposed system is validated and the THD content of the grid currents is found good.

Simulation of Hybrid PV Solar System with Fuel Cell in MATLAB Simulink

This paper discusses the simulation of a fuel cell hybrid solar photovoltaic system in MATLAB Simulink. To achieve the stated objective, it is proposed to dynamically model a hybrid system using Simulink to analyze its performance and optimize its operation, improving the efficiency and stability of the power supply under different operating conditions, then the dynamic simulation model employs energy conversion equations of the solar PV panel and the fuel cell to meet the electrical load requirements, where the solar panel uses solar radiation and ambient temperature, while the fuel cell produces electricity by electrolysis of water, which separates hydrogen from oxygen. In the first graph, the power at load increases sharply at 0.5 seconds and stabilizes between 0.5 and 1.5 seconds, with a sharp drop at 1.6 seconds. In the second graph, PV power increases at 0.5 seconds, reaching 80 kW between 0.5 and 1.5 seconds, dropping to zero at 1.6 seconds. The fuel cell shows similar behavior. These results indicate a coordinated operation for a stable power supply to the load, responding efficiently to changes in demand and generation.

Renewable Energy-Based Electric Drive with a Novel Control Technique for Smooth Power-Sharing

Energy management between different power sources, which are used to feed Electric vehicles (EVs) is one of the complex scenarios. Normally, power management is done based on the Electric vehicle load requirements. In this work, three different energy sources are considered, in that one is an active energy source and two are passive energy storage elements. The Photo Voltaic (PV) based energy source is considered an active element, on the other hand, the Battery sand supercapacitor (SCap) is treated as a passive type of element. To manage the power flow between two energy sources, a novel control technique is adopted by considering the speed and current of the electric motor as major input parameters known as the Measurement of the parameter-based controller (MPBC). The Measurement of a parameter-based controller is used to control the pulse signals of the Bidirectional converters connected at the battery and supercapacitor ends, and the required pulse signals can be generated by the Conventional Proportional Integral (PI) controller. The main circuit is implemented with a novel hybrid controller which is used to provide controlled pulse signals to the bidirectional converters connected to the battery and supercapacitor. Finally, the MATLAB/Simulink model was developed with the novel hybrid controller and examined the performance at different load conditions of the motor by considering three different states of power delivered by the PV array.

Electric delivery vehicle routing problem optimization model with time-varying traffic congestion

In order to plan a reasonable scheme for the fleet travel and minimize the energy consumption of electric vehicles during traffic congestion periods, while relieving the mileage anxiety of delivery personnel, the pure electric delivery vehicle routing problem considering time-varying traffic congestion was studied. Firstly , a novel mixed integer programming model (TD-EVRP) is established to step for its extended model of EVRP, which especially characterizes the time-varying traffic congestion state and measures the energy consumption of electric delivery vehicles. This model also refines its constraints including customer time window, vehicle load, and vehicle charging requirements. Secondly, a traffic congestion avoidance strategy is introduced into the model, which allows vehicles to park and charge at customer points during peak traffic periods in order to actively avoid unnecessary energy consumption caused by traffic congestion. Finally, the improved ant colony algorithm is designed to acquire the optimal solution.

Bi-Level Operation Optimization and Performance Analysis for a Distributed Energy System with Energy Network

The increasing energy crisis and environmental problems promote the development of distributed energy systems (DESs) that utilize combined heat and power technology, renewable energy technology, and waste heat recovery technology to meet various load requirements. Although there is existing work and research on a variety of DESs, most previous studies tend to focus on energy production with little consideration of a distributed energy network and its energy loss, which results in large errors in energy-efficiency calculations and performance analyses. In this paper, a new DES model is proposed with full consideration of an energy network and the full use of solar energy, terrestrial heat, and exhaust gases. At the same time, an effective bi-level optimization method is also proposed for the daily operation of the DES in order to improve the system performance and benefits in the energy, the economy, and the environment. Specifically, the co-generation energy station and water heating network in the DES are optimized separately with two different optimization models. The first-level optimization model is used to seek the optimal values of water mass flow rate and water temperature of the water heating network, and the second-level optimization model is built to determine the optimal energy purchasing strategy and the optimal energy outputs of the co-generation energy station. In order to verify the advantages and effectiveness of the proposed system and method, a contrastive simulation study is undertaken to provide a comparison of the global optimization method. Simulation results show that energy loss, energy cost, and energy consumption of the DES using the bi-level optimization operation strategy only account for 22.51%, 33.42%, and 51.31% of the quantities of the global optimization method, respectively. The hourly curves of the optimal operating variables also demonstrate that the proposed bi-level optimization method can improve the operating stability of the DES better than the global optimization method.

Blast resistance of CFRP composite strengthened masonry arch bridge under close-range explosion

Carbon fiber reinforced polymers (CFRP) are recognized for their exceptional strength-to-weight ratio. They offer a viable and effective solution for strengthening and retrofitting masonry bridges, helping to extend their service life, improve structural performance, and meet modern safety and load requirements. Wrapping of CFRP around masonry elements can enhance their confinement and ductility. This flexibility plays a crucial role in preventing sudden brittle failure, allowing for controlled deformation, which is essential for blast resistance. Additionally, CFRP materials possess the ability to flex and absorb energy, which proves beneficial in containing and redistributing forces generated during an explosion, consequently reducing the risk of catastrophic failure. This study employed the coupled Eulerian–Lagrangian (CEL) technique available in the finite element software Abaqus/Explicit to simulate the blast loads. Various detonation scenarios were considered, taking into account factors such as location and their impacts on bridge structures. A detailed micro-model was developed using finite element software and accurate geometric data acquired from FARO laser scanning of the case study. The properties of masonry units and backfill were characterized using the Johnson-Holmquist II damage model and Mohr–Coulomb criteria. The Jones-Wilkins-Lee equation of state (EOS) was applied to replicate the behavior of trinitrotoluene (TNT). In accordance with the JH-II model, the researchers formulated a VUMAT code. The study examined the distinct damage mechanisms and overall structural responses of bridges. By evaluating the blast resistance of individual bridge models, the most critical scenarios were pinpointed. Carbon Fiber Reinforced Polymer (CFRP) was then utilized as a method to fortify bridges against blast loads. A comparison was made between the damage propagation before and after the reinforcement.

Virtual energy dispatching method for hybrid microgrid demand response based on Lyapunov optimization

Abstract The hybrid microgrid (HMG) possesses power generation, storage, and distribution capabilities, serving as an integrated foundational structure for advanced localized distribution networks. However, due to significant discrepancies in load demands and energy consumption among different users, the photovoltaic (PV) generation output and end-user load requirements exhibit unpredictability, resulting in relatively low self-sufficiency ratio (SSR) and self-consumption ratio (SCR) of the HMG PV system. To address this issue, this study proposes a virtual energy dispatching method for hybrid microgrid demand response based on Lyapunov optimization. Initially, a bidirectional virtual energy dispatching system model based on energy provider/buyer classification is constructed, optimizing load demands and energy management of both the load side and the main utility grid (MUG) while considering demand response. Subsequently, a Lyapunov optimization-based bidirectional virtual energy dispatching algorithm (LOBVED) is introduced, optimizing queueing systems in stochastic networks based on drift-plus-penalty technique to resolve the dynamic interactions among stability, performance, and energy self-sufficiency in the HMG environment, aiming to maximize the PV SSR and SCR of the HMG while ensuring the reliability of battery energy storage (BES) energy queues. Finally, the effectiveness of the proposed method is validated through MATLAB simulations.

ANALISIS POTENSI PEMBANGKIT LISTRIK TENAGA ANGIN DI TAMAN TEKNOLOGI TOWER TURYAPADA

Tower Turyapada is a technology concept tourism center with various attractions located in Pegayaman Hill, Singaraja and is programmed to meet Building Green Building (BGH) criteria. One component of the BGH assessment is the use of renewable energy. The use of renewable energy that is suitable to be utilized in this tower building is PLTB (Wind Power Plant), because it is located in a hilly area with strong winds. The potential of wind power plant has been analyzed using descriptive method through quantitative approach. Analysis of wind energy potential using primary data by taking direct measurements in the Turyapada Tower area in February - March and using secondary data from the I Gusti Ngurah Rai Meteorological Station, Badung Regency. The analysis results show the average value of wind speed in the Tower Turyapada area in February - March amounted to 3.55 m / s and 4.58 m / s. The wind turbine specification uses TSD-500. Wind turbine specifications use TSD-500 because it can generate electricity at low wind speeds and uses 10 units of turbines. The results of the analysis obtained electrical energy of 2,159 kWh / year. The electrical load requirement of the Pedestal Building as the main building of the Turyapada Tower Technology Park is 7,787,000 kWh / year, so it cannot meet the electrical load of the Pedestal Building because it only supplies power by 0.00028%. This research was conducted to find out how much wind energy can produce electrical energy with wind energy conditions in the Turyapada Tower Area.