1,720,968 research outputs found
Generation expansion planning for high-potential hydropower resources: The case of the Sulawesi electricity system
Full text linkTo ensure sustainable development, the generation expansion planning (GEP) should meet the electricity demands in the specify time horizon. The GEP will determine the type and capacity of generator units to meet with the minimum cost, required reserve margin and energy balance. In this paper, a GEP to minimize the cost by considering the high penetration hydro energy potential was carried out in Sulawesi electricity region. GEP optimization is done by finding the minimum total cost value that is done through WASP-IV. There were two approaches for conducting the optimization that are regional balanced and resources-based approaches. The effect of renewable energy plant, especially the hydro energy, can be seen through a resource-based scenario, where the generating units were priories installed close to the energy source location. On the other hand, the regional balanced approach would install the generating units close to the load center. This paper compared the results of regional balance to the resource-based scenarios. The results show that resource-based approach can achieve a renewable energy power plant mix of up to 30%. The regional balance scenario total costs were 13.57 billion in high projection electricity demand. On the other hand, the resource-based scenario total costs were 13.38 billion high projection electricity demand
Simulasi Optimal Power Flow Sistem Kelistrikan PT. PLN (Persero) P3BS UPB Sumatera Bagian Utara
No full textMultistage preventive scheme for improving voltage stability and security in an integrated renewable energy system
No full textPiezoelectric Energy Harvester for IoT Sensor Devices
Full text linkLimited battery power is a major challenge for wireless sensor network (WSN) in internet of things (IoT) applications, especially in hard-to-reach places that require periodic battery replacement. The energy harvesting application is intended as an alternative to maintain network lifetime by utilizing environmental energy. The proposed method utilized piezoelectricity to convert vibration or pressure energy into electrical energy through a modular piezoelectric energy harvesting design used to supply energy to sensor nodes in WSN. The module design consisted of several piezoelectric elements, of which each had a different character in generating energy. A bridge diode was connected to each element to reduce the feedback effect of other elements when pressure was exerted. The energy produced by the piezoelectric is an impulse so that the capacitor was used to quickly store the energy. The proposed module produced 7.436 μJ for each step and 297.4 μJ of total energy with pressure of a 45 kg load 40 times with specific experiments installed under each step. The energy could supply WSN nodes in IoT application with a simple energy harvesting system. This paper presents a procedure for measuring the energy harvested from a commonly available piezoelectric buzzer. The specific configurations of the piezoelectric and the experiment setups will be explained. Therefore, the output energy characteristics will be understood. In the end, the potentially harvested energy can be estimated. Therefore, the configuration of IoT WSN could be planned
Transient Stability Assessment Considering Number and Location of PMUs Using CNN-LSTM
No full textElectric power systems in the future will increasingly adopt wide area monitoring systems (WAMS) based on phasor measurement units (PMUs). Conventional methods are not able to utilize the data effectively and efficiently. This research focuses on utilizing PMU data measurement for transient stability detection using convolutional neural network and long short-term memory (CNN-LSTM) by considering the number and location of PMUs. This research aims to detect stable and unstable transient stability based on bus voltage magnitude and angle data. The CNN-LSTM architecture consists of several layers, including the time-distributed layer, two-dimensional convolution layer, batch normalization layer, dropout layer, max-pooling layer, flatten layer, LSTM layer, and dense layer. The case study used in this research is a modified IEEE 39 bus with a PV system. The proposed method produces an accuracy above 99.5% in normal and distorted data quality for all test scenarios. In addition, the results of this study show a trend that the more PMUs used, the better the detection performance, and PMU locations that pay attention to observability and dynamic stability have better detection performance
A Review of Stochastic Hosting Capacity Problems Concerning High Photovoltaic Penetration
No full textThe number of requests for integrating customer-scale photovoltaic systems on distribution grids has increased over the last few years. Consequently, this scenario
expands the role of the electrical distribution planners. The operators of a traditional electrical distribution system are responsible for predicting the amount of electricity used. Forecasting the power generation of the linked photovoltaic systems is also necessary due to the significant increase in photovoltaic penetration. In relation to the uncertainty characteristics of the photovoltaic size and placement, this new role presents a considerable challenge to the electrical distribution planners. Therefore, this paper provides a review of the position of previous studies in solving problems that
have been formulated through the development of the hosting
capacity determination method. A detailed discussion and a
summary of existing approaches are also provided. Therefore,
it can be used by electrical distribution planners to find
appropriate approaches to deal with the high penetration of
photovoltaic and systems
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