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Purpose – This study aims to design and build a wireless supervisory control and data acquisition (SCADA) system based on Protocol AX.25 with the aim of monitoring the performance of several parameters in Microhydro Power Plant (MHPP). This system can monitor several MHPP parameters such as voltage, current, frequency, and turbine rotation so that it can be accessed directly at one central location.

Design/Methodology/Approach – The design is done by taking into account the real parameters that exist in the MHPP. Some parameters that become the main object to see the performance of MHPP are voltage, current, frequency, and turbine rotation. The voltage generated by the MHPP must be adjusted to the voltage supplied by State Electricity Company to the consumer, including the phase used. The resulting stream should also be monitored for power to be adjusted to the turbine spin. The generator frequency is kept stable according to the standard frequency of the State Electricity Company generator.

Findings – The remote terminal unit (RTU) system has been simulated using 2 ACS712 current sensors, voltage sensor, zero crossing point, frequency sensor, and rotation sensor functionalized to monitor MHPP parameters. The AX.25 protocol has been applicable in the wireless SCADA network for monitoring the performance of MHPP by embedding in KYL-1020UA transceiver radio using the 433 MHz frequency and the audio frequency shift keying modulation system. Radio transmitter KYL-1020UA has been successfully simulated to send data from sensors to display on the computer through SCADA built applications. The data changes in the RTU section can be displayed properly on the graphic user interface in accordance with the existing display at the MHPP location.

Research Limitations/Implications – There are only two RTUs that will be connected to communicate, in this case MHPP-1 with callsign “RTU-001” and MHPP-2 with callsign “RTU-002.” While the existing devices in the data access section parameters MHPP as master station with callsign “MSSCADA” monitoring the performance of parameters sent from the RTU. There is no collision or error in data transmission. Baudrate is varied at 1,200 bps, 2,400 bps, 4,800 bps, and 9,600 bps for effective throughput calculation and AX.25 protocol efficiency. The transmission distance is varied at 100 m, 200 m, 300 m, and 500 m to see the bit error rate with baudrate 1,200 bps and 9,600 bps.

Practical Implications – This product is expected to be applied to several MHPP locations in Aceh Province so that its monitoring system is more centralized and efficient.

Originality/Value – This research if for the efficient monitoring of several MHPP located far apart and can be monitored in one central location so that operators do not have to be located at the plant site.

The malfunction variables of power stations are related to the areas of weather, physical structure, control and load behaviour. To predict temporal power failure is difficult due to their unpredictable characteristics. As high accuracy is normally required, the estimation of failures of short-term temporal prediction is highly difficult. This study presents a method for converting stochastic behaviour into a stable pattern, which can subsequently be used in a short-term estimator. For this conversion, K-means clustering is employed, followed by Long-Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) algorithms are used to perform the Short-term estimation. The environment, the operation and the generated signal factors are all simulated using mathematical models. Weather parameters and load samples have been collected as part of a data set. Monte-Carlo simulation using MATLAB programming has been used to conduct experimental estimation of failures. The estimated failures of the experiment are then compared with the actual system temporal failures and found to be in good match. Therefore, for any future power grid, there is a testbed ready to estimate the future failures.

Purpose – We summarize three previous neuroeconomic studies with two features that distinguish them from most others in experimental economics: (1) the use of physical pain to induce incentives and (2) acquisition of data on brain activation levels. By correlating behavior when payoffs are painful with brain activation, we are able to test for the neurobiological relevance of important phenomena previously observed in experimental studies that are at odds with classical economic theories of decision-making. These specific phenomena are (a) negative discounting of future payoffs; (b) nonlinear probability weighting; (c) the experience of regret and rejoice when making a decision under risk.

Methodology/approach – The expectation of pain is created through the use of mild electric shocks to the top of the foot. Pain confers disutility, so decisions are made in the domain of losses relative to the status quo. Simultaneous with these decisions, brain activation data is acquired through functional magnetic resonance imaging (fMRI).

Findings – We find evidence for negative time discounting of electric shocks. Participants who exhibited the most extreme forms of this discounting were distinguished by early and robust activation of a subset of the cortical pain matrix. We also find evidence for probability weighting in the domain of electric shocks, which is manifest at the neural level. We find evidence both behaviorally and neurally for regret and rejoice functions for painful outcomes.

Originality/value of chapter – Previous experimental economic studies in the domain of losses have typically used monetary rewards. Here, we report behavioral effects and neural correlates using pain.

Research to find new energy source is still an intensive work by researchers in this field. One of the energy sources with no negative impact to environment is solar energy. Solar cell is used to convert solar energy to electrical energy. The electrically powered solar cell in direct current (DC) power is not suitable for our daily office equipment since they need the alternating current (AC) power. This research has succeeded in realizing a solar cell automation tool based on Arduino Uno with input from solar energy, from which output AC voltage can be used for the needs of household appliances and office equipments. Output power of this tool is approximately 700 W, which can turn on the lights, charge the hand phones, laptops, and so forth.

The platform economy reflects the business model of some of the largest and fastest-growing firms in the economy. Platform business models emerge and thrive because of the potential profit in taking advantage of transactions cost reductions to connect people for mutual benefit, and this value creation is best understood by thinking about the epistemology of decentralized market processes. Three essential aspects of knowledge are relevant to platform business models: (1) knowledge can be private and diffuse; (2) knowledge can be contextual; and (3) knowledge may not exist outside of the economic process. After defining and analyzing the technology, economic, and institutional aspects of platforms the author defines and applies market epistemology to explore how platforms harness technological and organizational features to create value-enhancing market platforms by exploiting the epistemic benefits of technology-enabled decentralized market processes. The author concludes by using this epistemic framework to propose an electricity distribution platform business model – the retail electricity industry is undergoing a process of technological dynamism, and as a regulated infrastructure industry, evolving into a decentralized market industry is presenting challenges to which this epistemic framework can bring increased understanding.

Do social movement organizations increase the supply of a public good? We address this question by investigating the role of generalist social movement organizations and technology-focused organizations for the development of the electric vehicle (EV) charging infrastructure in California from 1995 until 2012. We find that increases in the membership of Electric Auto Association (EAA) chapters in the cities of California enhanced the number of EV charging stations set up in each city. Our analyses also show that the organizational diversity of the environmental movement spurred the growth of EAA membership but did not directly increase the establishment of charging stations.

Purpose – The purpose of this study was to determine the efficacy value of national street lighting on energy conservation and carbon dioxide (CO₂) emission reduction.

Design/Methodology/Approach – The methods used are the measurement of electrical parameters (low voltage network), the national road illumination level with SON lamp specification, 400 W, 180 W, and 110 Lumen/W, the simulation of energy conservation calculation, and the CO₂ emission reduction obtained by utilizing panel solar cells as a source of energy and LED lights for illumination.

Finding – The results show the efficacy of a 100-W light bulb at an altitude of 8 m for the following specification of light bulbs: LED, 130 Lumens/W, SON, 110 Lumen/W, and MBF, 53 Lumen/W gives the illumination level respectively 13,913 Lux, 11,773 Lux, and 5,672 Lux. By replacing the 180 W SON lamp with an LED, 100 W, of energy conservation by 3.171 GW h is obtained, which is equivalent to a CO₂ emission reduction of 3.641 kTon CO₂.

Originality/Value – This study is a continuation of a study of energy conservation with the utilization of solar cells as an electrical power source for an LED bulb that replaces low-voltage networks as a power source for the bulb type SON.