Electricity is needed by the whole society. Sasnek village is one of the villages located in Sawiat District, South Sorong Regency, West Papua Province. Sasnek village is very clear and inhabited around 100KK. This village has not been served by electricity until now.  Micro-hydro power plants are small-scale power plants whose capacity presents between 100 W to 100 kW. This study will be used for loading stages with a 12 Volt DC power capacity, because it is one of the most efficient, young and safe ways. Measurement of air discharge, discharged by 2 liters / second from a measurement area of 5 m2 and an average air speed of 00.65 m / d.  However, due to the condition of the river water flowing throughout the year in the sense of never dried, then used a correction factor of 0.75. Thus the flow that can be used is equal to 0.65 m3 / d. Based on the analysis of the potential contained in Sasnek PLTMH, it can be calculated Distribution Grid sourced from Sasnek PLTMH is 10 KW.With the careful planning so that the results of its implementation will give a positive impact to be meeting the needs of electricity in the village and surrounding villages sasnek.

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Study of PLTMH development planning in sasnek village sawiat district, South Sorong Regency West Papua Province

• Business intelligence (BI) capabilities/reliability affect performance capabilities. • Artificial intelligence (AI) has an impact on Data mining systems (DMS). • Integration of BI Infrastructure (BII) affects the Supply chain management. • Performance evaluation capabilities has an impact on competitive advantage. • BI capabilities are related to BI reliability. Thus, BII impresses BI reliability. Improving organizational performance is a priority for the managers and experts of companies. Performance appraisal capabilities are activities that use available information to improve business processes and achieve company goals. Knowledge information entered into companies, on the one hand, is effective in learning people and, on the other hand, is used in management decisions. This study aims to improve these organizational performances by using Business intelligence (BI) and Artificial intelligence (AI) on Data mining systems (DMS) in privately held companies. This descriptive survey study is based on the purpose of applied and quantitative research. The statistical population includes managers of privately held companies. These companies use BI and AI in their data mining systems. The results revealed that BI capabilities & reliability affect performance capabilities. Further, Performance evaluation capabilities (PEC) impact competitive advantage; Since the BI capabilities are related to BI reliability, thus, Business intelligence infrastructure (BII) impresses BI reliability. Path coefficient between the two variables of integration of BII on BI capabilities is β = 0.389. Moreover, the T-statistic between these two variables is t = 5.768. Path coefficient between the two variables of BI capabilities over reliability business intelligence is β = 0.158. Moreover, the T-statistic between these two variables is t = 1.967. Path coefficient between the two variables of Integrate BII with business intelligence reliability is β = 0.344. Moreover, the T-statistic between these two variables is t = 4.452. Innovation has a significant impact on the company's performance by creating an improved market position, which indicates a competitive advantage and superior performance. 

Business intelligence ability to enhance organizational performance and performance evaluation capabilities by improving data mining systems for competitive advantage

Available transfer capability is an index to measure the security and economic viability of an interconnected system. However, to accurately determine this index, other associated parameters need to be accurately evaluated. One of these parameters is the capacity benefit margin (CBM). For efficient power generation reliability and sustainability, a certain amount of supply capacity is commonly reserved by utilities, which in most cases remain unused, to reduce the effect of generation outage. To minimize this unused reserve, utilities usually reserve a predetermined amount of tie-line capacity between interconnected areas to have access to external supply. This tie-line reserved for this purpose is termed as capacity benefit margin (CBM). In this paper a technique for computing CBM is used, the sensitivity of CBM support from other areas to the increase in load in one of the areas is investigated, and conclusively, demand side management is proposed to improve the quantification of CBM. The contribution of this work is the assessment of the CBMs support from other areas during a critical condition, using the flexibility of DSM technique. The modified 24-bus IEEE reliability test system is employed for the verification of the approach.

https://journal.portalgaruda.org/index.php/EEI/article/download/1909/1368

A systematic approach to evaluating the influence of demand side management resources on the interarea capacity benefit margin

Renewable energy sources (RES) such as wind turbines (WT) and solar cells have attracted the attention of power system operators and users alike, thanks to their lack of environmental pollution, independence of fossil fuels, and meager marginal costs. With the introduction of RES, challenges have faced the unit commitment (UC) problem as a traditional power system optimization problem aiming to minimize total costs by optimally determining units’ inputs and outputs, and specifying the optimal generation of each unit. The output power of RES such as WT and solar cells depends on natural factors such as wind speed and solar irradiation that are riddled with uncertainty. As a result, the UC problem in the presence of RES faces uncertainties. The grid consumed load is not always equal to and is randomly different from the predicted values, which also contributes to uncertainty in solving the aforementioned problem. The current study proposes a novel two-stage optimization model with load and wind farm power generation uncertainties for the security-constrained UC to overcome this problem. The new model is adopted to solve the wind-generated power uncertainty, and energy storage systems (ESSs) are included in the problem for further management. The problem is written as an uncertain optimization model which are the stochastic nature with security-constrains which included undispatchable power resources and storage units. To solve the UC programming model, a hybrid honey bee mating and bacterial foraging algorithm is employed to reduce problem complexity and achieve optimal results. 

/pdf/optimal-intelligence-planning-of-wind-power-plants-and-power-1tqz542t.pdf

Optimal Intelligence Planning of Wind Power Plants and Power System Storage Devices in Power Station Unit Commitment Based

Nowadays, designing a framework for an environmentally-friendly waste collection network is of higher importance due to population growth. This study presents a multi-depot green capacitated location routing problem (MGCLRP) considering the time window and in-facility queuing under uncertainty. A scenario-based robust optimization is employed to deal with demand and travelling time uncertainties. Moreover, the M/M/c queuing system calculates the expected total wait time at a recycling center. As a solution method, we develop an algorithm to find the optimal number of potential locations and use this optimal number to find the main objectives of the problem. Then, two versions of NSGA-III, enhanced by greedy initializations, are proposed to solve the large-scale instances. The obtained results show the superiority of the proposed NSGA-III over the simple version of this algorithm. Finally, we investigate the applicability of the given model in a practical case study for Tehran. 

Multi-Depot Green Capacitated Location Routing Problem Considering Uncertainty and In-Facility Queuing

A zonal optimization solution to reliability security constraint unit commitment with wind uncertainty

In electric power systems, the generated power should be equal with the demand and power of network is mainly controlled through generation system. In such operation, the demand is satisfied through changing the generated power and afterward, the safe operation of power system is reached. But during recent years, a new concept has been developed in electric power systems namely demand side management (DSM). DSM is the modification of consumer demand for energy through various methods such as financial incentives and education. Usually, the goal of demand side management is to encourage the consumer to use less energy during peak hours, or to move the time of energy use to off-peak times such as nighttime and weekends. One of the important models of DSM is interruptible loads. Interruptible loads are the right for an electricity utility to interrupt supply to a customer, typically during a system emergency, to relieve short term network constraints up to a couple of hours. Interruptible loads can be deployed in one of two ways. The network operator gives notice of an interruptible load event to the customer, then relies on the customer to reduce their electricity usage; or unilaterally interrupts supply to the customer. In this paper, the effect of interruptible loads on the power system reliability is investigated. A multi machine power system is considered as cases study. Simulation results show the great effects of interruptible loads on the power system reliability.

Habib Daryabad

Papers

A zonal optimization solution to reliability security constraint unit commitment with wind uncertainty

Investigating the Effect of Demand Side Management on the Power System Reliability