Sürdürülebilir Kalkınma Amaçları

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• MakaleYalnız künye2020/r/gumushane/14847
  A novel billing approach for fair and effective demand side management: Appliance level billing (AppLeBill)

  Çakmak, Recep; Altaş, İsmail Hakkı

  Demand side management (DSM) is an important part of smart electrical grid studies due to high energy efficiency it provides. Effective DSM techniques are hinged on participation level of the customers and control manner of their loads so if there is no fair and appropriate management, customers will not embrace demand side management applications. Besides, the customers might not participate to the demand response process willingly if their comforts are not considered. Therefore, the DSM systems must consider fairness and customer's comfort as well as distribution system objectives. Multifarious DSM systems have been proposed in the literature, however, the fair billing has not included as a parameter in most of these studies. This paper introduces a novel billing approach based upon appliance level billing (AppLeBill) for fair and effective demand side management. The proposed AppLeBill idea offers a billing strategy such that time-shiftable appliances (TSAs) in a residence may have a separate billing rate rather than a single billing rate for total electricity usage. The proposed AppLeBill concept includes three different schemes which are explained and simulated in order to compare each other in terms of their potential benefits.

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• BildiriYalnız künye2020/r/gumushane/14693
  A fuzzy decision maker to determine optimal starting time of shiftable loads in the smart grids

  Altaş, Ismail Hakkı; Çakmak, Recep

  Smart grid studies have been increased tremendously for past ten years in order to modernise and solve problems of current electrical grids. One of the aim of the smart grids is to react autonomously to the problems in electrical networks by means of artificial intelligence and decision maker. Fuzzy logic-based embedded control systems simulate human thoughts and decision making processes. So, fuzzy logic and fuzzy decision makers can be utilised in smart grids for automated system management. In this paper, a fuzzy decision maker has been proposed to manage time-shiftable loads in residences. The proposed fuzzy decision maker determines optimal starting time of time-shiftable loads in residential areas in order to provide balanced power curve and decrease peak load consumptions by scheduling the loads. Design stage of the proposed fuzzy decision maker have been introduced and presented clearly. Finally, a design example has been given to show the decision results.

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• BildiriYalnız künye2019/r/gumushane/13277
  Design of a MATLAB GUI for Day Ahead Forecasting of PV Panel Power

  Bektas, Sibel Cevik; Cakmak, Recep; Altas, Ismail H.

  This paper introduces design and utilization of a MATLAB graphical user interface (GUI) platform to forecast day ahead hourly Photovoltaic (PV) panel power by using forecasted day ahead global horizontal solar radiation. This platform, which would be a useful and practical tool for researchers who are study on energy management, planning and forecasting studies, consists of three parts. The first part predicts day ahead global horizontal solar radiation by trained artificial neural network (ANN) model. The second part performs the calculation of solar irradiation on the module, which has a tilted angle according to forecasting solar radiation data. The last part estimates the power generated by PV panel according to the calculated incident radiation. In this study, the solar irradiation forecasting, the calculation of incident radiation to tilted module and prediction of the solar power to be generated by the PV module are done. The designed GUI has been utilized to forecast solar radiation and PV output power for test days. Then obtained forecasted data have been evaluated with mean absolute percentage error (MAPE) and correlation coefficient (R).

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• BildiriYalnız künye2018/r/gumushane/16199
  Hourly Solar Irradiation Prediction by Artificial Neural Network Based on Similarity Analysis of Time Series

  Ulutas, Ahsen; Çakmak, Recep; Altas, Ismail Hakki

  Solar energy is a renewable energy source which has intermittent and variable characteristic. Solar irradiation must be predicted in advance in an electrical grid which has solar energy based electrical power generation systems in order to operate the electrical grid stable and efficient. In this study, a multi-layered, feed forward artificial neural network (ANN) has been designed to predict the hourly solar irradiation of next day. The designed ANN has been trained by data which has been obtained via similarity analysis. Total solar irradiation on horizontal plane, relative humidity and temperature data of Trabzon province for 2015-2017 have been used as the training data set. Hourly solar irradiation prediction has been performed by utilizing the designed ANN and test data set. The prediction results have been evaluated as to root mean square (RMS), mean absolute error (MAE) and mean absolute percentage error (MAPE) performance criteria. The obtained performance criteria results show that the proposed ANN could make prediction with acceptable error.

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• BildiriYalnız künye2018/r/gumushane/15096
  Optimal scheduling of time shiftable loads in a task scheduling based demand response program by symbiotic organisms search algorithm

  Cakmak, R.; Altas, I.H.

  Demand side management is one of the key issues in smart electrical grid studies. Power demand of consumers can be managed via demand response(DR) programs. Task scheduling (TS) based demand response is one of the DR schemes. Objective of the TS approach is to schedule activation time of the appropriate time-shiftable loads to reduce power consumption in peak-demand hours. Heuristic optimization methods can be used to provide this objective. Symbiotic Organisms Search (SOS) and Cuckoo Search (CS) algorithms are two of the most recent heuristic methods. In this paper, scheduling of the time-shiftable home appliances executed by SOS and CS algorithms. Time-shiftable home appliances of the consumers and run time tolerances of them aggregated by mini public survey to achieve results which close to reality. Obtained results are indicated the superiority of the SOS algorithm and demonstrated the positive effects of the demand side management on the electrical grid.

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• BildiriYalnız künye2017/r/gumushane/15002
  A day ahead hourly solar radiation forecasting by artificial neural networks: A case study for Trabzon province; [Yapay Sinir Aǧlari ile Gün Öncesi Saatlik Güneş Radyasyonu Tahmini: Trabzon İli Örneǧi]

  Çevik, Sibel; Çakmak, Recep; Altaş, Ismail Hakki

  The integration of renewable energy sources to the electrical grid leads to some issues in the grid because of intermittent and variable characteristics of renewable energy sources such as wind and solar. It has been predicted that the solar based electricity production will has highest annual increase rate among the other renewable sources. Due to the intermittent and volatile nature of the solar energy in an electricity grid where photovoltaic systems are intensive, load planning is essential. Therefore, day ahead solar radiation forecasting will contribute to the load planning studies. Artificial neural networks are one of the methods that are applied frequently and successfully in forecasting studies. In this study, a cause effect based artificial neural network (ANN) has been designed and performed for day ahead hourly solar radiation forecasting in Trabzon province. A similar day selection algorithm has been utilized to get more accurate forecasting by the ANN. The designed ANN has been trained and tested in MATLAB simulation environment without using ready codes of MATLAB ANN toolbox. The obtained results reveal that the designed ANN forecasts the solar radiation with acceptable error for a place such as Trabzon which has rainy and cloudy weather conditions.

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• BildiriYalnız künye2016/r/gumushane/14991
  Scheduling of domestic shiftable loads via Cuckoo search optimization algorithm

  Cakmak, Recep; Altas, Ismail H.

  Electrical power systems have been developed to more advanced structures called as smart grids. Among many other issues, demand side management (DSM) is one of the important instruments of the smart grids. DSM techniques increase the efficiency of the grid, and modify consumer's electrical demand via demand response (DR) programs using financial incentives. In this study, shiftable domestic loads scheduled by Cuckoo search algorithm (CSA) to ensure balanced load curve as much as possible while considering the consumers' preferences. The main motivation of this paper is scheduling the usage hours of the shiftable household appliances in a neighborhood by applying the recently developed metaheuristic CSA. This paper proposes an approach to increase the efficiency and lifetime of utility network by scheduling and operating shiftable domestic loads while considering consumer's demand in terms of financial benefits. Proposed CSA based scheduling mechanism is compared with that of Genetic algorithm (GA). The results reveal positive effects of the scheduling and the performance of the CSA over GA.

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• BildiriYalnız künye2013/r/gumushane/13114
  The effect of integration types on FLC based MPPT systems

  Cakmak, Recep; Altas, Ismail H.

  Operating the photovoltaic (PV) array at its maximum power available is important to increase system efficiency. In order to operate PV systems at their maximum power point, many maximum power point tracking (MPPT) methods have been proposed. Fuzzy logic controller (FLC) based MPPT methods have some advantages over classical MPPT methods. The way of using the FLC outputs has an effective role in obtaining the desired results. In this study, the effect of a discrete-time integration method investigated in MPPT including FLC whose output is subjected to integration operation. The system has been designed and simulated in MATLAB/Simulink software. The results were given as a comparison.

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• BildiriYalnız künye2012/r/gumushane/12026
  Modeling of FLC-incremental based MPPT using DC-DC boost converter for standalone PV system

  Cakmak, Recep; Altas, Ismail H.; Sharaf, Adel M.

  This paper presents the modeling of a Fuzzy Logic Controller-Incremental (FLC-Inc.) based maximum power point tracking (MPPT) method and its comparison with traditional Perturb and Observation (P&O) method for standalone photovoltaic (PV) systems. The PV system, which is composed of PV panels, boost converter, MPPT unit and dc load, is modeled and digitally simulated in MATLAB/Simulink. The simulated results are illustrated to show the improvements obtained by the proposed FLC-Inc. based MPPT method.

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