• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2377-2398
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• 2021

In the recent modernized world, utilization of natural resources (renewable & non-renewable) is increasing drastically due to the sophisticated life style of the people. The over-consumption of non-renewable resources causes pollution which leads to global warming. Consequently, government agencies have been taking several initiatives to control the over-consumption of non-renewable natural resources and encourage the production of renewable energy resources. In this regard, we introduce an IoT powered integrated framework called as green home architecture (GHA) for green score calculation based on the usage of natural resources for household purpose. Green score is a credit point (i.e.,10 pts) of a family which can be calculated once in a month based on the utilization of energy, production of renewable energy and pollution caused. The green score can be improved by reducing the consumption of energy, generation of renewable energy and preventing the pollution. The main objective of GHA is to monitor the day-to-day usage of resources and calculate the green score using the proposed green score algorithm. This algorithm gives positive credits for economic consumption of resources and production of renewable energy and also it gives negative credits for pollution caused. Here, we recommend a green score based tax calculation system which gives tax exemption based on the green score value. This direct beneficiary model will appreciate and encourage the citizens to consume fewer natural resources and prevent pollution. Rather than simply giving subsidy, this proposed system allows monitoring the subsidy scheme periodically and encourages the proper working system with tax exemption rewards. Also, our GHA will be used to monitor all the household appliances, vehicles, wind mills, electricity meter, water re-treatment plant, pollution level to read the consumption/production in appropriate units by using the suitable sensors. These values will be stored in mass storage platform like cloud for the calculation of green score and also employed for billing purpose by the government agencies. This integrated platform can replace the manual billing and directly benefits the government.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2146-2156
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• 2017

When a failure occurs in active distribution system, it will be isolated through the action of circuit breakers and sectionalizing switches. As a result, the network might be divided into several connected components, in which distributed generations could supply power for customers. Aimed at decreasing customer interruption cost, this paper proposes a theoretically optimal island partition model for such connected components, and a simplified but more practical model is also derived. The model aims to calculate a dynamic island partition schedule during the failure recovery time period, instead of a static islanding status. Fluctuation and stochastic characteristics of the renewable distributed generations and loads are considered, and the interruption cost functions of the loads are fitted. To solve the optimization model, a heuristic search algorithm based on the hill climbing method is proposed. The effectiveness of the proposed model and algorithm is evaluated by comparing with an existing static island partitioning model and intelligent algorithms, respectively.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.12
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• pp.638-644
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• 2017

Optimal cooling operation algorithm was developed based on a simulation case of a single family house model equipped with renewable energy facility. EnergyPlus simulation results were used as virtual test data. The model contained three energy storage elements: thermal heat capacity of the living room, chilled water storage tank, and battery. Their charging and discharging schedules were optimized so that daily electricity bill became minimal. As an optimization tool, linear programming was considered because it was possible to obtain results in real time. For its adoption, EnergyPlus-based house model had to be linearly approximated. Results of this study revealed that dynamic cooling load of the living room could be approximated by a linear RC model. Scheduling based on the linear programming was then compared to that by a nonlinear optimization algorithm which was made using GenOpt developed by a national lab in USA. They showed quite similar performances. Therefore, linear programming can be a practical solution to optimal operation scheduling if linear dynamic models are tuned to simulate their real equivalents with reasonable accuracy.

• Journal of Power Electronics
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• v.15 no.1
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• pp.202-215
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• 2015

This paper investigates the stability and performance of model predictive controlled active-front-end (AFE) rectifiers for energy storage systems, which has been increasingly applied in power distribution sectors and in renewable energy sources to ensure an uninterruptable power supply. The model predictive control (MPC) algorithm utilizes the discrete behavior of power converters to determine appropriate switching states by defining a cost function. The stability of the MPC algorithm is analyzed with the discrete z-domain response and the nonlinear simulation model. The results confirms that the control method of the active-front-end (AFE) rectifier is stable, and that is operates with an infinite gain margin and a very fast dynamic response. Moreover, the performance of the MPC controlled AFE rectifier is verified with a 3.0 kW experimental system. This shows that the MPC controlled AFE rectifier operates with a unity power factor, an acceptable THD (4.0 %) level for the input current and a very low DC voltage ripple. Finally, an efficiency comparison is performed between the MPC and the VOC-based PWM controllers for AFE rectifiers. This comparison demonstrates the effectiveness of the MPC controller.

• Korean Chemical Engineering Research
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• v.56 no.6
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• pp.804-810
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• 2018

Most biofuel companies are in a small scale with short experience of operating the entire supply chain. In order to compete with existing fossil fuel competitors, renewable companies should be more responsive to demand. It is financially important to reflect this in the decision supporting system of the company. This paper addresses an evolutionary algorithm based methodology for the distribution problem of renewable energies. A numerical example was presented to illustrate the applicability of the proposed methodology with some remarks.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.8
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• pp.556-561
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• 2011

In this study, the theoretical maximum power of a heat engine was investigated by sequential Carnot cycle model, for a low-grade heat source of about $100^{\circ}C$. In contrast to conventional approaches, the pattern search algorithm was employed to optimize the two design variables to maximize power. Variations of the maximum power and the optimum values of design variables were investigated for a wide range of UA(overall heat transfer conductance) change. The results show that maximizing heat source utilization does not always maximize power.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1053_1054
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• 2009

A significant number of renewable energy systems have been connected to the grids as supplement power source. The renewable energy systems require control algorithm to maintain the power-supply reliability and quality. This paper proposes a novel control algorithm for smart Power Conditioning System (PCS) with harmonics and reactive power compensation. The smart PCS is used to feed Photovoltaic (PV) power to utility and compensate harmonics and reactive power at the same time. The experimentation is carried out on the proposed grid-connected PV generation system, and controlled by digital signal processor. The grid-connected PV generation system injects PV energy into the grid and performs as Active Filter (AF) and Static Synchronous Compensator (STATCOM) without additional devices. The experiment results show that the proposed control algorithm is effective for smart PCS with harmonics and reactive power compensation.

• New & Renewable Energy
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• v.8 no.3
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• pp.14-22
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• 2012

Performance of photovoltaic (PV) generator systems relies on its operating conditions. Maximum power extracted from PV generators depends strongly on solar irradiation, load impedance, and ambient temperature. A most maximum power point tracking (MPPT) algorithm is based on a perturb and observe method and an incremental conductance method. It is well known the latter is better in terms of dynamics and tracking characteristics under condition of rapidly changing solar irradiation. However, in case of digital implementation, the latter has some error for determining a maximum power point. This paper presents a PID based MPPT algorithm for such PV systems. We use neural network technique for determining PID parameters by online learning approach. And we construct a boost converter to regulate the output voltage from PV generator system. Computer simulation is carried out to evaluate the proposed MPPT method and we accomplish comparative study with a perturb and observe based MPPT method to prove its superiority.

• Proceedings of the KIPE Conference
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• 2011.07a
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• pp.32-33
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• 2011

This paper is about to the efficiency improvement of inverter for renewable energy. It is proposed the structure enhanced quality by using individually DC/DC converter for MPPT and only one inverter for DC/AC and the grid control algorithm for current control mode to the converter and inverter. The grid control algorithm is possible to setting the current reference to the dependent function of DC distribution voltage.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.60 no.3
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• pp.133-137
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• 2011

The purpose of smart grid is the low $CO_2$ through expansion of renewable energy. To achieve the purpose of smart grid, typical radial power distribution system will be changed to loop power distribution system. The loop power distribution system have many advantages such as low power loss, low voltage drop, and increase of connection of renewable energy. In this paper, the algorithm for minimization of interrupted section of power distribution system is proposed through communication between circuit breaker and recloser in loop power distribution system. The proposed algorithm is proved through case studies about reliability evaluation