Jun Yoshinaga

Voltage control of multiple step voltage regulators by renewing control parameters

This paper presents a novel method of determining the control parameters and a voltage control method for multiple step voltage regulators (SVRs) in a single feeder. The main feature of the proposed method is the updating of the control parameters at constant intervals to minimize the amount of voltage violations and the tap operation times of the SVRs while maximizing the voltage margin from the proper limits in the distribution system. To determine the SVR control parameters, a combined method of a greedy algorithm and a tabu search is used. To verify the proposed method, numerical and experimental simulation studies based on an actual distribution model with photovoltaic (PV) sources are carried out. The results show that the proposed control method can reduce the amount of voltage violations and tap operation times of the SVRs compared with the conventional voltage control method.

Upgrading the Voltage Control Method Based on the Photovoltaic Penetration Rate

In this paper, we propose a comprehensive scheme to determine a suitable method and timing for upgrading the voltage control method. Voltage control methods are expected to be upgraded in accordance with the photovoltaic (PV) penetration in distribution systems. The suitable method and timing detailed in this paper are based on the limit of the PV penetration rate, which is constrained by the regulated voltage deviation. The upgrade process involves moving the on-load tap changer (OLTC) control method from the conventional scalar line drop compensator (LDC) method to the vector LDC method or centralized control method. Then, a static var compensator (SVC) or step voltage regulator (SVR) is installed. The locations of the SVR and SVC are determined to maximize the PV penetration rate. The suitable method and timing are demonstrated using a general distribution system. In addition to the numerical simulations, experiments are performed using an active network system with energy resources. The experimental results are consistent with the numerical simulation results, thus validating the proposed scheme. The maximum PV penetration rate obtained using the OLTC control method is 55%. Whereas, the installation of the SVR and SVC increased the rate to 95% and 100%, respectively.

Method for Determining Line Drop Compensator Control Parameters of Low-Voltage Regulator Using Random Forest

Compensation of a voltage within the appropriate range becomes difficult when a large number of photovoltaic (PV) systems are installed. As a solution to this problem, the installation of a low-voltage regulator (LVR) has been studied. In this paper, we propose a method for instantly and accurately determining the line drop compensator (LDC) method parameters as a part of a voltage management scheme, which consists of prediction, operation, and control. In the proposed method, the solution candidates of the proper LDC parameters are narrowed by using a random forest that learns the relationship between the power-series data and the properness of the LDC parameters, thereby reducing the computational cost. We performed numerical simulations to verify the validity of the proposed method. From the results, the LDC parameters can be rapidly and accurately determined. Additionally, the desirable voltage control performance is verified.

Novel voltage control of multiple step voltage regulators in a distribution system

This paper presents a novel method for determining the control parameters and a voltage control method for multiple step voltage regulators (SVRs) in a single feeder. The main purpose of the proposed method is to reduce the amount of voltage violation and the tap operation times and to extend the voltage margin from the upper and lower voltage limits by updating the control parameters of the SVRs. To determine the control parameters of the SVRs, an improved greedy algorithm is used. In order to verify the proposed method, a numerical and experimental simulation study based on an actual distribution model is carried out. The results show that the proposed control method has the capability to reduce the amount of the voltage violation in a distribution system and the tap operation times of the SVRs.

Method for determining line drop compensator parameters of low voltage regulator using support vector machine

Highly accurate predictions of load demand and photovoltaic (PV) output have become possible in recent years because of improved measuring instruments and the increase of databases on load demand and PV output. The appropriate control parameters for actual power system operation can be determined by using these predictions. Although parameters determined by conventional methods are accurate, they may not be determined in time before the beginning of operation because extensive time is required for the calculations. In this paper, the support vector machine-a machine learning method that solves the two-class classification problem-is used to determine the line drop compensator (LDC) parameters instantly. To verify the validity of the proposed method, we carried out numerical simulations to determine the LDC parameters. From the simulated results, we found that the proposed method can instantly and accurately determine the LDC parameters.

Versatile Modeling Platform for Cooperative Energy Management Systems in Smart Cities

With growing attention to sustainability and recognition of the impact of global warming problems, energy supply and consumption have become critically important. This paper presents the construction of a modeling platform accommodating cooperative energy management systems (EMSs), which virtually produces the model of a smart city with a distribution network (DN) by using a wide range of data obtained from the real world. The platform involves models of various EMSs, governing the operation of a power system or controlling consumer-installed devices, and simulating the power flow, electrical losses, and voltage in the DN. In addition, indices measuring the sustainability of the model city, such as CO2 emission, are estimated from scenarios, for example, photovoltaic system installation, electric vehicle penetration, etc. The results can be visually displayed and the platform is highly versatile and applicable to various types of issues associated with smart cities. Two case studies are presented in detail.

Method for determining voltage control parameters of low-voltage regulator using forecast interval of photovoltaic output

A low-voltage regulator (LVR) is investigated as a countermeasure for voltage violation caused by the integration of photovoltaic (PV) systems in distribution systems. To achieve appropriate voltage control by the LVR, the appropriate control parameters need to be determined. We have proposed schemes to determine the appropriate control parameters using PV forecast profiles. In a previous work, the control parameters were determined on the basis of one-scenario PV forecast, which derives one forecast value in each time step. However, voltage violation could not be avoided by this method in a time step with a large forecast error. In this paper, we propose a method for determining the voltage control parameters of the LVR based on the forecast interval of the PV outputs to quantitatively consider the PV forecast error. The numerical simulation results show that the proposed method can reduce the amount of voltage deviation compared with the conventional method.

Coordinated voltage control of load tap changers in distribution networks with photovoltaic system

Maintaining voltage levels in distribution networks (DNs) with photovoltaic systems (PVs) is a complicated task for conventional voltage control schemes that only use a load ratio control transformer (LRT) and step voltage regulators (SVRs), because of local voltage fluctuation caused by the introduction of PVs. This paper proposes a coordinated voltage control scheme consisting of multiple kinds of load tap changers (LTCs). The proposed scheme determines the location at which to introduce low-voltage regulators (LVRs) and provides control parameters for the LTCs by considering the behavior of the other LTCs. We carried out numerical simulations using a DN model including PVs to verify the validity of the proposed scheme. The results specify the characteristics of the voltage deviation that cannot be prevented by a conventional voltage control scheme, and the proposed scheme significantly reduces such local voltage deviation.

Deployment of low-voltage regulator considering existing voltage control in medium-voltage distribution systems

Many photovoltaic (PV) systems have been installed in distribution systems. This installation complicates the maintenance of all voltages within the appropriate range in all low-voltage distributio...

Capacity determination of a battery energy storage system based on the control performance of load leveling and voltage control

AbstractThis paper proposes a method to determine the combined energy (kWh) and power (kW) capacity of a battery energy storage system and power conditioning system capacity (kVA) based on load leveling and voltage control performances. Through power flow calculations, a relationship between the capacity combination and the control performance is identified and evaluated. A tradeoff relationship between the capacity combination and control performance is confirmed, and the proper capacity combination for operation is determined based on the evaluated relationship. In addition, the control performance of the capacity combination is evaluated through the power flow calculation, confirming that the proposed method is effective for determining the optimized capacity combination.