Search

The enforcement of a feed‐in tariff (FIT) program in Japan has increased the number of installations of photovoltaic generation systems in its residential sector. After the end of an FIT program, the surplus electricity of an individual prosumer is purchased by the utility company at a reduced price, which may have an economic impact on the prosumer. To avoid this adverse effect, peer‐to‐peer (P2P) electricity transactions among prosumers based on blockchain and smart contract technologies as well as introduction of residence‐use stationary storage batteries are generating significant interest. In this study, the potential economic merit of P2P transactions and residential storage battery introduction are evaluated using a total optimization approach. For realizing a more practical perspective, this study also investigates the economic merit based on a partial optimization approach, in which an individual prosumer pursues its own profit. Furthermore, in this study, the grid‐side merit of P2P electricity transactions among prosumers is examined. Comparison of the merits determined by the total and partial optimization approaches shows that the realization of P2P transactions could provide a notable economic merit to the participants and reduce both the required facility capacity and power flow variation. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Network reconfiguration results in voltage deviations because of the time-varying nature of loads. Nowadays, with the integration of renewable energy sources with the power grid, the optimal configuration should be determined taking into account the variations in loads and distributed generations. In this study, a long-term reconfiguration method named the long-term extended flow algorithm, which improves the timeliness of configuration behavior on time-varying loads, is proposed to substitute for the previous short-term ones. Moreover, optimal reconfiguration instants are achieved by a novel approach of optimal daily schedule called accumulation of unbalanced load distribution based on the trade-off between switching operations costs and reduction in voltage deviations. The proposed methods were tested by case studies of two test distribution systems under real-time measured data with the interconnection of photovoltaic generators in the MATLAB environment. By applying the proposed methods, the total operating cost of the network is reduced significantly within reasonable computation time, and its efficiency is also improved compared to fixed configuration, online reconfiguration policies, and daily schedule proposed by previous authors. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The supervisory control and data acquisition (SCADA) system is used in power systems worldwide because of its maturity and capability. However, the SCADA system is vulnerable to fast system changes. Wide area monitoring system (WAMS) based on phasor measurement units (PMUs), which requires high investment, is being thought of as one of the solutions in recent power systems. This paper proposes a procedure to upgrade SCADA into WAMS by installing sufficient numbers of additional PMUs without removing conventional measurements from the existing SCADA system. The WAMS hybrid configuration is focused on the optimal PMU placement and state estimation strategy for hybrid PMU-SCADA measurements. The optimal placement of PMUs is subject to the improvement in estimation accuracy. For guaranteeing secure operation, line contingencies and some important buses are considered as subproblems of PMU placement. The state estimation procedure manages the initial state variable and modifies the weighting factor strategy that is suitable for the hybrid system especially during fast system changes. The results show that the proposed WAMS hybrid guarantees better estimation accuracy and faster state estimation process than SCADA in both non-contingency and contingency conditions. In addition, the WAMS hybrid has the capability to perform preventive strategy for securing voltage stability, which was previously applied in the PMU-based WAMS system. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The interconnection of distributed generators (DGs) in a power system increases the difficulty of managing the system. The minimization of the voltage deviation by network reconfiguration is an important requirement for dealing with the issue. We had previously developed a reconfiguration technique, named the intelligent flow algorithm (IFA), for determining the optimum or suboptimum network configuration within a short computation time. In the present paper, we propose an extension of IFA, named the extended flow algorithm (EFA), for more effective determination of the optimal network configuration of a distribution system containing massive installations of DGs. EFA is a two-stage method in which the configuration that produces uniform power supply, referred to as the balanced configuration, is first generated, and then used to seek the optimal configuration using an improved branch exchange approach. Accordingly, EFA is more simplified to improve its computation speed on large-scale systems. The algorithm was tested by case studies of different test distribution systems in the MATLAB environment, and was confirmed to have high performance to cope with DG installations and large-scale systems. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The high degree of penetration of residential rooftop photovoltaic systems causes the overvoltage problem in power distribution systems. This paper aims to introduce demand-side management for a distribution system for overvoltage prevention. A real-time overvoltage prevention coordination scheme between an on-load tap changer ( OLTC) and multi-community energy management systems (multi- CEMSs) is proposed. The main objectives of this control are to relieve the stress in the OLTC tap operation using household schedulable loads and to maximize customer profit in each CEMS. The load scheduling performed by each CEMS is formulated as a combinatorial, nonlinear, time-series scheduling optimization problem and is solved by a sequential search method named voltage-ranking-based load combination search algorithm. The effectiveness of the proposed method is validated in a model distribution system with1800 customers. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Demand response ( DR), which is used to shave the peak demand for securing supply reliability in a power system, is one of the promising constitutions for the end users. In a commercial building ( COB), the most popular adjustable DR resource ( DRR) is the chiller system. More specifically, its power consumption can be reduced by thermal mass control (precooling) in a specified DR duration. On the other hand, installation of energy storage systems ( ESSs) is going on at an accelerated pace because of its high economic efficiency. ESSs have been used for peak-shift operation under the time-of-use ( TOU) tariff. However, ESS can be also used as an attractive DRR because it can reduce the net load by discharging the ESS for a specified DR duration. Based on this background, this paper presents a method for determining the optimal DR capacity in a COB with a chiller system and ESS. In the proposed scheme, the optimal DR capacity ( kW) can be determined so that the total expected cost of a COB becomes minimum by using the chiller system and ESS while avoiding the DR penalty threat adopted in the Korean DR market. Uncertainty in the ambient temperature, the amount of reduction, and DR durations are considered as the scenarios. The estimation and economic evaluation of the proposed scheme is ascertained through case studies. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]