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a b s t r a c tRealization of benefits from on-grid distributed generation based on renewable energy sources requires employment of energy storage to overcome the intermittency in power generation by such sources, while accounting for time-varying electricity prices. The objective of this study is to examine the effects of time-varying electricity prices on the performance of energy storage components for an on-grid hybrid renewable energy system (HRES) utilizing an optimized fuzzy logic controller (FLC). To achieve the objective, FLC membership functions are optimized for minimizing the operational cost of the HRES based on weekly and daily prediction of data for grid electricity price, electrical load, and environmental parameters, including wind speed, solar irradiation, and ambient temperature, using shuffled frog leap algorithm. FLC three inputs include (a) grid electricity price, (b) net power flow as the difference between energy produced and energy consumed, and (c) state of charge (SOC) of battery stack. It is confirmed that accounting for grid electricity price has considerable effects on the performance of energy storage components for operation of on-grid HRES, as the weekly and daily optimized FLCs result in less working hours for fuel cell and electrolyzer and less fluctuations in SOC of battery stack.

Abstract-Increasing penetration level of photovoltaic (PV) distributed generation (DG) into distribution networks will have many impacts on nominal circuit operating conditions including voltage quality and reverse power flow issues. In U.S. most studies on PVDG impacts on distribution networks are performed for west coast and central states. The objective of this paper is to study the impacts of PVDG integration on local distribution network based on real-world settings for network parameters and time-series analysis. PVDG penetration level is considered to find the hosting capacity of the network without having major issues in terms of voltage quality and reverse power flow. Time-series analyses show that distributed installation of PVDGs on commercial buses has the maximum network energy loss reduction and larger penetration ratios for them. Additionally, the penetration ratio thresholds for which there will be no power quality and reverse power flow issues and optimal allocation of PVDG and penetration levels are identified for different installation scenarios.

Public power system test cases that are of high quality benefit the power systems research community with expanded resources for testing, demonstrating, and cross-validating new innovations. Building synthetic grid models for this purpose is a relatively new problem, for which a challenge is to show that created cases are sufficiently realistic. This paper puts forth a validation process based on a set of metrics observed from actual power system cases. These metrics follow the structure, proportions, and parameters of key power system elements, which can be used in assessing and validating the quality of synthetic power grids. Though wide diversity exists in the characteristics of power systems, the paper focuses on an initial set of common quantitative metrics to capture the distribution of typical values from real power systems. The process is applied to two new public test cases, which are shown to meet the criteria specified in the metrics of this paper.

Abstract-Remarkable penetration of renewable energy in electric networks, despite its valuable opportunities, such as power loss reduction and loadability improvements, has raised concerns for system operators. Such huge penetration can lead to a violation of the grid requirements, such as voltage and current limits and reverse power flow. Optimal placement and sizing of Distributed Generation (DG) are one of the best ways to strengthen the efficiency of the power systems. This paper builds a simulation model for the local distribution network based on obtained load profiles, GIS information, solar insolation, feeder and voltage settings, and define the optimization problem of solar PVDG installation to determine the optimal siting and sizing for different penetration levels with different objective functions. The objective functions include voltage profile improvement and energy loss minimization and the considered constraints include the physical distribution network constraints (AC power flow), the PV capacity constraint, and the voltage and reverse power flow constraints.