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The wide spread of distributed energy resources (DERs) enabled the transformation of the passive consumer to an active prosumer. One of the promising approaches for optimal management of DERs and maximizing benefits for the community and prosumers is community energy trading (CET). CET gives the prosumers the flexibility and freedom to trade electricity within the neighborhood and maximize their economic benefits besides maximizing local consumption of renewable energy sources generation. Despite the economic benefits of CET for individuals and the whole community, it could cause impacts on the low voltage distribution network (LVDN). Therefore, there is a need for a comprehensive evaluation of the potential impacts of CET on LVDN. This study compared CET with the home energy management system (HEMS) regarding community operation costs and interaction with the retailer. Furthermore, this paper focused on assessing the impacts of CET between prosumers on the phase unbalance of LVDN. Moreover, the impacts on transformer loading, lines loading, and voltage deviations are assessed. Compared to the corresponding HEMS scenarios, the results demonstrate that CET reduces the community electricity cost by up to 31%. CET resulted in better self-consumption by reducing the exports to the retailer by 93% and better self-sufficiency by covering up to 54% of energy demand by community DERs. However, CET resulted in increasing the community peak demand, accordingly, higher impacts on the LVDN. The transformer is lightly loaded in all scenarios. CET resulted in limit violations in some lines, whereas most are lightly loaded. The voltage magnitude and voltage unbalance exceeded the acceptable limits at some nodes of the LVDN.

Power demand varies on a daily and seasonal basis. Responding to changing demands over time is challenging for energy suppliers as it causes expensive power plants to operate in high-demand seasons, usually summer, increasing the cost of electricity. Peak load shaving makes the load curve flatten by reducing the peak load and shifting it to times of lower demand, hence reducing the operation of expensive power plants. Hence, there is a need for large-scale and long-term ESS to store energy in the time of low-demand seasons for future utilization in the highest-demand ones. In this work, an energy management system (EMS) is developed to optimally manage a grid-connected pumped hydro storage (PHS) for peak shaving. The proposed model incorporates a dynamic economic dispatch (DED) over a study period of one year; hence, a DC power flow analysis considering transmission constraints is utilized to ensure a fast load flow estimation and a manageable simulation time. The framework can be adopted to assess the long-term profitability of PHS-utilizing GAMS as an optimization tool. Further, to draw conclusions that would suit the characteristics of the demand pattern. This analysis is essential to motivate the construction of new seasonal PHS plants due to the high construction costs they are identified with, especially in geographical areas where this technology is not yet considered or is hard to construct. The simulation results demonstrate that integrating 1500 MWh PHS reduced the operation of expensive thermal units by 1224 MWh annually. Further, a reduction in operation costs was recorded after integrating a PHS unit that ranged from 2.6 M to 22 M USD/year, depending on the storage capacity.

With countries moving toward renewable energy sources (RES), the need for dispatchability and storage solutions has become more prevalent. The uncertainty associated with wind turbine (WT) units and photovoltaic (PV) systems further complex a system with a high level of intermittency. This work addresses this problem by proposing an operational planning approach to determine the optimal allocation of WT units, PV systems, and hybrid energy storage systems (HESS) in smart grids. The proposed approach considers the uncertainties of the RES and load demand, price-based demand response, and distribution static compensator (DSTATCOM) functionality of the RES interfacing inverters. The operational planning problem is divided into two subcategories: (1) optimal long-term planning and (2) optimal operation. In the first problem, probabilistic models of RES and load reflect on the sizes and locations of the used RES and storage technologies. This allocation is further optimized via the optimal operation of the smart grid. The proposed operational planning approach is formulated as a nested optimization problem that guarantees the optimal planning and operation of the RES and HESS simultaneously. This approach is tested on the IEEE 33-bus distribution system and solved using meta-heuristic and mathematical algorithms. The effectiveness of the proposed approach is demonstrated using a set of case studies. The results demonstrate that the proposed approach optimally allocates the RES and HESS with a 30.4% cost reduction and 19% voltage profile improvement.

Recently, with the large-scale integration of renewable energy sources into microgrid (μGs) power electronics, distributed energy systems have gained popularity. However, low inertia reduces system frequency stability and anti-disturbance capabilities, exposing power quality to intermittency and uncertainty in photovoltaics or wind turbines. To ensure system stability, the virtual inertia control (VIC) is presented. This paper proposes two solutions to overcome the low inertia problem and the surplus in capacities resulting from renewable energy sources. The first solution employs superconducting magnetic energy storage (SMES), which can be deemed as an efficient solution for damping the frequency oscillations. Therefore, in this work, SMES that is managed by a simple proportional-integral-derivative controller (PID) controller is utilized to overcome the low inertia. In the second solution, the hydrogen storage system is employed to maintain the stability of the microgrid by storing surplus power generated by renewable energy sources (RESs). Power-to-Power is a method of storing excess renewable energy as chemical energy in the form of hydrogen. Hydrogen can be utilized locally or delivered to a consumption node. The proposed μG operation demonstrates that the integration of the photovoltaics (PVs), wind turbines (WTs), diesel engine generator (DEG), electrolyzer, micro gas turbine (μGT), and SMES is adequate to fulfill the load requirements under transient operating circumstances such as a low and high PV output power as well as to adapt to sudden changes in the load demand. The effectiveness of the proposed schemes is confirmed using real irradiance data (Benban City, Egypt) using a MATLAB/SIMULINK environment.

Abstract Along with the various features for implementing the Hybrid AC/DC Microgrid (HMG), this article proposes an approach for optimal allocation of multiple capacitors which are investigated in a proposed modeling based on the IEEE 14-bus distribution system. The power quality of the HMG has been investigated during the urgent intermittent of Distributed Energy Resources (DERs) and Reactive Power Compensation (RPC) methods. Moreover, the investigation has been achieved in the presence of unbalanced loads and nonlinear loads with maximum and minimum demand scenarios. To cope with the power quality concerns in the studied cases, the fixed capacitor bank as an RPC system in Medium Voltage (MV) level load buses has been utilized. Although the performance indices of the power quality improved in MV-level buses, the Low Voltage (LV) level load buses still endure extensive operation performance deteriorations caused by unbalanced loads. Therefore, in this article, a compensation scheme applied in LV-level load buses and MV-level buses has been proposed consistent with the power flow computations. The Multi-Objective Grey Wolf Optimizer (MOGWO) algorithm is implemented to optimize both the size and location of capacitor banks over different voltage levels with high accuracy. The comprehensive assessment and discussion of the simulation results demonstrate the superiority of utilizing the proposed compensation scheme in both MV-level and LV-level load buses. Hence, the power quality is not only enhanced but also the installation cost is reduced. The complete model of the studied system has been validated using MATLAB/ Simulink. Article Highlights The reactive power compensation method is used to improve the power quality in a hybrid AC-DC microgrid. The applied RPC method verifies using the MOGWO algorithm to optimize both the location and size of multiple capacitor banks. Power quality challenges and future research trends are debated.