ABSTRACT
The world has now looked towards installing more renewable energy sources type distributed generation (DG), such as solar photovoltaic DG (SPVDG), because of its advantages to the environment and the quality of power supply it produces. However, these sources' optimal placement and size are determined before their accommodation in the power distribution system (PDS). This is to avoid an increase in power loss and deviations in the voltage profile. Furthermore, in this article, solar PV is integrated with battery energy storage systems (BESS) to compensate for the shortcomings of SPVDG as well as the reduction in peak demand. This paper presented a novel coronavirus herd immunity optimizer algorithm for the optimal accommodation of SPVDG with BESS in the PDS. The proposed algorithm is centered on the herd immunity approach to combat the COVID-19 virus. The problem formulation is focused on the optimal accommodation of SPVDG and BESS to reduce the power loss and enhance the voltage profile of the PDS. Moreover, voltage limits, maximum current limits, and BESS charge-discharge constraints are validated during the optimization. Moreover, the hourly variation of SPVDG generation and load profile with seasonal impact is examined in this study. IEEE 33 and 69 bus PDSs are tested for the development of the presented work. The suggested algorithm showed its effectiveness and accuracy compared to different optimization techniques. © 2023 TÜBÍTAK.
ABSTRACT
The City of Zagreb in Croatia and its surroundings have experienced two strong earthquakes within nine months of 2020. Putting this in the context of the increased workload of healthcare facilities due to Covid-19, the distribution system operator (DSO) is encouraged to look for unconventional solutions such as integrating the battery energy storage system (BESS) to supply healthcare facilities during network fault conditions or other extreme network events. The BESS size and location are determined by optimization model, while the control system of the BESS converter, based on the virtual synchronous machine (VSM) concept, is define to test BESS ability to supply critical consumers in the off-grid mode. The models are tested and verified on several real world situations in Zagreb MV distribution network. Future developments and scenarios are also simulated to verify the robustness of the proposed investment. © 2022 IEEE.
ABSTRACT
The dependence on fossil resources remains high, accounting for 80% of the total primary energy production worldwide. In addition, the COVID-19 pandemic has devastated several industries and electric power is no exception. Therefore, renewable energy sources have become an important aspect of the energy sector, contributing to solutions to environmental problems and the development of a sustainable future. Therefore, this study proposes a model to evaluate the energy autonomy of a photovoltaic microgrid (EAPV,MG) using a battery energy storage system (BESS). To carry out the analysis, the energy consumption history of a residence and the solar irradiation data of the location were used. Thus, this study includes the evaluation of the energy compensation of a photovoltaic microgrid that directly injects energy into the residence, and the surplus is stored in a BESS for later use. The results show the relevance of EAPV,MG modeling for optimal system sizing. The model determines the autonomy of the microgrid without many power variations in the PV system for January, April, and October, corresponding to the summer, autumn, and spring seasons, respectively. However, in July (winter), the photovoltaic MG must increase the installation power considerably and the storage capacity of the BESS. Therefore, an optimal decision evaluating the EAPV,MG will allow broadening an overview to opt for a PV microgrid that injects the highest amount of energy based on the actual residential load profile and the optimal capacity of the BESS. Consequently, the analysis of the EA of a microgrid based on solar irradiation and actual load data is essential for developing an optimal and stable operation of the residential energy system.