OPTIMAL ENERGY MANAGEMENT-HYBRID WT–PV–BATTERY ENERGY STORAGE SYSTEMS-NUTCRACKER OPTIMIZATION скачать в хорошем качестве

OPTIMAL ENERGY MANAGEMENT-HYBRID WT–PV–BATTERY ENERGY STORAGE SYSTEMS-NUTCRACKER OPTIMIZATION

DESIGN OVERVIEW The rapid growth in global electrical power demand, coupled with environmental concerns and the depletion of fossil fuel resources, has accelerated the transition toward renewable energy sources and necessitated advanced energy management strategies for reliable, economical, and sustainable smart grid operation. In this context, this design proposes an efficient energy management framework for smart grids integrating hybrid wind turbine (WT), photovoltaic (PV), and battery energy storage system (BESS) resources using the Nutcracker Optimization Algorithm (NOA). The proposed approach optimally determines the placement, power dispatch, and operational scheduling of distributed renewable generators and energy storage units under varying load demands and environmental conditions. A comprehensive objective function is formulated to minimize real power losses and voltage deviations while satisfying operational constraints related to renewable generation limits, battery state-of-charge boundaries, and network voltage constraints. Network performance is evaluated using the backward–forward sweep load flow technique, ensuring accurate assessment of each candidate solution. Inspired by the intelligent foraging and caching behavior of nutcracker birds, NOA provides a balanced exploration–exploitation mechanism that enables effective convergence toward globally optimal solutions. Extensive simulation studies carried out on a 136-bus radial distribution system under multiple operating scenarios including PV-only, WT-only, BESS-only, and combined PV–WT–BESS—demonstrate the robustness and effectiveness of the proposed framework, with results confirming significant improvements in voltage profiles and substantial reductions in power losses compared with individual resource integration, thereby establishing the proposed NOA-based energy management strategy as a scalable and reliable solution for future smart grid and microgrid applications with high renewable energy penetration. OBJECTIVE FUNCTION The objective function,F(k)=min{w_1 f_1 (k)+w_2 f_2 (k)} f_1 (k)=min∑_(i=1)^br▒〖R_i*I_i^2 〗 , Power Loss f_2 (k)=1/b ∑_(k=1)^b▒|1-V_k |^2 , Average Voltage Deviation Index Scenarios 1. Basecase 2. Optimal allocation of PV 3. Optimal allocation of WT 4. Optimal allocation of BESS 5. Simultaneous allocation of PV, WT, and BESS Matlab Simulation Results 1. Active Power Loss (kW) 2. Reactive Power Loss (kVAr) 3. Minimum and Maximum Voltage (PU) @ Bus 4. Optimal PV, WT, and BESS Location 5. Optimal BESS Size 6. Execution Time Matlab Simulation Figures 1. Voltage Profile for 24 Hours (PV, WT, ESS, and PV WT with ESS) 2. Convergence graph REFERENCES Reference Paper-1: Stochastic Optimal Planning of Distribution System Considering Integrated Photovoltaic-Based DG and DSTATCOM Under Uncertainties of Loads and Solar. Author’s Name: Eyad S. Oda, Amal M. Abd El Hamed, Abdelfatah Ali and, Adel A. Elbaset, Source: IEEE Year:2021 Reference Paper-2: Energy Exchange Control in Multiple Microgrids with Transactive Energy Management Author’s Name: Mohammadreza Daneshvar, Behnam Mohammadi-Ivatloo, Mehdi Abapour, and Somayeh Asadi Source: IEEE Year:2020 Reference Paper-3: Optimal placement and sizing of photovoltaics and battery storage in distribution networks Author’s Name: Riad Chedid and Ahmad Sawwas Source: Wiley Year:2019 Request source code for academic purpose, fill REQUEST FORM below, http://www.verilogcourseteam.com/requ... If you need Matlab p-code(encrypted files) to check the results, contact us by email to info@verilogcourseteam.com You may also contact +91 7904568456 by WhatsApp Chat, for paid services. We are also available on Telegram and Signal. Visit Website: http://www.verilogcourseteam.com/ Visit Our Social Media Like our Facebook Page:   / verilogcourseteam   Subscribe:    / @verilogteam   Subscribe:    / verilogcourseteammatlabproject   Subscribe:    / verilogcourseteam