The global demand for electrical energy is constantly increasing while the production of fossil fuel based energy is declinin g and therefore the obvious choice of clean energy source which is abundant and could provide security for the future development is sun's energy. This paper summarizes the modeling of PV module and PV characteristics under shaded conditions. The power- voltage characteristic of photovoltaic array is non-linear and it exhibits multiple peaks including many local peaks and one global peak under non-uniform irradiances. In order to track the global peak, MPPT is the important component of PV systems. Though many review papers discussed the conventional techniques such as P&O, incremental conductance, ripple correlation control and only very few attempts have been made with intelligence MPPT techniques. This paper also discusses the various algorithms based on Fuzzy Logic, Artificial Neural Network, Ant Colony Optimization, Genetic Algorithm and Particle Swarm Optimization applied to maximum power point tracking in photovoltaic systems under changing irradiance conditions. This paper is intended to introduce a conceptual MPPT technique based on Firefly Algorithm (FA)

Due to the rapid growth in power consumption of domestic and industrial appliances, distributed energy generation units face difficulties in supplying power efficiently. The integration of distributed energy resources (DERs) and energy storage systems (ESSs) provides a solution to these problems using appropriate management schemes to achieve optimal operation. Furthermore, to lessen the uncertainties of distributed energy management systems, a decentralized energy management system named virtual power plant (VPP) plays a significant role. This paper presents a comprehensive review of 65 existing different VPP optimization models, techniques, and algorithms based on their system configuration, parameters, and control schemes. Moreover, the paper categorizes the discussed optimization techniques into seven different types, namely conventional technique, offering model, intelligent technique, price-based unit commitment (PBUC) model, optimal bidding, stochastic technique, and linear programming, to underline the commercial and technical efficacy of VPP at day-ahead scheduling at the electricity market. The uncertainties of market prices, load demand, and power distribution in the VPP system are mentioned and analyzed to maximize the system profits with minimum cost. The outcome of the systematic categorization is believed to be a base for future endeavors in the field of VPP development.

Advanced LSTM-Based Time Series Forecasting for Enhanced Energy Consumption Management in Electric Power Systems

The maximum possible power is extracted from a solar photovoltaic (PV) array utilizing MPPT. P&O algorithm is utilized in this MPPT approach to extract the highest solar power output with less or no oscillation than other MPPT techniques in the output PV power. The Perturb and Observe algorithm is easy and simple to understand and also to execute. Conversion efficiency of a PV structure can be enhanced by implementing DC to DC boost converter and MPPT algorithm. Duty cycle of a boost converter is introduced for increasing PV voltage level. MPPT algorithms has been created in MATLAB and tested in a simulated environment. MATLAB is used to model the PV array and boost converter.