Load Scheduling with Maximum Demand and Time of Use pricing for Microgrids

Several demand side management (DSM) techniques and algorithms have been used in the literature. These algorithms show that by adopting DSM and Time-of-Use (TOU) price tariffs; electricity cost significantly decreases, and optimal load scheduling is achieved. However, the purpose of the DSM is to not only lower the electricity cost, but also to avoid the peak load even if the electricity prices low. To address this concern, this dissertation starts with a brief literature review on the existing DSM algorithms and schemes. These algorithms can be suitable for Direct Load Control (DLC) schemes, Demand Response (DR), and load scheduling strategies. \end{abstract} Secondly, the dissertations compares two of DSM algorithms to show the performance based on cost minimization, voltage fluctuation, and system power loss [see in Chapter 5]. The results show the importance of balance between objectives such as electricity cost minimization, peak load occurrence, and voltage fluctuation evolution while simultaneously optimizing the cost

Optimized Household Demand Management with Local Solar PV Generation

Demand Side Management (DSM) strategies are of-ten associated with the objectives of smoothing the load curve and reducing peak load. Although the future of demand side manage-ment is technically dependent on remote and automatic control of residential loads, the end-users play a significant role by shifting the use of appliances to the off-peak hours when they are exposed to Day-ahead market price. This paper proposes an optimum so-lution to the problem of scheduling of household demand side management in the presence of PV generation under a set of tech-nical constraints such as dynamic electricity pricing and voltage deviation. The proposed solution is implemented based on the Clonal Selection Algorithm (CSA). This solution is evaluated through a set of scenarios and simulation results show that the proposed approach results in the reduction of electricity bills and the import of energy from the grid

An efficient hybrid photovoltaic battery power system based grid-connected applications

Power management systems for grid-tied photovoltaic-battery power systems are the focus of this research. Solar photovoltaic (PV) panels, lithium-ion batteries, and a voltage source inverter (VSC) are all part of the system. By employing the fuzzy logic (FL) technique, a PV system's power output can be maximized in a variety of weather circumstances. In addition, the state-of-charge-based power management system (PMS) was investigated to manage power sharing between sources and the grid and then manages the battery module's charge/discharge process. Active-reactive (PQ) control was used on the VSC converter while it was synced with the grid and regulated. In order to model and simulate the suggested system under various solar irradiances, Matlab/Simulink was employed. In contrast to the standard grid-connected inverter, which operates without batteries, the simulation results showed that adding the battery energy storage system BESS increased the system's performance. A grid-connected inverter that makes use of BESS can prevent the absence of PV energy or shading of the arrays. To explain why PMS is so effective, the simulations show that the injected grid current is more stable and has less total harmonic distortion (THD)

The control of permanent magnet synchronous motor drive based on the space vector pulse width modulation and fractional order PID controller

This study explains a new way to speed control for PMSMs based on the FOC and SVPWM techniques employed in the building of the permanent magnet synchronous motors (PMSMs). When it comes to current control, two inner and one outside feedback loops were used. Feedback control with FOPID controllers is used to optimize the performance of PMSM motor design. FOPID parameters were optimized using genetic algorithms in MATLAB/Simulink simulations. Good dynamic and static qualities are demonstrated through simulation results. There is also a comparison of PMSM PID and FOPID controllers included

Energy Management Optimization and Voltage Evaluation for Residential and Commercial Areas

In most smart grids, load management techniques are required to handle multiple loads of several types. This paper studies decentralized demand-side management (DSM) in a grid with different types of appliances in two service areas: one with many residential households, and one bus with commercial customers. Each building runs an individual optimal DSM to reschedule the usage time of its flexible appliances to reduce its electric energy cost at a manageable sacrifice of inconvenience according to the forecasted time-varying electricity price. Using the developed model, we examined the effectiveness of decentralized DSM by comparing its performance on the operation status of the grid in terms of electricity cost saving, rooftop photovoltaic (PV) utilization efficiency, voltage fluctuation, power loss, voltage rises, and reverse power flows, which can easily be seen at the commercial load bus