Hybrid PIPSO-SQP Algorithm for Real Power Loss Minimization in Radial Distribution Systems with Optimal Placement of Distributed Generation

This paper proposes the hybrid sequential quadratic programming (SQP) technique based on active set method for identifying the optimal placement and rating of distribution generation (DG) incorporated in radial distribution systems (RDS) for minimizing the real power loss satisfying power balance equations and voltage limits. SQP runs quadratic programming sequentially as a sub-program to obtain the best solution by using an active set method. In this paper, the best optimal solution is selected with less computation time by combining the benefits of both classical and meta-heuristic methods. SQP is a classical method that is more sensitive to initial value selection and the evolutionary methods give approximate solution. Hence, the initial values for the SQP technique were obtained from the meta–heuristic method of Parameter Improved Particle Swarm Optimization (PIPSO) algorithm. The proposed hybrid PIPSO–SQP method was implemented in IEEE 33-bus RDS, IEEE 69-bus RDS, and IEEE 118-bus RDS under different loading conditions. The results show that the proposed method has efficient reduction in real power loss minimization through the enhancement of the bus voltage profile

Framework of Transactive Energy Market Strategies for Lucrative Peer-to-Peer Energy Transactions

Leading to the enhancement of smart grid implementation, the peer-to-peer (P2P) energy transaction concept has grown dramatically in recent years allowing the end-users to successfully exchange their excess generation and demand in a more profitable way. This paper presents local energy market (LEM) architecture with various market strategies for P2P energy trading among a set of end-users (consumers and prosumers) in a smart residential locality. In a P2P fashion, prosumers/consumers can export/import the available generation/demand in the LEM at a profit relative to utility prices. A common portal known as the transactive energy market operator (TEMO) is introduced to manage the trading in the LEM. The goal of the TEMO is to develop a transaction agreement among P2P players by establishing a price for each transaction based on the price and trading demand provided by the participants. A few case studies on a location with ten residential P2P participants validate the performance of the proposed TEMO

State-Flow Control Based Multistage Constant-Current Battery Charger for Electric Two-Wheeler

Battery charging is a greater challenge in the emerging electric vehicle domain. A newer multistage constant-current (MSCC) charging technique encompassing state-flow control tool-based design is implemented for charging the battery of an electric two-wheeler. MSCC method allows for faster charging and reduced battery degradation per charge. The designed controller incorporates line current power factor correction, thereby limiting the total harmonic distortion (THD) in line current and reactive power. The control strategy for battery charging has been developed using the state flow chart approach for implementing MSCC. The model has been formulated and implemented in MATLAB/Simulink. The proposed control monitors the state-of-charge (SOC) of the battery, age, and thermal behavior due to the charging strategy. The results show that the proposed charging technique with a state flow control approach gives effective and efficient output with reduced THD. Simulation results disclose that the desired parameters are controllable, stable, and effective within the operational limits

Reduction of 1/f Noise in Single-Walled Carbon Nanotubes (SWCNTs) Using Gas Adsorption Technique

Single-walled carbon nanotube (SWCNT) plays a major role in electromagnetic absorption and shielding. Their applications as semiconductors make a breakthrough in communication by miniaturizing the communication devices. The main drawback of the SWCNT is found to 1/f noise. Because of this limitation, high attenuation at the low-frequency band cannot be achieved, limiting its application in terms of selectivity. The spectral density study shows that the noise’s amplitude is directly proportional to the temperature and inversely proportional to the number of carriers in the nanotube. The SWCNT is mainly synthesized using hydrocarbons which contains carbonaceous impurities. On the removal of impurities, more surface oxygen functional groups are formed. On the other hand, the diameter of the carbon nanotube is very small, increasing the resistance of carrier flow. In this research work, gas adsorption was used in SWCNT by treating the carbon nanotube using nitric acid. Isotherms determine porous size. The adsorbate-adsorbent interaction on carbon nanotube reduces the microporosity in the surface by treating with nitric acid. Therefore, the density of the surface increases and the CNT bundle separation will be reduced, increasing the carbon nanotube’s resistivity. This increase in resistivity reduces the excess carrier flow; therefore, the temperature will reduce the 1/f noise. The proposed system is cost-effective and has shown 11% improvement by reducing the noise amplitude by increasing carbon nanotube resistance. This proposed method has less complexity compared with existing models