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Abstract This paper describes the development of a meta-heuristic based algorithm to solve the optimal transmission switching (OTS) problem. The approach solves the mixed-integer non-linear problem considering simultaneous optimization of transmission topology and generation dispatch. The algorithm is the first ever application of particle swarm optimization (PSO) to model OTS and operates using combined real and binary (CRB) variables to solve a weighted sum of interdependent multiple objective functions. The unique stochastic generation principle of combinatorial variables is based on a blend of both uniform and biased Gaussian probability distribution functions. The required binary values of swarms are generated from the continuous values of the random Gaussian distribution with the application of the Heaviside function. All the transmission lines are considered as potential switch variables the operations of which are limited by different aspects. The algorithm can tackle the complex optimization problem with many constraints of varying difficulty. The randomness in CRB variables and unpredictability in switching may generate infeasible particle(s) resulting in island formation. The algorithm also proposes regeneration of these infeasible particle(s) by modifying them to a feasible one to avoid this islanding as well as to have stable switching possibilities. The improvement in the computational efficiency of the algorithm is proposed with the adoption of Micro-PSO for small load deviations. A wide range of unique solutions are obtained based on the preferences of the system operator. This OTS algorithm is tested using the IEEE 57 bus and the IEEE 118 bus system and encouraging results are obtained.

In the current situation with the unprecedented deployment of clean technologies for electricity generation, it is natural to expect that storage will play an important role in electricity networks. This paper provides a qualitative methodology to select the appropriate technology or mix of technologies for different applications. The multiple comparisons according to different characteristics distinguish this paper from others about energy storage systems. Firstly, the different technologies available for energy storage, as discussed in the literature, are described and compared. The characteristics of the technologies are explained, including their current availability. In order to gain a better perspective, availability is cross-compared with maturity level. Moreover, information such as ratings, energy density, durability and costs is provided in table and graphic format for a straightforward comparison. Additionally, the different electric grid applications of energy storage technologies are described and categorised. For each of the categories, we describe the available technologies, both mature and potential. Finally, methods for connecting storage technologies are discussed.

Considerable interest is being shown in using biochar production from waste biomass with a variety of disciplines to address the most pressing environmental challenges. Biochar produced by the thermal decomposition of biomass under oxygen-limited conditions is gaining popularity as a low-cost amendment for agro-ecosystems. The efficiency of biochar formation is affected by temperature, heating rate, feedstock type, particle size and reactor conditions. Properties such as pH, surface area and ash content of produced biochar increases with increasing temperatures. Biochar produced at lower heating rates may have high porosity and be beneficial for morphological changes in the soil. Biochar can help to enhance soil health and fertility as well as improve agricultural yield. As a result, biochar can assist in increasing food security by promoting sustainable agricultural systems and preserving an eco-friendly environment. Biochar is also widely being used as a sorbent for organic and inorganic pollutants, owing to its large surface area, allowing it to be immobilized from soil with ease. The functional groups and charges present on the surface of biochar play an important role in pollutants removal. This review focuses on the mechanisms of biochar production using different waste materials as a feed stock, factors that influence biochar quality as well as application of biochar in agricultural soil and their reclamation as well. This article also discusses knowledge gaps and future perspectives in the field of biochar-based toxic-pollution remediation.

The Geomagnetically induced current (GIC) produces unwanted adverse consequences in the power system. It causes problems in the power system like transformer core saturation, really miss operation, blackout of system, voltage instability and heating of transformers, disturbance in communication systems, corrosion of pipelines, railway tracks etc. This paper provides information about GIC and its different effects in various technological systems. Also present the possible solution to reduce GIC.

The growing population and increasing urbanization have led to a surge in domestic wastewater generation, posing significant challenges for effective and sustainable treatment. The present study demonstrates a novel and sustainable approach for the onsite treatment of domestic wastewater using an integrated settler-based biofilm reactor (ISBR) with efficient biogas generation. The ISBR provides an optimized environment for the growth of biofilm, facilitating the removal of organic pollutants and pathogens. Moreover, the ISBR enables the recovery of a valuable resource in the form of biogas, thus enhancing the overall utility of the treatment process. The performance of the ISBR was comprehensively evaluated at laboratory scale through treating the actual domestic wastewater generated from the hostel of Manipal University Jaipur. The ISBR system was operated under an ambient environment at a hydraulic retention time (HRT) of 24 h. The results demonstrated remarkable efficiency in terms of chemical oxygen demand (COD), total suspended solids (TSS), and coliforms removal, with average removal efficiency being more than 90%. According to the COD mass balance analysis, 48.2% of the influent COD was recovered as bioenergy. The chromatogram revealed a high percentage of methane gas in the collected biogas sample. The field emission scanning electron microscope (FESEM) analysis of the accumulated sludge in the ISBR system depicted the morphology of methanogenic bacteria. Both the experimental and theoretical results confirmed the feasibility and sustainability of the ISBR system at the onsite level.

A thermoelectric generator with zero internal resistance, vanishing heat leakage and negligible production of Thomson heat is considered. It is shown that such a generator behaves as an ideal Carnot engine or an endoreversible Carnot engine depending upon whether the heat transfer mechanism at the junctions is reversible or a finite rate. Furthermore, the optimized power of the generator is found to be greater than that of the endoreversible Carnot engine.

Abstract This article introduces an effective stochastic operation framework for optimal energy management of the shipboard power systems including large, nonlinear and dynamic loads. The proposed framework divides the ship power system into several agents, which coordinate with each other based on their demands/supplies until. The alternating direction method of multipliers (ADMM) is deployed as the multi-agent framework to solve the reformulated distributed energy management problem in the ship. Two types of turbo-generators are considered in the proposed system model, including single-shaft and twin-shaft models, to increase the part-load efficiency in certain times when facing variable speed operation. The proposed distributed framework is equipped with a recursive mechanism, which helps the ship system for running optimal load scheduling when facing insufficient power generation. In order to model the uncertainty effects associated with the forecast error in the interval-ahead load demand, a stochastic framework based on unscented transform is devised which can work in the nonlinear and correlated environments of shipboard power systems. Due to the nonlinear cost function in each agent, a powerful optimization algorithm based on modified θ-firefly algorithm (Mθ-FOA) is proposed. This is a phasor algorithm, which helps for escaping from premature convergence and getting trapped in local optima. The appropriate performance of the proposed stochastic model is examined on the real dataset of a ship power system. The simulation results show the high robustness, guarantied consensus, economic operation and feasible solution when power generation shortage based on load shedding in the system.

Abstract The evolutionary algorithm of invasive weed optimization algorithm popularly known as the IWO has been used in this paper, to solve the unit commitment (UC) problem. This integer coded algorithm is based on the colonizing behavior of weed plants and has been developed to minimize the total generation cost over a scheduled time period while adhering to several constraints such as generation limits, meeting load demand, spinning reserves and minimum up and down time. The minimum up/down time constraints have been coded in a direct manner without using the penalty function method. The proposed algorithm was tested and validated using 10 units and 24 h system. The most important merit of the proposed methodology is high accuracy and good convergence speed as it is a derivative free algorithm. The simulation results of the proposed algorithm have been compared with the results of other tested algorithms for UC such as shuffled frog leaping, particle swarm optimization, genetic algorithm and Lagrangian relaxation and bacterial foraging algorithm.