With the increasing electricity power consumption and time-varying load demands, maintaining system reliability and economic operation has become a challenging task for power system operators during the scheduled outages. Nevertheless, very few publications in the current literature tackle this maintenance schedule problem by means of evolutionary algorithms, and, when they do, they focus only on generators. In the proposed model, the authors have considered coordinated maintenance scheduling (CMS) with cost minimisation and reliability maximisation as a multi-objective criterion, and fuzzy-based teaching learning-based optimisation is used as an optimisation tool for solving the formulated maintenance model. The proposed model solves the CMS along with security-constrained unit commitment (SCUC) over 1-year planning horizon and the final SCUC solution prescribes an economic and secure operation for composite power systems. The method is demonstrated on the IEEE 30-bus, IEEE reliability test system (single and three areas) and practical Indian utility 19-unit power systems, and the results are presented. Nomenclature NGnumber of generating units NL number of transmission lines i, j indices of generating units and transmission lines t index of periods NT number of intervals under study X it maintenance start indicator of unit i in interval t = 1 if the unit i is available at time t = 0 otherwise Y jt maintenance start indicator of line j in interval t = 1 if the line j is available at time t = 0 otherwise P′ it output power from generating unit i at time t C it quadratic function in terms of P′ it D it maintenance cost of unit i at time t D′ jt maintenance cost of transmission line j at time t R it set of start time periods I t set of units that are in maintenance in period t P it generating capacity of unit i in period t L t equivalent load for the maintenance period C t

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In recent years, the existence of wireless sensor networks (WSNs) has increased its growth on various applications. One of the applications of these low-cost sensors relies on monitoring the aquaculture where the fish are living. Even though more traditional methods are available for monitoring the movement of fish, WSNs provide an extreme solution for monitoring and it provides exact values by combining all the important parameters. One of the important parameter that is needed for precise measurement is called as quality of water. If the contamination level is very much lesser, then the fish can able to live in the environmental water for a long period of time. If the sensors are installed, then the contamination level of water can be easily observed and therefore in turn provides a way for recycling the water. Since, the sensors can able to cover more distance the range measurement needs to be taken because it is more important for determining the distance between each sensor within a specific location. Some individuals might have installed the pump for providing the flow of water; therefore, if the prime requirements are measured correctly and if exact values are taken, then the flow of pump in addition with velocity of water in the pump can be measured. The reason behind measuring the flow and velocity of water is that sufficient amount of water should always be maintained which will be indicated with a threshold value. If the values are either lesser or higher, then the sensors will sense those values and it will report to the wireless modules immediately for taking appropriate actions. Also, the velocity of water should always be maintained constantly because the solubility of oxygen will be inclined with respect to the velocity of water. All the parametric values will be passed to the router and it will be sent to all labours even in their languages which will be easy to understand. The information thus passed will be stored in a server using any database systems. Even the workers can

Summary Phasor measurement unit (PMU) plays a key role in concurrent power system state estimation and security enhancement processes. Considering the cost of PMU as an important concern, confined number of PMUs is located at hazardous locations for power system observability. The PMU placements can be explored further for various power system operational studies. One promising indicator is that not only the PMUs should be informative, but also they should be able to perceive the voltage stability levels under critical loading conditions. In topical eons the role of voltage stability is essential which causes severe difficulty. Regrettably, this results in enhancement and impractical vision because of same cost of consumption of PMUs. It is sufficient to reduce the deployment cost provided that the factors such as reliability of the measurement system, observability can be certain for effective placement of PMUs. In line with the above concern, to solve the problem efficiently, a realistic multiobjective model that includes 3 objectives such as (1) system observability with minimum number of PMUs, (2) envisaging the communication cost involved in these placements, and (3) enhancing the voltage stability levels of the system is proposed. The developed model is solved as a nonlinear and constrained optimization problem in multiobjective framework. The binary coding scheme is conventionally preferred for solving PMU placement problem, hence, binary‐coded ant lion optimizer has been developed and is applied for the first time to solve the developed multiobjective PMU placement model. The standard IEEE test systems (14 bus, 30 bus, and 57 bus systems) and a large scale system containing 2383 buses are used to ratify the proposed model and the envisioned optimization tool. Numerical outcome specifies that binary‐coded ant lion optimizer is robust and effective in finding the best compromise solution.