Smart cities employ technology and data to increase efficiencies, economic development, sustainability, and life quality for citizens in urban areas. Inevitably, clean technologies promote smart cities development including for energy, transportation and health. The smart city concept is ambitious and is being refined with standards. Standards are used to help with regulating how smart cities function and contributing to define a smart city. Smart cities must be officially recognized by national and international authorities and organizations in order to promote societal advancement. There are many research and review articles on smart cities. However, technical standards are seldom discussed in the current literature. This review firstly presents the study of smart city definitions and domain. The well-known smart city standards will be presented to better recognize the smart city concept. Well-defined standards allow meaningful comparisons among smart cities implementation. How smart city initiatives make a city smarter and improve the quality of life will be discussed for various countries. This review highlights that technical standards are important for smart cities implementation. This paper serves as a guide to the most recent developments of smart cities standards.

This paper describes a new maximum-power-pointtracking method for a photovoltaic system based on the Lagrange Interpolation Formula and proposes the particle swarm optimization method. The proposed control scheme eliminates the problems of conventional methods by using only a simple numerical calculation to initialize the particles around the global maximum power point. Hence, the suggested scheme will utilize fewer iterations to reach the maximum power point. The proposed algorithm is verified with the OPAL-RT real time simulator and the Matlab Simulink tool, with several simulations being carried out, and compared to the Perturb and Observe method, the Incremental Conductance method, and the conventional Particle Swarm Optimization based algorithm. The simulation results indicate the proposed algorithm can effectively enhance stability and fast tracking capability under fastchanging non-uniform insolation conditions.

Optimal voltage regulation is one of the main issues to address in a Smart Grid context. In this domain, the application of traditional hierarchical control paradigms has some disadvantages that could hinder their application in Smart Grids where the constant growth of grid complexity and the need for massive pervasion of distribution generation systems require more scalable and more flexible control and regulation paradigms. To try and overcome these challenges, this paper proposes the concept of a decentralized nonhierarchal voltage regulation architecture based on intelligent and cooperative smart entities. This paper intends to bring two main contributions to the existing literature. The first is the definition of a decentralized architecture aimed at computing the actual value of the cost function and its gradient without the need of a central fusion center acquiring and processing all the sensor acquisitions. The second is the proposal of a distributed and cooperative optimization strategy aimed at identifying the optimal asset of the voltage controllers.

In its broadest sense, passive filters have been a very potent technique for power system harmonic suppression because of their possible different frequency response characteristics that can achieve a certain required harmonic filtering target, also due to their simplicity and economical cost. This paper presents an application of FORTRAN feasible sequential quadratic programming to find the optimal sizing of parameters of C -type passive filters for minimizing the total voltage harmonic distortion of nonlinear loads, where maintaining a given power factor at a specified range is desired. The optimal design of the C -type passive filter as an alternative to the conventional passive filtering techniques is introduced, and a detailed comparison of the results between an uncompensated system and a C -type filter are discussed by means of different numerical examples, considering source and load nonlinearities, while taking into account compliance with the IEEE standards 519-1992 and 18-2002.

Optimal phasor measurement units (PMUs) placement refers to the strategic placement of PMUs to achieve the full observability of power systems with a minimum number of PMUs. A strategic placement is needed because of the economic or technical restriction that hinders the deployment of PMUs on every bus. A modified version of the binary particle swarm optimization method is proposed in this paper by integrating a mutation strategy and the V-shaped sigmoid function for placing the PMUs that maintains the full power system observability in the presence of zero-injection bus, single PMU loss, and PMU's channel limits while maximizing the measurement redundancy. The solution that has the highest measurement redundancy was selected as the best placement of PMUs. The use of mutation strategy and V-shaped sigmoid function in this paper improves the population diversity, thereby minimizing the chance of the particles being trapped in the local optima, consequently leading to a quality solution. In order to validate its effectiveness, the results obtained by the proposed method are compared with other published techniques to demonstrate the accuracy and validity of the proposed technique. The results of the IEEE 300-bus system show that the proposed method effectively managed to reduce the number of PMUs needed.