In the present scenario, the utilities are focusing on smart grid technologies to achieve reliable and profitable grid operation. Demand side management (DSM) is one of such smart grid technologies which motivate end users to actively participate in the electricity market by providing incentives. Consumers are expected to respond (demand response (DR)) in various ways to attain these benefits. Nowadays, residential consumers are interested in energy storage devices such as battery to reduce power consumption from the utility during peak intervals. In this paper, the use of a smart residential energy management system (SREMS) is demonstrated at the consumer premise to reduce the total electricity bill by optimally time scheduling the operation of household appliances. Further, the SREMS effectively utilizes the battery by scheduling the mode of operation of the battery (charging/floating/discharging) and the amount of power exchange from the battery while considering the variations in consumer demand and utility parameters such as electricity price and consumer consumption limit (CCL). The SREMS framework is implemented in Matlab and the case study results show significant yields for the end user.

An economic evaluation of a network of distributed energy resources (DERs) comprising a microgrid structure of power delivery system in an Indian scenario has been made. The mathematical analysis is based on the application of tuned genetic algorithm (TGA). The analyses for optimal power operation pertaining to minimum cost have been made for two cases in Indian power delivery system. The first case deals with the consumers’ individual optimal operation of DERs, while in the second one, consumers altogether form a microgrid with the optimal supply of power from DERs. The total annual costs for these two cases are found to be economically competitive and encouraging. A reduction of approximately 5.7% in the annual cost has been obtained in the case of microgid system than that in the separately operating consumers’ system for a small locality of India. It is observed that the application of TGA results in a reduction of the minimum cost depicting an improved outcome in terms of energy economy.

Effective utilization of renewable energy sources and efficient management of electric energy are essential for any developing countries like India. This can be envisioned through the implementation of concepts of smart grid (SG). One of the key requisites for SG implementation is that the grid should be completely observable. Renovation of conventional Indian power grid to a SG necessitates incorporation of the phasor measurement units (PMUs) in the present power grid measurement and monitoring system. Since the cost of PMU is high and any bus containing a PMU makes the neighboring connected buses observable, optimal placement of PMUs is very important for complete observability of the grid. This paper proposes optimal redundant geographical locations in the northern, eastern and north-eastern regions of Indian power grid for PMU placement. The PMUs installed in these geographical locations will make the grid completely observable and maintain the observability under the conditions of failure of some PMUs or branch outages. Integer linear programming has been used for finding the optimal PMU locations. The results proposed in this paper can be a stepping stone for revamping the Indian power grid to a SG ensuring complete observability during different contingency conditions.

Efficient utilization of energy resources is essential for a developing country like India. The concept of smart grid (SG) can provide a highly reliable power system with optimized utilization of available resources. The present Indian power grid requires revolutionary changes to meet the growing demands and to make the grid smarter and reliable. One of the important requirements for SG is the instantaneous monitoring of the voltage, current and power flows at all buses in the grid. The traditional monitoring system cannot satisfy this requirement since they are based on nonlinear power flow equations. Synchro-phasor-measurement devices like phasor measurement units (PMUs) can measure the phasor values of voltages at installed buses. Consequently, the currents passing through all branches connected to that bus can be computed. Since the voltage phasor values at the neighboring buses of a bus containing the PMU can be estimated using Ohm’s law, it is redundant to install PMUs at all the buses in a power grid for its complete observability. This paper proposes the optimal geographical locations for the PMUs in southern region Indian power grid for the implementation of SG, using Integer Linear Programming. The proposed optimal geographical locations for PMU placement can be a stepping stone for the implementation of SG in India.

This paper presents a novel modified interactive honey bee mating optimization (IHBMO) base fuzzy stochastic long-term approach for determining optimum location and size of distributed energy resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting. A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduction in peak load level and reduction in voltage deviation are considered simultaneously as the objective functions. First, these objectives are fuzzified and designed to be comparable with each other. Then, they are introduced into an IHBMO algorithm in order to obtain the solution which maximizes the value of integrated objective function. The output power of DERs is scheduled for each load level. An enhanced economic model is also proposed to justify investment on DER. An IEEE 30-bus radial distribution test system is used to illustrate the effectiveness of the proposed method.

This paper presents various approaches used by researchers for handling the uncertainties involved in renewable energy sources, load demands, etc. It gives an idea about stochastic programming (SP) and discusses the formulations given by different researchers for objective functions such as cost, loss, generation expansion, and voltage/V control with various conventional and advanced methods. Besides, it gives a brief idea about SP and its applications and discusses different variants of SP such as recourse model, chance constrained programming, sample average approximation, and risk aversion. Moreover, it includes the application of these variants in various power systems. Furthermore, it also includes the general mathematical form of expression for these variants and discusses the mathematical description of the problem and modeling of the system. This review of different optimization techniques will be helpful for smart grid development including renewable energy resources (RERs).

Smart technologies when used in the traditional grid infrastructure will provide a different environment and working conditions in the grid by bringing the required smartness into the grid, called the smart grid. The smart grid can play a major role in the upcoming days to come because there is a necessity to integrate coordinated renewable energy resources into the grid and to operate the grids at a higher efficiency considering many aspects including reliability of the supply. Apart from this, there is a necessity to manage the demand supply gap in the smart grid by optimally scheduling the generators or by effectively scheduling the demand side resources instead of going for the traditional methods like partial or full load shedding. This paper presents an overview on the present state-of-the-art of smart grid technologies and broadly classifies the papers referred into two major areas, papers based on improvement of operational efficiency in smart grids and papers based on smartness in maintaining the demand supply gap. Some of the papers projected in this work also give a brief overview of the necessity of the smart grid.

With the latest introduction of the demand side management (DSM) in smart grids, the power distribution units are able to modify the load schedules of the consumers. This involves a co-operative interaction of the utility and the consumers so as to achieve customer load modifications in which the customer, utility and society all are benefited. The interaction is performed with the help of the devices known as the smart meter. This paper shows the use of game theory and logical mathematical expressions in order to achieve the objectives. The objectives are to minimize the peak to average ratio (PAR) and the energy cost. The outcome of the game between supplier and customers helps to shape the load profile. The design proposed in this paper is very user-friendly and is based on simple logarithmic programming computations. In this paper, residential, commercial and industrial types of loads are taken into account. A basic 24 h load schedule along with the fluctuating prices at each hour of the day is forecasted by the supplier of the various shiftable and non-shiftable loads and then that schedule is conveyed to the user. The users are encouraged to shift their high load devices to off-peak hours which will not only reduce their electricity costs but also substantially reduce the PAR in the load demand.

The number of electric vehicles are increasing in the society as they are considered as zero emission vehicles and also because conventional fuels are becoming expensive. Additional electrical power should be produced to meet the energy requirement of this increase in electric vehicle population. To use the existing grid infrastructure without any failure, installing distributed generator at secondary distribution network is essential. In this work, sizing of wind-driven permanent magnet synchronous generator—photovoltaic hybrid distributed generating system has been attempted to meet the energy demand of electric vehicles of a particular residential area. Different feasible combinations for wind generator capacity and photovoltaic capacity are obtained to satisfy the additional energy requirement. Results are analyzed based on energy, financial payback periods and daily power profile of the hybrid system. Based on this analysis, the sizes of wind generator and photovoltaic array have been chosen to meet the energy demand of electric vehicles of that particular residential locality.

Boosting the resilience of power systems is a core requirement of smart grids. In fact, resilience enhancement is crucial to all critical infrastructure systems. In this study, we review the current research on system resilience enhancement within and beyond smart grids. In addition, we elaborate on resilience definition and resilience quantification and discuss several challenges and opportunities for system resilience enhancement. This study aims to deepen our understanding of the concept of resilience and develop a wide perspective on enhancing the system resilience for critical infrastructures.