Naran M. Pindoriya

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Grid-connected Photovoltaic (PV) systems, when produce power comparable to local demand, pose a risk of sustained operation in islanded mode unintentionally. This paper presents a case study to assess the probable scenarios of unintentional islanding in a spot network with roof-top PV system. Most probable time slots during which the unintentional islanding(More)
This paper presents a fast and efficient method which combines the Monte Carlo simulation (MCS) and the least squares support vector machine (LSSVM) classifier, for reliability evaluation of composite power system. LSSVM is used to accurately pre-classify the power system operating states as either success or failure states during the Monte Carlo sampling.(More)
This paper presents a multi-objective evolutionary algorithm to solve the day-ahead thermal generation scheduling problem. The objective functions considered to model the scheduling problem are: 1) minimizing the system operation cost and 2) minimizing the emission cost. In the proposed algorithm, the chromosome is formulated as a binary unit commitment(More)
Thrust from government policies, regulations, and solar technology advancements have brought rapid rise in installed capacity of off-grid and grid-connected Solar Photovoltaic (SPV) systems in India. This paper presents an update on a case study undertaken for the underground cable fed electrical power distribution network with two types of local(More)
Wind power is the most promising and mature technology among the renewable energy resources. But the intermittent nature of wind makes it difficult to predict, schedule, manage and control wind power generation efficiently. Grid integration of large scale wind farms may pose significant challenges on power system operation and management. Battery energy(More)
In this paper, a novel approach is proposed to solve the day-ahead multi-objective thermal generation scheduling problem. The proposed method combines the principles of Non-dominated Sorting Genetic Algorithm-II (NSGA-II) with problem specific crossover and mutation operators. Heuristics are used in the initial population by seeding the random population(More)
Battery Energy Storage Systems (BESS) can be used for peak load shaving and load leveling apart from other potential applications in low voltage unbalance distribution networks. This paper proposes a simple approach for phase-wise day-ahead dispatch of BESS with the main objective of peak load shaving and secondary objective of load leveling. The first(More)
Outage detection is the first and foremost step in the electric power distribution outage management system (OMS). Unplanned outage detection is very important for improving the distribution system reliability and accessibility. Traditionally, customers' trouble calls are the primary source of outage notification. However, customers report only one third of(More)
Distributed renewable energy resources (DER) based power generation has gained much attention in recent years as conventional power generation units are facing problem like fossil fuel depletion. The hybrid AC-DC microgrid not only allows connection of variable distributed AC and DC resources to utility but also reduces multiple conversions in individual AC(More)
Due to the significant contribution of air-conditioning load towards total energy consumption in residential buildings, accurate modelling and forecasting of such load is key to effective demand-side energy management programmes. This paper suggests a data driven framework for 15 min-ahead AC load forecasting based on modern machine learning techniques that(More)