The contribution of solar photovoltaics (PV׳s) in generation of electric power is continually increasing. PV cells are commonly modelled as circuits. Finding appropriate circuit model parameters of PV cells is crucial for performance evaluation, control, efficiency computations and maximum power point tracking of solar PV systems. The problem of finding circuit model parameters of solar PV cells is referred to as “PV cell model parameter estimation problem,” and is highly attracted by researchers. In this paper, the existing research works on PV cell model parameter estimation problem are classified into three categories and the research works of those categories are reviewed. Based on the conducted review, some recommendations for future research are provided.

Parameter estimation of solar photovoltaic (PV) cells: A review

Usually, consumers experience power failures due to problems in the distribution systems. Distribution systems have evolved to an extent where smart technologies are needed for their smooth operation. Network reconfiguration is one of the functions of distribution automation that improves the performance of the system by altering the structure of the distribution network. In literature, different network reconfiguration problems have been resolved with various methods. However, the active power loss minimisation problem is considered most of all, because if these losses are less than the standard, the distribution companies can benefit monetarily. In addition, during the last few decades, distribution system reliability has been developed to provide interruption free electricity services. With improved system reliability, power distribution companies can save the expenses that are spent on a distribution system's maintenance and operation after a power failure. This paper thus gives a general background, literature review and comparative analysis of methods used for network reconfiguration for reliability enhancement and loss minimisation in the distribution network, so that new researchers can easily read the literature, especially in this area. Moreover, this is the first effort to collect the previous and the most recent research works on the field of reliability of distribution system through network reconfiguration. Therefore, this work will serve as a one stop source for the guidance of the new researchers in this field.

Review on reliability improvement and power loss reduction in distribution system via network reconfiguration

Distribution system optimisation is defined as satisfying the demand of the system in the most economical, reliable and environment-friendly way while all the related operational or geographical constraints are met. In the case that the future load of the system is intended to be met, the problem is also called “expansion planning” problem. In this paper, the existing researches on distribution system optimisation problem are reviewed from the viewpoint of their used optimisation algorithm, used objectives, used decision variables, load model, case study, planning type and planning period. This review found that although diverse optimisation algorithms have already been applied to distribution system optimisation problem, developing efficient algorithms with the ability of escaping from local optima and finding near-global solutions is required. In particular, development of diversity enhancement strategies for metaheuristics and applying them to this problem seems to be fruitful. This review also found that some aspects of distribution systems such as deregulation and demand side management have not been taken into account in modelling of distribution system optimisation problem.

Optimisation of electric distribution systems: A review

Optimal simultaneous day-ahead scheduling and hourly reconfiguration of distribution systems considering responsive loads

This paper proposes a two-stage energy management scheme (EMS) for AC–DC hybrid smart distribution systems (DSs). The proposed EMS is formulated as a multi-objective optimization problem to minimize the DS operation costs and energy losses. The proposed EMS is achieved in two stages. In the first stage, a network reconfiguration algorithm determines the optimal day-ahead reconfiguration schedule for a hybrid DS. In the second stage, a real-time optimal power flow algorithm determines the real-time operational schedule of the energy resources. This paper also introduces a new linearized power flow model for AC–DC hybrid DSs. This new model facilitates the formulation of the first-stage algorithm as a mixed-integer linear programming problem and the formulation of the second-stage algorithm as a linear programming problem. The proposed two-stage EMS was tested on a case study of a hybrid DS that included different types of loads and distributed generators. The results demonstrate the efficacy of the proposed EMS: the optimal day-ahead reconfiguration schedule was successfully obtained in the first stage, and the proper and optimal real-time operation was achieved in the second stage.

Energy Management of AC–DC Hybrid Distribution Systems Considering Network Reconfiguration

Distribution system reconfiguration for loss minimization using modified bacterial foraging optimization algorithm

Nowadays Distribution networks are growing in complex due to the increase in power demand, variation in load and different kinds of load. So these leads to degradation of quality power to the consumers. The efficient Operation of Distribution networks can be achieved by reconfiguring the network for reducing the line losses and for improving the system reliability. IHSA (Improved Harmony Search Algorithm) provides a better solution as it looks for optimal positions in the distribution system to switch on/off tie lines for optimal power flow and thus reduces the distribution power losses. These tie line switches can be used as emergency service restoration after a fault in the feeder. Autonomously controlling the sectionalizing switches in the distribution feeder makes possible to perform emergency service restoration in a shorter time.

Reconfiguration of distribution system for loss reduction using improved harmony search algorithm

Photovoltaic (PV) energy is becoming a more common way to produce clean, renewable energy. The PV modules with lengthy strings will be affected for the shading effects, resulting in a huge decrease in the final output power. To counter this, distributed maximum power point monitoring has been suggested, in which individual DC-DC converters are connected to a central DC-DC converter in which each PV module to get the most power out of it. To achieve the opti-mum power output, Distributed MPPT (DMPPT) is used and it compensates for shading effects and module mismatching issues.

Distributed MPPT Configuration for Improving Solar Energy Production

WSN (Wireless Sensor Network) is a unique variety of temporary type of Local area networks that are highly distributed self-organized systems. There is a detailed collection of various sensor nodes which are vastly deployed throughout the environment. Sensor node is a very small electronic device that is attached to a sensor network. They have an uncomplicated working mechanism that collects the data from any physical movement of an event that occurs or event query that is time driven. The notable feature of the sensor network is data gathering. Each sensory node can gather data, analyse that information and make that information to move to the location that is a destination. Routing algorithms play a vital role in making routing decision that delivers the packet to the exact point through optimal route. Since there is an energy restriction in WSNs, the energy related economisation becomes the most avoidable objective of various routing protocols. routing protocols of various sensor networks is reviewed and presented in this paper which provides a clear classification of various categories and comparison of the various methods.

A Review Paper on Various Energy Saving Techniques in WSN

Artificial Intelligence (AI) approaches, such as the big data, mobile computing, and Internet of Things (IoT) have become more common in the computer science area in recent years. It is critical to properly manage resources in order to maintain service quality, service level agreements, and the system's overall availability. AI may be used to address the needs of cloud resource management, and this study examines and evaluates several approaches. Fog computing systems, intelligent cloud computing systems and edge-cloud systems are all types of AI-based cloud resource management systems that have been reviewed in this contribution. In this research, an intelligent resource management method that controls mobile resources by monitoring device states and projecting their future stability is proposed. We look at the possibility of using our suggested resource management system to a variety of cloud-based platforms.

K. Rajalakshmi

Papers

Distribution system reconfiguration for loss minimization using modified bacterial foraging optimization algorithm

Reconfiguration of distribution system for loss reduction using improved harmony search algorithm

Distributed MPPT Configuration for Improving Solar Energy Production

A Review Paper on Various Energy Saving Techniques in WSN

Analysis of the Requirement and Artificial Intelligence-based Resource Management System in Cloud