This study investigates the effect of distributed Energy Storage Systems (ESSs) on the power quality of distribution and transmission networks. More specifically, this project aims to assess the impact of distributed ESS integration on power quality improvement in certain network topologies compared to typical centralized ESS architecture. Furthermore, an assessment is made to see if the network topology in which an ESS position supports its ability to restore node voltage magnitude within acceptable ranges. The power quality of a benchmark interconnected distribution and transmission network was determined using NEPLAN software. Following that, twelve variants of the benchmark were modeled, each with a different ESS integration architecture and (or) topology. Their power quality performance was compared to that of a benchmark network in addition to several cross analyses to determine the relative impact on power quality within the context of their respective ESS integration methodologies. The findings of this study buttress the understanding that the distributed ESS integration architecture within the distribution network topology, where the majority of consumer loads are connected, provides the strongest case for voltage magnitude power quality compensation, as required by the UK Electrical System Grid Code’s 5% rated node voltage compliance processes regulation.

With the increase in the complexity of the topology of transmission and distribution systems, associated with the predictability in the management of the dispatch of prosumers, new techniques for state estimation, and application of metaheuristics are necessary. In the current work a pilot project in Greece that addresses the difficulties of congestion and balancing management that system operators face in the renewable energy sources era, in accordance with the OneNet’s architecture is described. Available resources of grid’s flexibility are identified, and the implementation of an integrated monitoring system based on weather conditions with an energy control and dispatch system in the Greek electricity grid is addressed. The document suggests that flexibility resources will derive through predictions that have been improved and efficient forecasts from increased spatial resolution Numerical Weather Predictions and integration of Artificial Intelligence preventing the power system of entering dangerous topological or operational states.

This paper mainly dealt with the technical and economic feasibility of an off-grid hybrid power generation system for a remote rural Turtuk village of Ladakh, located in the northern part of India. The study showed that the proposed configured renewable integrated hybrid system, using Hybrid Optimization of Multiple Energy Resources (HOMER) software, efficiently met the energy demand, exhibiting optimum performance with low investment. The proposed PV(115 kW)/Wind(1 kW)/Battery(164 strings of 6 V each)/DG(50 kW) hybrid system was a highly commendable, feasible solution preferred from a total of 133,156 available solutions resulting from HOMER simulations. The net present cost and energy cost of the proposed configuration were $278,176 and $0.29/kWh, respectively. The proposed hybrid configuration fulfilled local load, with 95.97% reduced dominant harmful carbon dioxide emission, as compared to the sole us of a diesel generator power supply system. The technical performance of the hybrid system was ensured, with advantages including the highest renewable penetration and least unmet load. Furthermore, the analysis exclusively evaluated the impact of the system’s economic parameters (namely, its expected inflation rate, nominal discount rate, and project lifetime) on the net present cost and cost of energy of the system using a noble single fix duo vary approach.

In this paper a realistic medium voltage (MV) network with four different distributed generation technologies (diesel, gas, hydro and wind) along with their excitation and governor control systems is modelled and simulated. Moreover, an exponential model was used to represent the loads in the network. The dynamic and steady state behavior of the four distributed generation technologies was investigated during grid-connected operation and two transition modes to the islanding situation, planned and unplanned. This study aims to address the feasibility of planned islanding operation and to investigate the effect of unplanned islanding. The load sharing islanding method has been used for controlling the distributed generation units during grid-connected and islanding operation. The simulation results were validated through various case studies and have shown that properly planned islanding transition could provide support to critical loads at the event of utility outages. However, a reliable protection scheme would be required to mitigate the adverse effect of unplanned islanding as all unplanned sub-cases returned severe negative results.

The limited availability of fossil fuels such as coal and increasing air pollution levels due to the burning of coal have pushed the trend of generating electricity from fossil fuels to generating it from locally available renewable resources. It is expected that the cost of electricity will decrease when locally available renewable resources are used. In this paper, it was proposed to commission a solar PV system in a part of an academic building of SRM IST University. The present study is an effort in-line with many initiatives taken up by the Indian Government. The performance index of solar PV system was analyzed. Supporting data were obtained from the NASA PDAV tool and then techno-economical analysis was carried out on HOMER. The average performance ratio and capacity factor of the solar PV system were obtained as 64.49% and 14.90%, respectively. For the optimal configuration, the net present cost and the levelized cost of electricity are $639,981 and $0.34 per kWh, respectively. As per the estimation, there will be no air pollution due to the proposed configuration, whereas if only a diesel generator is commissioned, then 200,417 kg of carbon dioxide will be emitted annually.

A method for applying combinatorial optimization algorithms to Energy Storage System (ESS) scheduling is presented in this paper. Scheduling is essential for the integration of ESS in electrical networks at grid level or at consumer level to achieve the objectives of integration such as constraint management or energy cost reduction and for efficient storage dispatch. It also shows that for a time-of-use (ToU) tariff scheme based on the shape of the demand profile with higher prices tied to peak periods, effective load-leveling, and peak demand reduction always leads to energy cost reduction. While other methods usually require more information such as generation cost curves or ToU tariffs to schedule ESS, the proposed method uses only demand profile information and ESS parameters to achieve load-leveling and peak demand reduction and also considers the entire optimization time horizon. This is done by combining heuristic bin packing and subset sum algorithms with specific modifications to the standard forms and through transformations. A case study is presented in which the algorithm is used to schedule household ESS with repurposed electric vehicle batteries and the results are compared to a demand response scheme on the same setup.