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Generation planning in the power system has been a complex and challenging multi-objective optimization problem. Numerous methodologies have been developed and applied to solve this problem. Still, researchers look forward to further improved methods that can further enhance the outcomes for this problem. This article suggests a hybrid FPA-PPSO scheme that combines the flower pollination algorithm (FPA) and phasor particle swarm optimization (PPSO) algorithm to solve this problem. The suggested FPA-PPSO scheme includes a high search efficiency, balanced local and global search capabilities, etc. which can help in more efficient planning of the generation in a microgrid. To analyze the supremacy of the suggested FPA-PPSO scheme over FPA and PPSO methods, a comparative study using twenty-three benchmark functions is presented. From the analysis conducted from the Friedman test, the suggested method gets a rank of 1.59 which is better compared to PPSO and FPA which get ranks of 2.61 and 3.04 for the twenty-three benchmark functions. Further, the suggested method is tested using four test cases to show its effectiveness in solving the scheduling problem of a microgrid considering renewable energy sources, energy storage systems, and demand response management. The obtained results conclude that the suggested methods show promising performance in planning the generating unit. Using the DRM scheme further helps to efficiently schedule the generation as the utilities save up to $ 25545 more when DRM planning is considered. [ABSTRACT FROM AUTHOR]

With the global consensus to achieve carbon neutral goals, power systems are experiencing a rapid increase in renewable energy sources and energy storage systems (ESS). Especially, recent development of hub substations (HS/S) equipped with ESS, applicable for resolving site constraints if implemented as mobile transformers, is expanding the development of ESS-equipped facilities. However, these units require centralized control strategies considering variability within integrated networks. While studies on electric vehicle charging considering the variability of renewable energy or load are widely studied, ESS management scheme for individual substations requires further optimization, especially considering the state of distributed sources at lower levels and transmission system operators. Thus, in this study, an optimal control approach for ESS located at the connection point of transmission and distribution systems, including further consideration of the loss in distribution lines and the constraints of renewable energy sources is presented. This study attempts to derive proactive control strategies for ESS in HS/S to operate with various distribution networks. By establishing control priorities for each source through optimal operation strategy, a suitable capacity of ESS and its economic benefits for distribution network management can be examined. Validation of the current analysis results is performed by utilizing MATPOWER. By adapting the operational range of design scenarios, diverse distribution systems can be tested against multiple configurations of connected devices. [ABSTRACT FROM AUTHOR]

In the operation and control of power systems, load frequency control (LFC) plays a critical role in ensuring the stability and reliability of interconnected power systems. Modern power systems with significant penetration of highly variable and intermittent renewable sources present new challenges that make traditional control strategies ineffective. To address these new challenges, this paper proposes a novel LFC strategy that employs a cascaded fractional-order proportional integral-fractional-order proportional integral derivative with a derivative filter (FOPI-FOPIDN) as a controller. The parameters of the FOPI-FOPIDN are optimised using a variant of the particle swarm optimization (PSO) in the literature called ADIWACO. The effectiveness and scalability of the proposed strategy are validated by extensive simulations conducted on two- and three-area test systems and performance comparisons with recent LFC control strategies in the literature. The performance metrics used for the evaluation are ITAE values, deviations in the power flows in the tie-lines, and deviations in the frequencies of the control areas with the power systems subjected to diverse load and RES generation disturbances in several experimental scenarios. Governor dead band, communication time delay, and generation rate constraints are considered in one of the scenarios for more realistic evaluation. Again, the controller's robustness to uncertain model parameters is validated by varying the parameters of the three-area test system by ± 50%. The simulation results obtained confirm the controller's robustness and its superiority over the comparison LFC strategies in terms of the above performance metrics. [ABSTRACT FROM AUTHOR]

Globally, grid systems are facing substantial challenges due to the rapid growth in power demand. New technologies equipped by means of smart energy resources are one promising solution to cope with this challenge, leading to microgrid systems. The growing demand to develop the power sector by utilizing alternative energy resources plays an influential role in the advancement of low-voltage DC (LVDC) systems. With the prompt development of LVDC distribution grids, bipolar LVDC distribution topology is becoming a leading and promising solution. Therefore, this review paper represents a comprehensive overview as well as a comparative and critical analysis for the development of novel methods on LVDC grid analysis, control strategy, and protection schemes to solve energy management problems that lead to a futuristic novel solution in the green revolution. [ABSTRACT FROM AUTHOR]

Market power is a dominant feature of many modern electricity markets with an oligopolistic structure, resulting in increased consumer cost. This work investigates how consumers, through demand response (DR), can mitigate against market power. Within DR, our analysis particularly focusses on the impacts of load shifting and self-generation. A stochastic mixed complementarity problem is presented to model an electricity market characterised by an oligopoly with a competitive fringe. It incorporates both energy and capacity markets, multiple generating firms and different consumer types. The model is applied to a case study based on data for the Irish power system. The results demonstrate how DR can help consumers mitigate against the negative effects of market power and that load shifting and self-generation are competing technologies, whose effectiveness against market power is similar for most consumers. We also find that DR does not necessarily reduce emissions in the presence of market power. [ABSTRACT FROM AUTHOR]

This paper estimates the seasonal and zonal CO 2 marginal emissions factors (MEFs) from electricity production in the Italian electricity system. The inclusion of the zonal configuration of the Italian wholesale power market leads to a complete measurement of marginal emission factors which takes into account the heterogeneous distribution of RES power plants, their penetration rate and their variability within the zonal power generation mix. This article relies on a flexible econometric approach that includes the fractional cointegration methodology to incorporate the typical features of long-memory processes into the estimation of MEFs. We find high variability in annual MEFs estimated at the zonal level. Sardinia reports the highest MEF (0.7189 tCO 2 /MWh), followed by the Center South (0.7022 tCO 2 /MWh), the Center North (0.4236 tCO 2 /MWh), the North (0.2018 tCO 2 /MWh) and Sicily (0.146 tCO 2 /MWh). The seasonal analysis also shows a large variability of MEFs in each zone across time. The heterogeneity of results leads us to recommend that policymakers consider the zonal configuration of the power market and the large seasonal variability related to carbon emissions and electricity generation when designing incentives for renewable energy sources expansion and for achieving emission reduction targets. [ABSTRACT FROM AUTHOR]

The economic dispatch of power has evolved, shifting focus from cost optimization to prioritizing emission reduction from traditional fossil-fueled generators. Utilities now integrate renewable energy sources (RES) to mitigate emissions and address fossil fuel depletion. This paper introduces a social network search (SNS) algorithm tailored to address dynamic dispatch challenges in microgrids, with a specific focus on integrating RES such as solar and wind power. Through the analysis of four distinct test cases, the efficiency of the proposed SNS algorithm is rigorously demonstrated. Initially, the study addresses economic load dispatch (ELD), emission dispatch (EMD), and combined economic and emission dispatch (CEED) within an isolated microgrid setting, emphasizing RES integration. Subsequently, a comparative analysis of two CEED methods, penalty price factor (PPF) and fractional programming (FP), is conducted to determine optimal strategies for minimizing generation costs and emissions. Further exploration in test cases 3 and 4 examines the SNS algorithm’s effectiveness in tackling complex and non-convex dynamic dispatch problems by incorporating valve point loading (VPL) effects and ramp rate constraints. The results underscore the positive impact of RES integration on microgrid management and emissions reduction. Notably, RES integration leads to a 5.25% and 5.33% reduction in generation costs for ELD and CEED, respectively, alongside a 5.62% decrease in emissions. Moreover, the results highlight the advantages of the FP method in minimizing pollutant emissions and PPF in minimizing generation costs. Additionally, the simulation and statistical analyses demonstrate that the proposed SNS algorithm consistently yields high-quality solutions, surpassing other implemented and reported algorithms. [ABSTRACT FROM AUTHOR]

World in moving towards renewable energy sources and most of the renewable sources are generating DC output, which is somehow difficult to utilize in AC equipments and transmission to different places. These energy sources are now integrated with the grid using multilevel inverters for their optimal utilization. Power electronics plays a vital role in driving many circuits and make supply favorable as per load requirement. The performance of the inverter is decided by total harmonic distortion, which depicts that the signal should be as close to the ideal sine wave. The THD of the inverter can be reduced by using more switches and creating multilevel in the inverters. These switches ought to be triggered efficiently; therefore different triggering methods are being used for the same. In this research a comparative analysis of two different triggering techniques have been carried out for 7 and 11 level "New modified cascade H bridge multilevel inverter (NMCHB MLI)." These techniques are equal phase triggering and modified sinusoidal pulse width modulation triggering. The simulation of both the inverters has been done in Matlab/Simulink environment. The performance analysis is carried out by total harmonic distortion of both the triggering techniques and found to be within the international IEEE standards. [ABSTRACT FROM AUTHOR]

The electricity cost increase as a result of the increase in the share of renewable energy sources (RES) in the energy system creates economic preconditions for the transition of industrial consumers to electricity supply from their own generating sources. A system of discounts to the price of electricity has been developed for industrial consumers in the German power system. The surcharge for supporting the RES development for basic consumers can be reduced by 95%, and the network charge—by 80%. In this paper, the cost of electric energy is assessed in autonomous and centralized power supply systems for the target structure of generating capacities, providing an increase in the share of RES up to 65% in electricity consumption in the German power system. [ABSTRACT FROM AUTHOR]

In accordance with the energy strategy, the share of renewable energy sources (RES) in Germany's electric energy consumption is expected to increase up to 35% by 2020, 50% by 2030, 65% by 2040 and 80% by 2050. An increase in RES share in the energy system will affect the operating modes of all types of power plants. The structure of generating capacities should ensure the maintenance of electrical modes taking into account the daily and seasonal unevenness of electricity consumption. Currently, the balance of production and consumption in the German energy system in the days with the maximum generation of renewable energy plants is ensured by the export of electricity. [ABSTRACT FROM AUTHOR]

For robust monitoring, control and proper energy management of renewable energy sources (RES), wireless sensing networks (WSNs) are proved to be a vital solution. Since the power system is stepping towards the smart grid system and the use of WSNs provides numerous advantages in terms of economical, reliable and safer transmission of controlling and monitoring signals, with their low cost and easy deployment. This research proposes a new architecture for efficient monitoring, control and proper energy management of smart grid system. The architecture is evolved by taking into account the SCADA system in-conjunction with WSNs as sensor nodes. The data transmission is done though wireless link based on IEEE 802.15.4 security protocol. The WSNs are arranged in multi-hop mesh network for efficient data transmission between sensor and coordinating nodes. A new economical model based on Wireless Switch-yard System is used for integrating RES. Three different scenarios are considered, i.e., with RES, without RES and with both, RES and main grid supply for proper energy management and control strategy. A total of 10.5 kW is connected as smart home load to smart grid system. The State of Charge of battery storage system varies for maintaining the constant DC link voltage at 100 V. The efficacy of proposed model is verified through laboratory setup on Power Hardware-In-Loop system. [ABSTRACT FROM AUTHOR]

Keywords: Energy landscapes; Germany's "Energiewende"; Renewable energy sources (RES); Sustainable development; Transition of energy systems EN Energy landscapes Germany's "Energiewende" Renewable energy sources (RES) Sustainable development Transition of energy systems 1 3 3 12/24/20 20201222 NES 201222 The transition of energy systems toward renewable energy sources (RES) is a key issue for sustainable development. Thus, new energy landscapes will emerge changing energy provision from "energy for space" to "energy from space". Energy landscapes, Germany's "Energiewende", Renewable energy sources (RES), Sustainable development, Transition of energy systems. [Extracted from the article]

This paper focuses on IOT based soft switching boost converter based solar energy applications for smart cities and making cities smarter and greener around the globe. It presents one of the applications of the Internet of Things to design and implementation of a highly efficient boost converter used for powering the Arduino and the Bluetooth device for controlling the switching of the led and buzzer by using smart city applications. The soft switching boost converter is essential to maximize the low-level voltage obtained from the solar board to the enhanced voltage conversion ratio for the efficient electric power generation. In this paper, the three separate methodologies of DC-DC boost converters with additional resonant/snubber circuit and resistive load associated with solar panel modules proposed with maximum power point tracking (MPPT) control. The MPPT is obtained by modified augmented perturb and observe algorithm. IoT helps Smart City(SC) systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. It is utilized to extract the most extreme power from solar panel by controlling the duty ratio of the suggested soft switching based boost converter. In this paper a smart IOT system is used to control and monitoring the effect of reference power variations, parameter values to the voltage control to the converter. The solar panel, boost converter and the MPPT is modeled using MATLAB/SIMULINK environment and reach the power transfer efficiency up to 97%. [ABSTRACT FROM AUTHOR]

This paper presents a software tool that has been developed for optimal configuration of hybrid power systems. These systems can be either interconnected to the main power grid or operated autonomously, and may contain a variety of components, including dispatchable generators (e.g., diesel generators, microturbines, biogas generators), non-dispatchable renewable energy technologies (e.g., wind turbines, photovoltaics), batteries, converters and dump loads. A software tool that optimizes such systems has been developed in MATLAB, using a combination of genetic algorithms and tabu search. The optimal configuration is expressed in terms of minimum cost of electricity (in €/kWh), taking into account operational and component size constraints. The needed input includes weather data (e.g., solar, wind, and temperature time-series), load data, system components data, and general parameters (e.g., project lifetime, discount rate). As a case study, in this paper the tool is used for evaluating an autonomous hybrid power system that includes renewable energy technologies in Chania region, Crete. Moreover, the performance of the tool is investigated for seven additional scenarios of the case study, via sensitivity analysis, studying the effect on the results of the uncertainty of weather and cost data. [ABSTRACT FROM AUTHOR]