Grid-connected Hybrid Energy System Research Articles

Techno-economic optimization of a hybrid energy system with limited grid connection in pursuit of net zero carbon emissions for New Zealand

As New Zealand moves towards net zero carbon emissions by 2050, multiple factors must be considered including increased electrical load due to electrification, variability of renewable energy generators, required storage capacity, system economics and limitations on grid transmission capacity. Complex and region-specific interactions between the various design choices involved are likely to require an understanding of a range of optimal and near-optimal designs for proposed micro-grid systems as opposed to a single optimal point. This work develops a novel multiscale optimization algorithm for optimization from a univariate capacity optimization approach to a multivariate one. This enhanced algorithm is applied to a grid-connected hybrid energy system consisting of local wind and solar generation, battery storage, and a limited grid connection for industrial and residential loads. This analysis is repeated for current 2023 and forecasted net zero 2050 grid conditions. Development of local generation allows for a 36.8% reduction of levelized cost of electricity in the 2023 case and a 38.6% reduction in the 2050 case. This results in a projected reduction of 19920 tonnes of CO2/yr. The algorithm and methodology developed are broadly applicable to optimization of next-generation energy grids.

Power Management Optimization of HES Connected to the Grid-Based IEMS

This paper presents a study of a grid-connected hybrid energy system (HES) consisting of photovoltaic/wind/fuel cell/battery/supercapacitor (SC). The purpose of using SC with the battery is to create a hybrid energy storage system (HESS) with high energy density. To prevent overcharging of the latter, a discharge load was employed (in our case, a resistance). The objectives of this research are to operate the photovoltaic generator and the wind power generator at their maximum power points by applying the perturbation and observation (P&O) technique and the tip speed ratio (TSR) technique, respectively. On the other hand, the energy management of the proposed system aims to achieve an energy balance between the grid and the HES despite climate changes and changes in energy demand to which the system is exposed, and to lengthen the life cycle of the HESS by keeping the state of charge (SOC) within a limited range. This management is accomplished by using a classical energy management strategy. To achieve optimal power management of the proposed system, a new intelligent energy management strategy (IEMS) based on the FLC-FOPI is proposed. A comparative analysis was also conducted between the classical strategy and the proposed strategy. As for the grid-side converter, direct power control based on SOSMC technique (DPC-SOSMC) has been proposed to regulate the flow of active and reactive power according to grid demand based on HRES. To demonstrate the effectiveness of the proposed controllers, simulation results evaluating the proposed system under variable conditions are presented using the Matlab-Simulink platform.

Control Scheme for AC-DC Grid Connected Hybrid Energy System for Power Quality Improvement

Abstract: Renewable electricity assets inclusive of air, solar, water, biomass, and many others. Are crucial for sustainable development and social development, in addition to assembly power wishes through the usage of renewable electricity resources. Complete renewable electricity such as wind strength is needed in the energy device to lessen environmental influences. The project proposes the STATCOM manage plan for grid-connected wind electricity structures to increase strength excellent. The bang-bang controller changed into advanced for STATCOM primarily based at the hysteresis cutting-edge manipulate scheme. STATCOM has been merged with common coupling to reduce electricity excellent problems. The STATCOM manage scheme implemented for the grid related wind strength era machine used to enhance the power quality is simulated the usage of the MATLAB / Simulink inside the electricity device block set. This proposed scheme ensures an increase in energy great in production output.

Comparative Investigation of On-Grid and Off-Grid Hybrid Energy System for a Remote Area in District Jamshoro of Sindh, Pakistan

To meet electricity requirements and provide a long-term, sustainable existence, remote areas need to promote renewable projects. Most of the time, wind and solar power sources are selected as renewable energy technologies to help satisfy some of the power requirements. Alternative approaches should be employed, considering the inconsistent characteristics among those resources, to offer efficient and long-lasting responses. Electricity production needs to be conducted with the help of a wide range of energy sources to be productive and efficient. As a result, the current research concentrates on feasible analyses of interconnected hybrid energy systems for such remote residential electricity supply. To help a remote area’s establishment decide whether to adopt renewable electricity technology, this paper evaluates the techno-economic effectiveness of grid-connected and standalone integrated hybrid energy systems. The electricity requirements for the entire selected remote area were determined first. Furthermore, the National Aeronautics and Space Administration, a national renewable energy laboratory, was used to evaluate the possibilities of green energy supplies. A thorough survey was performed to determine which parts were needed to simulate the interconnected hybrid energy systems. Employing the HOMER program, we conducted a simulation, optimizations, and economic research. Considering the net present cost, cost of energy, and compensation time, an economic comparison was made between the evaluated integrated hybrid systems. The assessment reveals that perhaps the grid-connected hybrid energy system is the best option for reliably satisfying remote areas’ energy needs.

A Novel EA-Based Techno–Economic Analysis of Charging System for Electric Vehicles: A Case Study of Qassim Region, Saudi Arabia

Because of the fast expansion of electric vehicles (EVs) in Saudi Arabia, a massive amount of energy will be needed to serve these vehicles. In addition, the transportation sector radiates a considerable amount of toxic gases in the form of SO2 and CO2. The national grid must supply a huge amount of electricity on a regular basis to meet the increasing power demands of EVs. This study thoroughly investigates the technical and economic benefits of an off-grid and grid-connected hybrid energy system with various configurations of a solar, wind turbine and battery energy storage system for the electric vehicle charging load in the Qassim region, Saudi Arabia. The goal is to decrease the cost of energy while reducing the chance of power outages in the system. This is achieved by using a new optimization algorithm called the modified salp swarm optimization algorithm (MSSOA), which is based on an evolutionary algorithm approach. MSSOA is an improved version of SSOA, which addresses its shortcomings. It has two search strategies to enhance its efficiency: first, it uses Levy flight distribution (LFD) to help individuals reach new positions faster, and second, it instructs individuals to spiral around the optimal solution, improving the exploitation phase. The MSSOA’s effectiveness is confirmed by comparing its results with those of the conventional salp swarm optimization algorithm and particle swarm optimization (PSO). According to simulation findings, MSSOA has excellent accuracy and robustness. In this region, the SPV/WT/BESS-based EV charging station is the optimal option for EV charging stations. The SPV/WT/BESS design has the lowest LCOE of all feasible configurations in the region under study. The optimum values for the LCOE and TNPC using MSSOA are USD 0.3697/kWh and USD 99,928.34, which are much lower than the optimized values for the LCOE (USD 0.4156) and TNPC (USD 1,12,671.75) using SSOA. Furthermore, a comprehensive techno–economic analysis of optimized hybrid systems is assessed by incorporating the grid-connected option. The grid connected system results in optimized values of the LCOE (USD 0.0732/kWh) and TNPC (USD 1,541,076). The impact of different grid purchase prices on the levelized cost of energy is also studied. Our results will assist the researchers to determine the best technique for the optimization of an optimal energy system.

Power Quality Analysis of Fuzzy DVR based Hybrid Solar PV-PEMFC System Under Severe Disturbance

Hybrid Energy System (HES) is becoming popular as it is identified as the most safe, sustainable, and long-term option for energy management. The grid-connected power network is vulnerable to frequent interruptions, which can lead to instability and a huge blackout. Furthermore, the presence of switching devices in industrial and domestic applications causes disturbances such as voltage swell/sag, waveform distortion, interruptions, impulsive voltage, and so on. Dynamic voltage restorer, known as a modern power compensating device, is cost effective, compact in size and can handle more energy capacity than DTSATCOM and UPFC. Hence for addressing the power quality issues in hybrid solar photovoltaic (PV)-proton exchange membrane fuel cells (PEMFC) system, dynamic voltage restorer (DVR) has been designed in this paper. As the fuzzy logic technique can provide flexible solutions in the case of uncertainty, fuzzy logic-based controller has also been employed with DVR to regulate the firing pulses of a PWM generator. Based on the simulation results obtained using fast fourier transform (FFT) analysis in MATLAB/Simulink, the dynamic performance of HES against the most important contingency condition or three phase faults is analyzed in detail. Further, the impact of DVR on power quality improvement under severe fault has also been demonstrated in this research work. On analyzing the total harmonic distortion (THD) values of HES under heavy disturbances, the fuzzy controlled dynamic voltage regulator (FCDVR) is identified as an efficient control mechanism for enhancing power quality in grid-connected HES.

Planning and optimization of sustainable grid integrated hybrid energy system in India

The purpose of this study is to conduct the techno-economic-environmental feasibility analysis of a grid-connected hybrid energy systems, making use of locally renewable resources such as solar, wind, and biomass (pine needles). In the absence of a storage unit, five different configurations are investigated. With the use of a newly invented gaining-sharing knowledge optimization method, a mathematical model for optimum size is developed. The Gaining-sharing knowledge algorithm is based on how individuals learn and distribute information throughout their lives. The results of gaining-sharing knowledge-based model is also compared with the standard software tool, Hybrid optimization of multiple energy resources, and the commonly used optimization techniques Genetic algorithm and Biogeography-based optimization to confirm the effectiveness of the proposed approach. The Gaining-sharing knowledge (GSK) based model performance is found best among all. The grid-integrated biomass gasifier/PV amalgam system is determined to be the most economical with an energy production cost of 5.2 ₹/kWh and it saves 87.9% CO2 per annum when compared to a diesel-only system.

Techno-economic comparative study of grid-connected PV/reformer/FC hybrid systems with distinct solar tracking systems

The purpose of this study is to analyze and compare the techno-economic performance of grid-connected Hybrid Energy Systems (HES) consisting of Photovoltaic (PV) and Reformer Fuel-Cell (RF-FC) using different types of solar PV tracking techniques to supply electricity to a small location in the City of Chlef, Algeria. The PV tracking systems considered in this study include fixed facing south at four different angles (32°, 34°, 36°, 38°), horizontal-axis with continuous adjustment, vertical-axis with continuous adjustment and a two-axis tracking system. The software tool HOMER Pro (Hybrid Optimization of Multiple Energy Resources) is used to simulate and analyze the technical feasibility and life-cycle cost of these different configurations. The meteorological data, consisting of global solar radiation and air temperature, used in this study was collected from the geographical area of the City of Chlef during the year 2020. This study has shown that the optimal design of a grid-connected hybrid PV/RF-FC energy system with Vertical Single Axis Tracker (VSAT) leads to the best economic performance with low values of Net Present Cost (NPC), Cost of Energy (COE) with a Positive Return on Investment (ROI) and the shortest Simple Payback (SP) period. In addition, from the simulation results obtained, it can be concluded that the Horizontal and Vertical Single-Axis Trackers (HSAT and VSAT) as well as the Dual-Axis Tracker (DAT) are not always cost effective compared to the Fixed Tilt System (FTS). Therefore, it is necessary to carefully analyze the use of each tracker to assess whether the energy gain achieved outweighs the overall shortcomings of the tracker.

Feasibility Study of the Grid-Connected Hybrid Energy System for Supplying Electricity to Support the Health and Education Sector in the Metropolitan Area

One of the biggest issues impeding a country’s progress is the lack of power. To overcome this issue, hybrid renewable energy systems (HRES) play an important role. Due to rising consumption and diminishing resources globally, sustainability has recently attracted more attention. Bangladesh has access to renewable energy sources, including solar, micro-hydro, biomass, wind, and others. The objective of this research is to minimize the net present cost (NPC), cost of energy (COE), and CO2 emissions of the suggested electricity network using the Hybrid Optimization Model for Multiple Energy Resources (HOMER) Pro Software. This investigation explores the possible use of a hybridized energy system (i.e., solar, wind, and diesel) with battery storage in Bangladesh’s northern area. Utilizing HOMER Pro software, an optimal grid-connected system is chosen after evaluating the techno-economic viability of several configuration options. For the Rangpur metropolitan region, seven distinct grid-connected solutions with stationary renewable sources are simulated. The HRES is designed to meet demands for hospital, diagnostic, school, and operation theatre loads of 3250.00 kWh, 250.00 kW maximum requirement, and 570.00 kWh, 71.25 kW maximum electricity demand, respectively. Multivariate linear regression (MLR) is used to assess the suggested optimal combination in terms of system size, cost, technical performance, and environmental stability. The findings show that the metric real-time rate (annual) has emerged as the most advantageous option since economic criteria like total NPC and COE are preferred above others.

Impact of Multi-Year Analysis on the Optimal Sizing and Control Strategy of Hybrid Energy Systems

Grid-connected hybrid energy systems (HESs) represent a very promising option for addressing the problem of power outages worldwide. The selection of a suitable optimization approach and operational strategy are important aspects of the optimal design and operation of these HESs. This study aimed to find the optimal grid-connected PV/battery system sizes to supply electricity for a residential house in Karbala, Iraq, using two control strategies, load following (LF) and cycle charging (CC). The optimization was performed using HOMER software with and without the multi-year effects. The comparison analysis was carried out by considering the techno-economic and environmental performance of the feasible systems. The simulation results indicate that optimal configuration is achieved by using the CC strategy. Furthermore, the multi-year module affects the optimal results dramatically. Under the CC strategy, the multi-year effects increase the required PV size from 6 kW to 7 kW and the required number of batteries from 18 to 20, leading to an increase in the net present cost from $26,750 to $33,102 and a decrease in CO2 emissions from 7581 kg/year to 7379 kg/year. The results also show that the optimization results are highly affected by the variations of some critical parameters, such as solar radiation, average load, and battery degradation limits. The achievements indicate the higher effectiveness of the multi-year effects and control strategy on the optimal design of HESs.

Optimal Control of BESS for Improved Grid Integration of the Hybrid DFIG/PV System Using Dual-Layer Adaptive Control

In view of the stochastic nature of wind and solar energy, maintaining quality power in grid-connected hybrid energy system is critical for efficient energy utilization, especially in the presence of non-linear loads. This paper deals with the control and performance assessment of grid-integrated hybrid energy system that comprises of doubly fed induction generator (DFIG) and photovoltaic (PV) system including battery energy storage (BES) as a stand-by supply to meet utility and load demand. In order to maintain power balance and address various power quality issues encountered with hybrid renewable integration along the source and the grid/load end, a dual-layer variable-step size adaptive control is implemented for the grid-interfaced converter of the proposed system. The variable step-size based dual-layer least mean square (LMS) adaptive control functions by extracting weights of various control signals (stator and load current) where the step-size parameter adjusts according to the conditions that limit the maladjustment error and increase the rate of convergence. The DC-link voltage control realized by bidirectional BES control reduces the steady-state error and fluctuations in the voltage. An artificial bee colony (ABC) optimization is adopted for optimal gain tuning of the DC-link voltage controller as a result of which the battery performance and grid-side converter performance is enhanced with the increased power exchange to the grid. The system model is developed in MATLAB/Simulink and controller performance is evaluated for diverse operating conditions including steady-state, unbalanced non-linear load conditions, wind-speed and solar irradiation variation and specified grid power modes.

Risk-averse based optimal operational strategy of grid-connected photovoltaic/wind/battery/diesel hybrid energy system in the electricity/hydrogen markets

The techno-economic advantages of grid-connected hybrid energy system (HES) exploit synergies to improve reliability and economic efficiency while maintaining grid stability. Therefore, this paper proposes a risk-averse optimal operational strategy of grid-connected photovoltaic/wind/battery/diesel HES to participate into two energy markets including electricity and hydrogen markets. The grid company can flexibly trade power into two markets to maximally achieve profits based on price arbitrage. The risk influences of the uncertainties, i.e., photovoltaic/wind generation, and electricity prices on the expected revenue are evaluated with CVaR model. For a better exhibition of seasonal variability effects on HES optimal operation strategy, two typical Spring/Summer days are chosen. The proposed risk-averse optimal operational strategy is formulated as a two-stage mixed-integer linear programming (MILP) model. The results in a Spring day simulation under non-risk situation indicate that the overall expected revenue can be improved 2.74 times larger if considering hydrogen market. Moreover, the optimal operational strategy of hydrogen production is considerably affected by unpredictable wind farm. Sensitivity analysis also validates that the changes of PV/WT curtailment penalty have a profound influence than battery degradation coefficient on the HES expected revenue.

Optimization of a grid-connected hybrid energy system: Techno-economic and environmental assessment

This study aimed to provide sustainable, secure, and clean energy for Tuzla campus of National Defense University Turkish Naval Academy. Research problem was to find technically and economically optimized hybrid energy system consists all or some of solar, wind, biomass, and battery sources in addition to grid and diesel generator of the campus. Greenhouse gas emissions of the optimum solution were calculated for environmental effect analysis. Additionally, the effects of the variables such as solar radiation, wind speed, expected inflation, and electricity unit prices on system were analyzed. The study conducted via Homer software under two scenarios based on legal regulations. As a result, the optimum system in both scenarios is a grid-connected hybrid system consisting of photovoltaics and wind turbines. Results presented reduction in net present cost of energy by 86.2%–90%, unit cost of energy by 92.7%–95.8%, operation & maintenance costs by $862,093–$933,695, emissions by 79%–82%. According to both optimization results and sensitivity analysis, no biomass generator was discovered in optimum solutions. It was also observed that batteries could be in the optimum system depending on economic variables. It is believed that this study, in which solar, wind, and biomass as well as battery, grid, and diesel generator were evaluated together under legal based scenarios, can be a reference for further researches due to its diversity in system components and its scenarios consisting legal aspects. The study also can serve as an example and a guide for other public university campuses.

An integrated framework for feasibility analysis and optimal management of a neighborhood-scale energy system with rooftop PV and waste-to-energy technologies

Hybrid energy systems with renewable energy penetration have become popular solutions to improve energy security and realize the carbon neural target in urban areas. In this paper, a holistic framework is proposed for the sustainable development of a neighborhood-scale energy system integrating rooftop PV and waste-to-energy technologies. Under this framework, potential assessment of local renewable energy, optimization approach, and sensitivity analysis are integrated for the optimal design and management of the hybrid energy system with uncertain analysis. Besides, the economic, efficiency, and environmental performance under grid-connected and off-grid operation modes are compared. This proposed framework is applied to a neighborhood area in Beijing. The results show that the grid-connected hybrid energy system will still rely on traditional energy supply with low cost but great carbon emissions. In the off-grid mode, 11 % of the rooftop area will be encouraged to deploy PV panels, which satisfying 39 % of the total electricity demand. Moreover, although decreasing the PV capital cost, raising the electricity price, and increasing carbon emission penalty cost will stimulate the development of local renewable energy, compulsive renewable energy penetration policy is more effective to promote the traditional energy system transformation and reduce carbon emissions.

A new intelligent approach for size optimization of a renewable energy based grid connected hybrid energy system

AbstractAdopting hybrid power systems to provide access to clean, reliable, and inexpensive energy is necessary for countries like India to accomplish their goals of sustainable development. This work proposes an optimization approach for sizing a grid‐connected hybrid renewable energy system (HRES) that includes photovoltaic, biomass, biogas, and a battery. In this research, a recently developed Aquila optimization algorithm is utilized to evaluate the optimal size of HRES for a cluster of villages near Sarai Jairam, Agra district, Uttar Pradesh, India using the MATLAB software package. The goal of this optimization approach is to reduce the net present cost for HRES while satisfying the operational constraints, including the reliability of the power supply and maximum utilization of the photovoltaic, biomass, and biogas complementary properties. Initially, three HRES configurations in the off‐grid mode were optimized using the suggested Aquila optimization technique. To confirm the findings, the optimization results for the same models of off‐grid HRES were obtained using the harmony search (HS) and particle swarm optimization (PSO) algorithms. The same algorithms were also used to optimize the grid‐connected SPV/biomass/biogas with the battery model of HRES. Finally, the outcomes from the off‐grid models presented above were compared to the grid‐linked model. The grid‐connected configuration which is obtained by the Aquila optimization approach provides an optimal solution with the least net present cos t (NPC) and minimum cost of energy (COE) when compared with HS and PSO. The optimal grid‐connected HRES includes 235 kW of PV, a 10 kW biogas generator, a 64 kW biomass generator, and a 50.40 kWh battery bank. The overall net present cost and the COE are found to be $547 670 and $0.0768/kWh, respectively.

Techno-Economic Feasibility Analysis of Solar PV- Wind Grid-connected Hybrid Energy systems for Electrification in Sultanate of Oman

Sultanate of Oman’s power sector is undergoing a rapid restructuring to involve renewable energy sources as part of the generation system. The present power sector majorly depends on the a-renewable energy source, natural gas for its power generation. CeA central grid system connecting all the provinces of Oman involving renewable and non-renewable energy sources in power generation is initiated and is gaining acceleration. Hybridization and its optimization of energy resources at different locations based on geographical factors, cost of electricity production, greenhouse gas emission, and initial and operating costs involved in the generation is still a major concern for the development of a central grid system. In this paper, the development of an optimal hybrid system for the load profile of the University of Technology and Applied Sciences – Shinas (UTAS- Shinas) is done. The initial study was done to develop load profile data of UTAS- Shinas. The annual Peak demand of the University is 720 kW. Various hybrid and standalone combinations involving renewable and non-renewable options are simulated and analysed with a hybridization software tool, HOMER Pro. Solar PV and wind are the major renewable energy resources, found to have ambient potential in Oman. When a renewable energy system is there in the hybrid system design, a non-renewable energy source can be added as a backup generation system to improve its system reliability. Optimization of the hybrid combinations is required as the cost of electricity generation will be expensive, if a wrong combination is selected. Out of the different hybrid combinations selected, PV- Wind – Natural gas-based hybrid system was found to be the most beneficial system for UTAS- Shinas, after considering Renewable energy fraction of 61.6 % power, which can penetrate to the system, the Net Present Cost (NPC), Cost of Energy (COE), Payback period and Greenhouse gas (GHG) emission control as the constraints for the optimization procedure. The practical implementation is done on campus by taking a sample load and illustrating the project with power sources PV of 3.5kW, wind energy conversion of 1.5kW, and grid connection from Majan Electricity Company with an auto change over the facility.

Adaptive Neuro Fuzzy Inference System Based Intelligent Control for Grid Connected Hybrid Energy System with Improved SEPIC Converter

The primary objective of this study is to meet the energy demands of the power consumer through the implementation of Hybrid Renewable Energy System (HRES) with multiple solar panels and wind turbines. As the photovoltaic (PV) power generation is enveloped with multiple advantageous measures like low maintenance, environmental-friendliness and fuel-efficient, it is significantly preferred in this study. However, the low power conversion quality of PV weakens the overall system and so the DC-DC improved SEPIC converter with magnetic coupling is employed to achieve maximum DC output voltage. In addition, the Adaptive Neuro Fuzzy Inference System (ANFIS) is implemented in this work totrack the maximum power from PV and to maximize the energy efficiency in an optimal manner. The MATLAB Simulink is used to validate the present study with optimal outcomes and the obtained results prove that the present approach delivers lesser THD of 1.00%, which in turn efficiently enhances the overall performance of the system. Thus, the research findings of this system are well suited to be applied as the solution for rectifying the issues in the DC link voltage control and grid compensation or synchronization.

Feasibility and techno-economic analysis of stand-alone and grid-connected PV/Wind/Diesel/Batt hybrid energy system: A case study

In this study, the economic and environmental benefits of stand-alone and grid integration are thoroughly analyzed with different system configurations of a PV/Wind/Diesel/Battery based hybrid energy system (HES) for five different climatic regions using hybrid optimization model for electric renewables (HOMER). A detailed techno-economic study of optimized hybrid systems is further examined by integrating the grid-connected option. The environmental benefits of HESs are discussed. The sensitivity of various sell-back price to the national grid is also investigated. Additionally, the barriers and opportunities of installing such projects in the off-grid regions are discussed. Results indicate that the cost of energy (COE, $/kWh) and the net present cost (NPC, $) of the stand-alone hybrid PV/Diesel/Battery for the Rajshahi region are slightly lower compared to other areas, considering the cost and environmental emissions. The same system in Chattogram shows great potential both financially and environmentally, over the other climatic zones. The grid-connected HES with the sell-back option offers significant cost-benefits (0.07$/kWh), even over the grid tariff (0.10$/kWh). Similar revenues can be attained with the grid-connected PV/Battery-based system as substantial amount of excess energy could be supplied to the grid facilities. In the grid integrated HES, around 45,582 kg-CO2/yr could be saved compared to grid only system, whereas this amount is 32,905 kg-CO2/yr over the stand-alone hybrid PV/Diesel/Battery one.

Electricity Curtailment Cost Coupled to Operation Model Facilitates Clean Energy Accommodation in Grid-Connected System

Electricity transmission in a grid-connected system provides an effective solution to promoting clean energy accommodation. However, with arbitrary determination in current operation models, the clean energy utilization ratio (CEUR) is not satisfactory largely due to the lack of electricity curtailment (the electricity equivalent of clean energy curtailment) cost-dependent optimization. In this study, a curtailment cost-dependent multi-objective operation (CCMO) model was proposed to complementarily operate a grid-connected hybrid energy system, identify optimal CEUR, and thus maximally reduce electricity curtailment. The CCMO model centers on coupling the punishment cost of electricity curtailment with the multi-objective function defined as the total cost of each grid component. The CCMO model was solved to derive the optimal equilibrium solution determined based on multiple non-dominated solutions. A grid-connected hybrid energy system including the Yunnan, Guangdong, and Guangxi Power Grids was used to test the model performance. The results showed that the CCMO model’s CEUR was up to 100% at hourly scale and 96.9% on daily average, which were both significantly higher than those in the current operation models. Furthermore, the CCMO’s optimal equilibrium solution, i.e., respective minimum total cost of each grid component, can also identify optimal transmission schemes of the daily channel utilization to make the peak utilization hours largest.

Pseudo inspired gravitational search algorithm for optimal sizing of grid with integrated renewable energy and energy storage

This study presents proposed Pseudo-Inspired Gravitational Search Algorithm (PI-GSA) for solving complex Economic Dispatch (ED) problem in the power system and Optimal sizing of the components for a self-contained and grid connected hybrid energy system that meets the load demand of a particular village. This method can be scaled according to the need of the system under investigation. From the results obtained, it can be inferred that with the use of local available energy sources, the grid connected mode serves as more economical and reliable choice for the electrification of numerous villages when compared with the stand-alone hybrid energy system. To check the effectiveness and performance of proposed algorithm simulation results for Complex Economic Dispatch (Cases 1) are compared with other methods reported in literature and Optimal sizing of the components for self-contained and grid integrated renewable energy resources (Case 2) are compared with the results obtained from Hybrid Optimization Model for Electric Renewable (HOMER). A qualitative comparison of the obtained result with other standard population based meta-heuristic techniques manifests proposed technique's superiority.