With the rapid growth of electricity generated by renewable power sources, especially solar photovoltaic (PV) and wind, both of which are highly variable and intermittent, attaining CO2-neutral power generation (which is achieved only if the CO2 generated from manufacturing and operation of renewable generation is offset by carbon removal) at utility level appears to be both a tantalizing prospect and a formidable challenge. When renewable energy sources (RES) account for a large portion of the power supply, their inconstant availability presents challenges to power grid service, leading to RES curtail and loss of efficiency of thermal power plants, which then are often operated at part-load as changing back-up power. Barelli et al. (2015) examined this factor in depth in relation to the Italian electricity generation mix from 2008 to 2012, and noted that the function of thermoelectric plants, in particular, had moved from base-load to fluctuating backup capacity. The main consequence was an increase in both energy consumption and wear-and-tear costs as a result of lower performance service. Tarroja et al. (2012) have produced metrics to assess the impact of intermittent renewable generation on the electric load demand that must be balanced by dispatchable generation resources, allowing for a more thorough analysis of the overall effects of allowing high renewable penetration levels. The metrics are concerned with the sizing, allocation, and alignment of load balancing services in order to meet load demand in a timely manner. For the state of California, they found that at high penetration rate of RES, the balancing generator fleet had low power factors. Surplus generation occurred at penetration rate above 45% with no uninterruptible base load. Set time-of-use electricity pricing became ineffective as the frequency of regular maximum and minimum load points became increasingly unpredictable.
Flores et al. (2016) examined the issue of how to choose electricity generating technologies for a decentralized energy generation system based on local renewable sources in a developing country's rural area (six municipalities in Western Honduras). Rather than constructing a high-reliability electricity generation system with high-quality power, the goal of this work was to give the fundamental configuration of an energy mix for a rural area with low-resolution energy data. The technologies were chosen using a non-linear integer programming methodology that aimed to reduce the levelized cost of power (LCOE). The model takes as inputs, data on energy resources, conversion technologies, the Honduran economic framework, the research area's electricity demand, and the cost of energy storage. Solar photovoltaics, wind turbines, biomass direct combustion with a steam turbine, and biomass gasification with a gas engine are among the energy resources evaluated, while electricity generation technologies considered include solar photovoltaics, wind turbines, biomass direct combustion with a steam turbine, and biomass gasification with a gas engine. As functions of electricity capacity, three case studies were proposed: off-grid, mini-grid, and grid-connected. The model outputs for each case study include the electricity supply share for each technology, the LCOE, and the number of power plants with the relevant power capacity needed to meet the study area's electricity demand. This work might be used as a starting point for early feasibility evaluations of renewable energy electrification projects in other rural areas of Honduras or other developing countries.
Ray et al. (2018) examined the possibility of hybridization of locally available diverse renewable resources to deal with intermittency of these resources. A multi-criteria optimization using cuckoo search algorithm for simultaneous best combination of economy, land use and greenhouse gas (GHG) emission was carried out for polygeneration with three utility outputs, namely, electricity, heat and high calorific value gas. Using data for a small hilly village of India with mostly poor people, they found the levelized cost of electricity at 100% reliability of power supply to be 0.1 USD/kWh. Dawoud (2021) studied the possibility of energy supply to the Egyptian city of Hurghada from a mixture of four separate hybrid renewable sources: solar photovoltaics (SPV), wind turbines, diesel engines, and storage batteries. HOMER software was used to conduct the simulation results, optimization, and modelling procedures. The combination of SPV-wind-diesel-battery source was found to have less cost of energy of 0.275$/kWh compared with the cost of 0.36$/kWh for the SPV-diesel combination.
Hydrogen is a potential energy carrier for renewable energy (Martin et al., 2020) as it has a clean emission when consumed. To implement hydrogen energy system in large-scale, a comprehensive hydrogen supply network should be built to supply the required hydrogen with optimal infrastructure arrangement. Mah et al. (2022) investigated the viability of an integrated hydrogen-electricity supply chain for the region of Johor, Malaysia through a spatial optimization framework that integrated geographical information with mathematical modeling for the design and optimization of a photovoltaic-based hydrogen-electricity supply chain. The proposed framework allowed the concurrent targeting of vehicle fuel and electricity demands as well as the identification of suitable locations for supply chain infrastructures. The case study results show that the minimum cost of hydrogen-electricity supply chain is about 14.9 billion USD/y assuming two days of autonomy, and that the cost of battery constitutes 43% of the total supply chain cost. When the days of autonomy is eight and above, hydrogen storage is preferred and electricity is regenerated from hydrogen using fuel cell.
There have been several recent studies of possibility of 100% RES at a regional level. Khoie et al. (2019) investigated energy mix strategies for regions of northern half of United States to go 100% renewable (solar PV, onshore wind, hydro, biomass and geothermal) and concluded that the West Coast, Mountain and Middle West regions could do so by around 2040 while Lake states, Mid-Atlantic, South Atlantic and New England states would not be able to reach this target even by 2050. Dong et al. (2020) in their paper have shown that interconnecting intermittent renewable energy (IRE) and nuclear to provide clean energy reliably and continuously on a wide scale is appealing due to their complementarity. The IRE can be integrated more easily by actively modifying the electric power output of nuclear cogeneration plants (NCPs), which results in regular redistribution of main steam to the turbine and cogeneration process.
National power, heating, cooling, and transportation systems must all achieve zero emissions in the future. To ensure the reliability of energy supply in 100 percent renewable energy systems, a large number of backup power plants as well as large-scale energy storage capacity are needed. Electricity can be partially converted into hydrogen, which can then be transported through pipelines, stored in large amounts in underground salt caverns to avoid seasonal effects, and used as electricity storage or a renewable transportation fuel. Oldenbroek et al. (2021) show how hydrogen-fueled fuel cell electric vehicles parked and connected to the grid in Denmark, Germany, the United Kingdom, France, and Spain could balance 100 percent renewable energy, heating, cooling, and transportation systems at the national level. Kumar and Jayanti (2021) have examined the possibility of the southern states of India going 100% renewable through distributed photovoltaic power generation (DPPG) coupled with existing wind, hydro and nuclear power sources. Cecen et al. (2022) present a SWOT (strength, weakness, opportunity and threat) analysis of the development of the DPPG sector in Turkey.
Load management under dominant renewables contribution to power generation has received quite a lot of attention in recent years. Ogunjuyigbe et al. (2015) offer a load allocation management system based on a set of rules implemented by the Modified Mild Intrusive Genetic Algorithm (MMIGA), which will fit the house owner's economical solar system inverter. In both abundant and insufficient energy supply, the algorithm optimized load allocation in real time. MMIGA is then used to intelligently generate a series of bits, which are subsequently implemented by the hardware according to a set of rules. A daily load discrimination profile is first developed, followed by the construction of a priority matrix for the relevant time of day. The suggested algorithm achieves the goals of being cost-effective, intelligent, and simple to use, and it can be applied to a variety of load profiles.
Electrical energy storage is often suggested as a key to the mismatch between supply and demand tendencies of erratic renewable electricity sources. However, the efficacy and utility of storage can vary depending on the situation. At a meso-level, residential sector background, the study by Laugs et al. (2020) offers a theoretical viewpoint on the merits of electrical energy storage combined with devolved supply systems consisting of solar PV and wind power. They used a balancing model based on Dutch weather data to couple demand and supply trends and determine the resulting loads under various scenarios. The results of the model show noteworthy differences in storage efficiency between solar PV and wind power, as well as robust diminishing-returns effects. Small storage capacities can help reduce excesses in over-dimensioned supply systems as well as scarcities in under-dimensioned supply systems. However, total imbalance removal demands large storage capacities.
Liu et al. (2020) have projected a power system electricity frequency control technique for a 100% renewable energy inaccessible power grid using model predictive control (MPC). Large capacity PV generation and storage batteries were presented based on an original 100 percent renewable energy power system as the price of PV panels and storage batteries fell considerably in these years. To match consumption and generation, MPCs were designed for each model (photovoltaic generation, wind turbine, storage battery, fuel cell and seawater electrolyser). In addition, demand response (real-time pricing) was used in this structure to lessen the load frequency by regulating the controllable loads.
Power systems that rely heavily on sporadic renewable electricity production, such as wind and solar, require a high level of suppleness in both power generation and demand. Heat pumps and combined heat and power units in district heating systems, as well as thermal storages, have all been scrutinized in the past for their ability to recover the energy system's adaptability. These technologies must be handled in a non-standard manner with swapped merit-order when used for power balancing. Monie et al. (2021) propose that a residential area could form a locally operated entity, such as a virtual power plant, that offers power-balancing services to a national power system. The theory is tested in a case study in Sweden, where the local agency consists of a combined heat and power plant, heat pumps, a local heat distribution system, and thermal storage. A simulation of the energy balances in the system was run with storage size optimization. The heat pumps devour all of the system's power excesses, according to the results. The mutual heat and power unit covers 43% of the annual load and 21% of the electricity peak load. Inter-seasonal thermal storage, it is concluded, is important for the system's versatility. Huge energy surpluses, when converted to heat and stored, restrict the virtual power plant's ability to use the combined heat and power unit for power balancing later. Despite this, a local virtual power plant may provide enhanced flexibility to the power grid by providing power-balancing services.
Future grid systems can be more energy efficient and stable if proper energy conservation strategies and renewable energy resources are implemented. Sarkar et al. (2020) have suggested a microgrid architecture and demand side management (DSM) technique for home energy management. Household loads were moved on the basis of price-based tariffs such as flexible and time-of-use tariffs to reduce peak load, peak to average, and energy costs. The binary particle swarm optimization algorithm was used to simulate the situation. According to simulations, DSM implementation resulted in a substantial reduction in peak loads and a trade-off between renewable resources and peak loads. By paying less for power and selling the surplus electricity to the grid, renewable energy incorporation with DSM could be a promising solution for significantly lowering overall electricity costs for households. Golla et al. (2021) presented a new control technique for a solar photovoltaic (PV) integrated universal active power filter (PV-UAPF). PV integration at the DC link will also lower demand on the supply system, easing the load on the utility grid. As a result, the suggested system combines the advantages of clean energy generation with improved power quality. The system's performance is further tested in the hardware configuration under various disturbances such as voltage sag/swell, load distortion, and PV power variation.
Boddapati & Nandikatti (2020) examined the impacts of the Government of India's 9-minute pan-India voluntary lights-off policy, which was planned and implemented in April 2020, on the National Grid, as well as the efforts taken to ensure grid stability during the event. In the nation's fight against the epidemic, the policy was a symbolic expression of public support with frontline healthcare and emergency workers. The technique used by the Indian power industry to control the grid during the nine-minute incident was discussed in this article. Variations in grid characteristics such as frequency, voltage, and load are assessed at all dispatch centres before, during, and after the nine-minute period, and the generation plan followed was displayed, along with real-time findings. This case study presents an overview of power system management, which includes strategic generator scheduling across the country to address abrupt and massive demand decreases on the power system.
Thus it can be said that integration of renewable energy for local/ regional power supply has received significant attention in recent years from different perspectives. While the potential for 100% renewable power generation has been studied at a regional scale from an overall energy balance point of view, studies on utility-scale balancing of consumer demand with hybrid power sources have not been reported. Specifically, the issue of energy storage requirements and possible technological solutions has not been addressed in a comprehensive way. Against this background, we propose a heuristic model that integrates (geographically) distributed and diverse power sources with geographically spread-out power consumption centres and diverse electrical energy storage systems through transmission and storage loss models. For a regional electricity grid, the model computes, over a given day, the minute-by-minute power demand from and power generation in each district, extracts matching power from a hierarchy of power sources so as to minimize transmission and storage losses, and stores excess power in a variety of power storage options. The model can thus generate useful insight into planning for regional establishment of power generation/ storage systems to meet CO2-neutral electricity demand at power grid level.