Minimum Storage Capacity Research Articles

Techno-financial analysis of 100% renewable electricity for the South West region of the UK by 2050

In the UK, the transition to 100% Renewable Energy Systems is a critical strategy in addressing climate change, aligning with the UK government's 2050 net-zero objective. This study explores the potential for such a transformation within the South West region of the UK by 2050. EnergyPLAN16.2 software was utilised for scenario modelling and the fmincon algorithm in MATLAB for optimisation analysis. The focus was on two scenarios involving hybrid renewable energy systems incorporating onshore wind, solar, offshore wind, and two energy storage systems which are lithium-ion battery energy storage and hydrogen fuel cell energy storage. The optimisation process entailed two stages: determining renewable energy configurations for cost-efficient coverage of annual electricity demand and computing the minimum energy storage capacity to ensure a constant power supply. The results suggest an optimal configuration of 4,460MW onshore wind, 9,880MW solar, 6,982MW offshore wind, and 2,273,662MWh of lithium-ion battery energy storage for 100% hybrid renewable energy systems in the South West region of the UK in 2050. This configuration achieves the lowest annual cost of 3208 M£/year, with a balanced wholesale electricity price ranging from 4.3p/kWh to 6.6p/kWh and a levelized cost of energy of 6.44p/kWh. Furthermore, hydrogen fuel cell storage systems can be another alternative, however, the present study showed it is not economical enough compared to lithium-ion battery storage systems. This research broadens the understanding of hybrid renewable energy systems implementation in large regions, offering valuable insights for sustainable energy planning in the South West region of the UK.

Re-evaluation of CO<sub>2</sub> storage capacity of depleted fractured-vuggy carbonate reservoir

<p>Confronting the dual crises of energy supply-demand imbalances and climate change, carbon neutrality emerges as a vital strategy for China in mitigating resource and environmental constraints, while fostering technological advancement and sustainable growth. In the context of extensive hydrocarbon exploitation, the CO<sub>2</sub> storage capacity within depleted oil fields could be significantly underestimated in comparison to the prevalent practice of saline aquifer sequestration. In this study, we employ both theoretical and computational models to investigate the temporal (from microseconds to millennia) and spatial (spanning pore, Darcy, and hybrid scales) dynamics of CO<sub>2</sub> trapping mechanisms in post-depletion carbonate reservoir with fractured-vuggy systems. The multiscale storage efficiency factor is obtained from simulation results and substituted into the existing analytical models for calculating CO<sub>2</sub> storage volume in field cases, reappraising the carbon sequestration potential of fracture-vuggy carbonate. Drawing from comparative results, we discern that depleted carbonate can dissolve and mineralize more CO<sub>2</sub> than saline layer, despite the storage volume can be considerably less. The annual storage capacity per well of two geological systems are comparable. Under unfavorable geological conditions, the minimum unit storage capacity of carbonate reservoir exceeds that of saline aquifer. The study's discoveries offer fresh perspectives on reliable and efficient CO<sub>2</sub> geological storage, contributing to the reduction of atmospheric carbon emissions and advancing the utilization of underground resources and global energy transformation.</p>

Stable power supply system consisting of solar, wind and liquid carbon dioxide energy storage

Renewable energy is becoming the main subject of energy consumption with the accelerating transformation of energy structure. The renewable power supply systems sourced by wind and solar energies have attracted wide attention as they are of great significance to regions that are rich in renewable energy. In this study, the stable power system consisting of solar, wind and liquid carbon dioxide energy storage is proposed for the sake of meeting user electricity load. Thermodynamic and economic performance of the proposed systems with different application scenarios is analyzed and some interesting findings are summarized. The round trip efficiency and energy density of the liquid carbon dioxide energy storage system are 58.34 % and 23.41 kWh/m3, respectively. The start hour of dispatch can cause obvious influence on the energy storage capacity and there is an optimal dispatch start time to achieve the minimum energy storage capacity. The overall energy efficiency of energy storage-aided power system including solar and wind powers is much higher than that of the single sourced system. The energy efficiency of the solar-wind-LCES system is 94.61 % while it is only 80.31 % and 76.29 % for the wind-LCES and solar-LCES systems, respectively. The introduction of the liquid carbon dioxide energy storage into the renewable power supply system can greatly reduce the electricity purchasing investment.

Sizing Batteries for Power Flow Management in Distribution Grids: A Method to Compare Battery Capacities for Different Siting Configurations and Variable Power Flow Simultaneity

Battery energy storage (BES) can provide many grid services, such as power flow management to reduce distribution grid overloading. It is desirable to minimise BES storage capacities to reduce investment costs. However, it is not always clear how battery sizing is affected by battery siting and power flow simultaneity (PFS). This paper describes a method to compare the battery capacity required to provide grid services for different battery siting configurations and variable PFSs. The method was implemented by modelling a standard test grid with artificial power flow patterns and different battery siting configurations. The storage capacity of each configuration was minimised to determine how these variables affect the minimum storage capacity required to maintain power flows below a given threshold. In this case, a battery located at the transformer required 10–20% more capacity than a battery located centrally on the grid, or several batteries distributed throughout the grid, depending on PFS. The differences in capacity requirements were largely attributed to the ability of a BES configuration to mitigate network losses. The method presented in this paper can be used to compare BES capacity requirements for different battery siting configurations, power flow patterns, grid services, and grid characteristics.

Effects of leaf type, litter mass and rainfall characteristics on the interception storage capacity of leaf litter based on process simulation

Forest litter plays an important role in the hydrological process of an ecosystem, but the mechanism of interception is not well understood and has not been fully evaluated. We conducted a process-based experiment under five simulated rainfall intensities. We directly quantified the interception of leaf litter and determined the effects of litter mass (MA), rainfall characteristics (RI) and leaf type (SP) on the interception of six common subtropical tree species, including two coniferous (Cunninghamia lanceolata (Lamb.) Hook. and Pinus massoniana Lamb.) and four broadleaf deciduous (Phoebe bournei (Hemsl.) Yang, Schima superba Gardn. et Champ., Liquidambar formosana Hance and Cinnamomum camphora (L.) Presl) species. The results demonstrated the following. (1) The interception process of litter can be divided into three phases: the wetting phase, the saturation phase, and the postrainfall drainage phase. The first phase of which arrived approximately 95% of the maximum interception storage (Cmax) and the duration was longer in broadleaf species than in coniferous species. This phase was significantly different among the species and rainfall characteristics, but it was not affected by litter mass. (2) Cmax and the minimum interception storage capacity (Cmin) of litter were not significantly different between the two forest types, but among the six species, especially between P.bournei and each of the two coniferous species, these values showed the greatest differences. (3) Cmax and Cmin increased significantly with litter mass and rain intensity. (4) Based on commonality analysis, the interaction between MA and RI largely outweighed the other variables in terms of their contribution to Cmax; however, MA surpassed all the other variables in its contribution to Cmin. We also found that the effects of the individual variables on Cmax and Cmin as well as their interactions, were significantly different; the three most influential variables for Cmax ranked in the descending order of their contributions were the interaction between MA and RI (41.07%), RI alone (23.69%), and MA (20.81%), and those for Cmin were MA alone (52.59%), the interaction between MA and RI (25.81%) and leaf types (14.58%). The quantitative and mechanistic explanations regarding the effects of leaf types, rainfall characteristics, litter mass and their interactions on litter Cmax and Cmin presented in this study are expected to increase our understanding of the mechanism underlying litter interception.

Probabilistic Approach to Tank Design in Rainwater Harvesting Systems

Storage tanks from rainwater harvesting systems (RWHs) are designed to provide flow equalization between rainfall and water demand. The minimum storage capacity required to take into account the maximum variations of stored water volumes, i.e., the active storage, depends basically on the magnitude and the variability of rainfall profiles and the size of the demand. Given the random nature of the variables involved in the hydrological process, probability theory is a suitable technique for active storage estimation. This research proposes a probabilistic approach to determine an analytical expression for the cumulative distribution function (CDF) of the active storage as a function of rainfall moments, water demand and the mean number of consecutive storm events in a deficit sub-period. The equation can be used by developers to decide on the storage capacity required at a desired non-exceedance probability and under a preset water demand. The model is validated through a continuous simulation of the tank behavior using rainfall time series from Milan (Northern Italy).

Adaptive Control of Energy Storage Systems for Real-Time Power Mediation Based on Energy on Demand System

The concept of i-Energy as a new smart demand-side energy management system is proposed, which can realize the versatile and efficient control of e-power flows between distributed generators, numerous appliances, and energy storage systems in the home domain, factories, offices, and local communities. The Energy on Demand (EoD) system is proposed, which is the automatic power control and management system that supplies power to home appliances based on the power demand requests issued from the home appliances. The EoD system can guarantee the reduction in total power consumption by implementing a ceiling control while keeping the quality of life (QoL) of the home user considering the limitation of power supply. This paper proposes an adaptive battery storage management and control method based on the EoD system, which we call the “storage-supported EoD system”. In particular, the storage-supported EoD system can handle multiple power generators, including storage batteries. The overall goals of this paper are not limited to the extension of multiple power supplies only; rather, it provides additional contributions, which are (i) extend the existing power consumption control of home appliances and peak demand shift control (i.e., EoD system) by adding a second power source, i.e., a storage battery system; (ii) propose adaptive storage system design and management for the EoD system; (iii) realize minimum storage capacity for large peak power consumption; and (iv) minimize the home user’s discomfort level due to the limited power supply of one power source. The simulation results have shown the effectiveness of the proposed algorithm with a couple of experiments using real-life data in the smart apartment room. Additionally, simulation results are presented to compare and evaluate the proposed system performance with the EoD system.

Feasible Dispatch Limits of PV Generation With Uncertain Interconnection of EVs in the Unbalanced Distribution Network

This paper presents a framework to determine the feasible dispatch limits of solar photovoltaic (PV) generation in the unbalanced distribution network considering the interconnection of electric vehicles (EVs) and associated uncertainties. The proposed framework determines the lower and upper dispatch limits of PV generation considering the worst-case realization of a) the minimum and maximum storage capacity of EVs, b) the minimum and maximum power dispatch of EVs, c) the lower and upper bounds for the arrival and departure times, and d) the available energy at arrival and departure times. The unbalanced operation of the distribution network as well as the uncertainty in the maximum PV generation and demand forecasts were considered. The problem formulation and solution approach are validated using the modified IEEE 34-bus and IEEE 123-bus distribution systems. The impacts of the budget of uncertainty and the vehicle-to-grid operation mode of EV clusters were addressed in the case studies. It is shown that integrating EVs with charging capability will increase the lower dispatch limit or increase the upper dispatch limit of the PV generation. Moreover, the increase in the budget of uncertainty will reduce the difference between the upper and lower dispatch limits by increasing the lower dispatch or decreasing the upper dispatch limit of the PV generation. Finally, it is shown that the vehicle-to-grid capability will reduce the total lower dispatch limit or increase the total upper dispatch limit of the PV generation in the operation horizon.

E&P Notes (November 2021)

E&P Notes (November 2021)

Charge/discharge control of wayside batteries via reinforcement learning for energy‐conservation in electrified railway systems

AbstractThe effective utilization of regenerative power generated by trains has attracted the attention of engineers due to its promising potential in energy conservation for electrified railways. Charge control by wayside battery batteries is an effective method of utilizing this regenerative power. Wayside batteries requires saving energy by utilizing the minimum storage capacity of energy storage devices. However, because current control policies are rule‐based, based on human empirical knowledge, it is difficult to decide the rules appropriately considering the battery's state of charge. Therefore, in this paper, we introduce reinforcement learning with an actor‐critic algorithm to acquire an effective control policy, which had been previously difficult to derive as rules using experts’ knowledge. The proposed algorithm, which can autonomously learn the control policy, stabilizes the balance of power supply and demand. Through several computational simulations, we demonstrate that the proposed method exhibits a superior performance compared to existing ones.

Optimal Energy Storage System-Based Virtual Inertia Placement: A Frequency Stability Point of View

In this paper, the problem of optimal placement of virtual inertia is considered as a techno-economic problem from a frequency stability point of view. First, a data driven-based equivalent model of battery energy storage systems, as seen from the electrical system, is proposed. This experimentally validated model takes advantage of the energy storage system special attributes to contribute to inertial response enhancement, via the virtual inertia concept. Then, a new framework is proposed, which considers the battery storage system features, including annual costs, lifetime and state of charge, into the optimal placement formulation to enhance frequency response with a minimum storage capacity. Two well-known dynamical frequency criteria, the frequency nadir and the rate of change of frequency, are utilized in the optimization formulation to determine minimum energy storage systems. Moreover, a power angle-based stability index is also used to assess the effect of virtual inertia on transient stability. Sensitivity and uncertainty analyses are further conducted to assess the applicability of the method. The efficiency of the proposed framework is demonstrated on a linearized model of a three-area power system as well as two nonlinear systems. Simulation results suggest that the proposed method gives improved results in terms of stability measures and less ESS capacity, when compared with other methods proposed in the literature.

Application of multi yield analysis approaches to reservoir system

Yield is used to characterise the capacity of a water resource. It is a fundamental water-supply planning concept, and an understanding of its attributes is critical for those who participate in water-supply issues. This study tends to carry out firm yield analysis by employing both the accumulated difference method (ADM) and reverse chronology method (RCM) in order to ascertain the minimum storage capacity required to sustain the required yield of kainji reservoir system without interruption. In applying (ADM), the inflows were accumulated and the difference calculated. The minimum inflow within the year of record was determined to be the firm yield. The yield of 30x109m3 was hypothetically chosen to determine the minimum capacity to sustain it without interruption during the period under record. Similarly the firm yield analysis was also done by employing the method of reverse chronology (RCM) to confirm the result in the accumulated difference method. This method is based on the premise that what is the minimum volume that has to be in storage at the end of the previous year plus the inflow can meet the demand during the current year. This was carried out by starting with the last year of the record and working back to the first year and the difference between the inflow and the required yield was determined. The shortages were then observed form the difference obtained; the maximum shortage was then selected as the required capacity.The firm yield was determined to be 22.7283×109m3. The minimum capacity required to sustain a yield of 30×109m3 per annum (the average annual demand) without interruption during the period under record was determined to be 7.3431×109m3. The interaction between the reservoir elements were significant considering the correlation matrix applied.

Technical Design and Financial Feasibility Analysis of Off-Grid Photovoltaic Power Supply System for Residential Load

Due to intensive promotion to use renewable energy, by the various benefits obtained by utilizing, and then supported by advances in generation technology: causing various parties to divert the type of fuel for their energy use activities. The same thing happens to residential electricity consumers, driven by the advantageous of electricity power generation that can be done on the consumer side, independent operation, reliability and quality of power, many consumers try to install renewable energy based generation such as photovoltaic system for their electricity supply. However, looking at the tariff of utility electricity and considering the investment needed: building a photovoltaic-based supply system is not necessarily the right choice. This paper presents a technical design for electricity supply of a residential load through an off-grid photovoltaic system. The technical basis for designing and the capacity of its constituent components is explained, as well as the analytical techniques carried out to assess the financial aspects of the development and operation of the system. The results of this analysis can be used for deciding whether it is appropriate to divert the source of electrical energy to the photovoltaic system. To show the steps of the analysis, a case study was carried out by designing an off-grid photovoltaic system for a residential load characterized by its daily load curve. The capacity and costs were calculated and financial analysis is carried out by looking at the extent to which the designed system can provide comparable benefits if the power is supplied from the utility at the prevailing price, as well as how long the system must be operated to obtain a breakeven return on investment. Based on the daily load curve in this case study, it is known the total daily energy consumption of the load is 6.885 kWh. This amount of energy must be provided from photovoltaic module with 5 hour effective per day, so the minimum capacity of PV-module is 1463.65 W. For an autonomy time of 1 day, a minimum energy storage capacity of 8.965 kWh is required. Investment costs which include the cost of procurement, system development, and the tax are Rp. 150,008,037. The financial benefits are calculated based on prices of the PLN 2016 non-subsidized tariff. It was assummed that the energy used that should be supplied from PLN, is substituted by photovoltaic generation system. NPV analysis and Payback period shows that the off-grid photovoltaic generation system will be feasible if the electricity price is 2.3 times the current price, and the discount factor (DF) for construction is 2.5%, in such electricity prices and DF factor, the payback period is reached if generation system is operated at least until the end of the 25th year. Financial analysis showed the inability of the off-grid electricity supply scheme based on the designed photovoltaic generation for current conditions.

Managing natural gas demand for free consumers under uncertainty and limited storage capacity

Demand for energy sources depends on several factors such as population growth, urbanization, industrialization, and climate. Among fundamental energy sources, natural gas is characterized by storage limitations and take-or-pay contracts, which makes it especially critical to forecast the demand accurately for cost management policies. Suppliers of natural gas require take-or-pay contracts to ensure that consumers pay for any unused amount up front; and if the demand exceeds the agreed amount, they pay for over-use as well. Consumers with a demand above the eligible consumer limit are categorized as free consumers; and they have to specify their daily, monthly, and annual demand in these take-or-pay contracts. In residential areas, natural gas is used predominantly for heating, hence its consumption has a strong seasonality. In winter, the variability in the atmospheric temperature leads to fluctuations in the demand, while in summer, weekend effects dominate. In order to take these features into account, a demand forecasting model based on a modulated expansion in Fourier series, supplemented by deviations from comfortable temperatures, is used in this study to determine the threshold value for the onset of natural gas usage for heating purposes. The upper and lower bounds for consumption are obtained as a function of temperature only, after analyzing the details of the temperature-consumption relationship using historical data. Moreover, a temperature-based simulation methodology is proposed and simulation results that provide guidelines to manage the costs of storage under uncertainty are presented by suggesting the minimum storage capacity required and showing the distribution of the costs.

Modified African Buffalo Optimization for Strategic Integration of Battery Energy Storage in Distribution Networks

This article presents a two-layer optimization scheme for simultaneous optimal allocation of wind turbines (WTs) and battery energy storage systems (BESSs) in power distribution networks. The prime objective of this formulation is to maximize the renewable hosting capacity of the system. For outer-layer, a new objective function is developed by combining multiple objectives such as annual energy loss in feeders, back-feed power, BESSs conversion losses, node voltage deviation, and demand fluctuations caused by renewables subject to various system security and reliability constraints. Furthermore, a modified variant of African buffalo optimization (ABO) introduced to overcome some of the limitations observed in its standard variant. The proposed modifications are first validated and then introduced for simultaneous optimal integration of multiple distributed energy resources in distribution systems. The proposed modified ABO is employed to determine the optimization variables of outer-layer. Whereas, a heuristic is proposed to solve the inner-layer optimization problem aiming to determine the optimal dispatch of BESSs suggested by outer-layer optimization. By considering the high investment and operating cost of BESSs, minimum energy storage capacity has been ensured during the planning stage. To present the efficacy of developed model, it is implemented on a 33-bus, benchmark test distribution system for various test cases. The comparative simulation results show that the proposed optimization model and modified ABO is very promising to improve the performance of active distribution systems.

Modelling and optimisation of a hybrid PV-wind turbine-pumped hydro storage energy system for mini-grid application in coastline communities

This study proposes a clean, reliable and affordable hybrid energy conversion technology that is based on sunlight and wind, with a hydro based energy storage system. The proposed system comprises Photovoltaic arrays, wind turbine (WT) and Pumped Hydro Energy Storage (PHES). The study was focused on satisfying energy demand of a typical coastline community, Patani (Lat. 5.23° N and Long. 6.17° E) – a Local Government Area (LGA). Genetic algorithm was adopted to optimise the PHES of the proposed hybrid plant to minimise the difference between energy demand and energy generated. Economic models were developed to ascertain the economic feasibility of the hybrid plant. High fidelity software (HOMER®, MATLAB® and MS Excel® spreadsheet) were utilised for the analysis and optimisation. The peak rated power of PV and WT required to satisfy the energy demand of the LGA are 217 kWp and 226050 kW, respectively. The minimum storage capacity of the PHES was estimated at about 3,930,615 kWh, with the upper reservoir volume of 43170.06 m3. The value of 0.27 $/kWh was obtained for the Levelised Cost of Energy (LCOE); while the loss of load probability of the proposed energy system was estimated at 0.1086. The proposed energy system supports the Sustainable Development Goal 7 – affordable and clean energy, with climate change mitigation potential.

The Potential of Sky Radiation for Humidity Control

The potential of sky radiation (SR) to serve the latent space cooling loads was evaluated. Using ASHRAE standard 55 comfort limits (room temperature 22 °C, relative humidity 60%, and dew-point temperature 13.9 °C), condensation was the chosen mechanism for humidity reduction. Typical meteorological year (TMY3) weather data were used for eleven ASHRAE climate zones. Three values of load-to-radiator ratio (LRR) (infiltration/ventilation volume flow rate times the ratio of building floor area to radiator area) were evaluated: 0.35, 3.5, and 35 m/h. Three thermal storage cases were considered: 1. Annual cooling potential, 2. Diurnal storage, and 3. Minimum storage capacity to serve the entire annual load. Six SR temperatures Trad = 13.9 to −26.1 °C were tested. Even in the most challenging climates, annual SR potential exceeded the total sensible and latent cooling load, at least for the lowest LRR and the highest Trad. For diurnal storage, SR served less than 20% of the load in the hot and humid southeast, but the entire load in the mountain west. The minimum storage capacity to meet the entire annual load decreased with decreasing LRR and decreasing Trad. For the southeast, large capacity was required, but for Louisville, for instance, sufficient capacity was provided by 0.05 m3 of water per m2 of floor area for LRR = 0.35 m/h. These results demonstrate that for much of the U.S., sky radiation has the potential to serve the entire annual sensible and latent cooling load.

Terrestrial Laser Scanning to Predict Canopy Area Metrics, Water Storage Capacity, and Throughfall Redistribution in Small Trees

Urban trees deliver many ecological services to the urban environment, including reduced runoff generation in storms. Trees intercept rainfall and store part of the water on leaves and branches, reducing the volume and velocity of water that reaches the soil. Moreover, trees modify the spatial distribution of rainwater under the canopy. However, measuring interception parameters is a complex task because it depends on many factors, including environmental conditions (rainfall intensity, wind speed, etc.) and tree characteristics (plant surface area, leaf and branch inclination angle, etc.). In the few last decades, remotely sensed data have been tested for retrieving tree metrics, but the use of this derived data for predicting interception parameters are still being developed. In this study, we measured the minimum water storage capacity (Cmin) and throughfall under the canopies of 12 trees belonging to three different species. All trees had their plant surface metrics calculated: plant surface area (PSA), plant area index (PAI), and plant area density (PAD). Trees were scanned with a mobile terrestrial laser scan (TLS) to obtain their individual canopy point clouds. Point clouds were used to calculate canopy metrics (canopy projected area and volume) and TLS-derived surface metrics. Measured surface metrics were then correlated to derived TLS metrics, and the relationship between TLS data and interception parameters was tested. Additionally, TLS data was used in analyses of throughfall distribution on a sub-canopy scale. The significant correlation between the directly measured surface area and TLS-derived metrics validates the use of the remotely sensed data for predicting plant area metrics. Moreover, TLS-derived metrics showed a significant correlation with a water storage capacity parameter (Cmin). The present study supports the use of TLS data as a tool for measuring tree metrics and ecosystem services such as Cmin; however, more studies to understand how to apply remotely sensed data into ecological analyses in the urban environment must be encouraged.

Optimisation of the Structure of a Wind Farm—Kinetic Energy Storage for Improving the Reliability of Electricity Supplies

An important issue in the correct operation of the power system is the reliability of the electricity supply from generation systems. This particular problem especially concerns renewable sources, the output power of which is variable over time and additionally has a stochastic character. The solution used in the work to improve the reliability indicators of wind farm sources is the partial stabilization of their output power achieved through cooperation with the kinetic energy storage. Excessive increase in storage capacity is associated with a large increase in investment and operating costs. It is therefore important to determine the minimum storage capacity required to maintain the accepted criteria for the reliability of energy supply. In this paper, a population meta-heuristics algorithm was used for this purpose. The obtained results confirm the possibility of limiting the energy capacity of the flywheels, they also indicate its non-linear character as a function of selected parameters of the reliability of energy supplies from wind farms.

Substitution of coal power plants with renewable energy sources – Shift of the power demand and energy storage

Because of their Global Climate Change contributions, it is desirable to reduce the amount of the global CO2 emissions. One of the ways to accomplish this is the substitution of coal with renewable energy sources, most notably wind and solar. However, the availability of wind energy and of insolation does not follow the diurnal and annual demand patterns of electric power. The large-scale substitution of coal with wind and solar significantly shifts the demand for the rest of the power producing units. When the contribution of wind and solar exceeds approximately 25% of the total annual energy produced, there are time periods within a year when excess electricity is produced that must be wasted/dissipated. This presents a severe constraint for the substitution of coal-generated electricity with renewables. At such production levels diurnal or seasonal storage of energy becomes necessary and hydrogen storage offers the best alternative. Based on the hourly, electricity demand of a region in North Texas, which has very high availability of wind and solar energy and is considered prime region for renewables, extensive calculations are made for: (a) the solar and wind rated power that are necessary for the substitution of part or all the power currently supplied by a coal-fired power plant; and (b) the storage requirements for this substitution. Significant seasonal and diurnal energy storage, on the order of 250,000 m3, is required for the total substitution of coal in the region. The calculations also reveal that the substitution of coal with the renewable energy sources may be optimized for minimum energy storage capacity.