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Over the past decades, forecasting electricity demand has been crucial in energy planning and power distribution management to establish sustainable strategies in undeveloped countries. This work proposes an integrated approach to evaluate Pakistan's energy sector and holistically investigate electricity-load strategies to prioritize them and prevent future electricity crises. This paper proposes a renewable energy technologies-based system design to eliminate energy shortfalls. Deep learning models can predict fluctuating variation in energy consumption, crucial for designing renewable energy systems. The strengths – weaknesses – opportunities, and threats (SWOT) analysis identified relevant factors and sub-factors, while the fuzzy-TOPSIS methodology prioritized alternative strategies. The results show that driving the nation to the functionality of an energy hub by sufficiently using its geostrategic location within the regional cooperation framework is the critical dominant factor. Besides, improving the country's investment environment was the least favored priority. Baluchistan was found to have the highest potential for wind energy, with an ability to generate 3270 MWh/year through wind power. [Display omitted] • An integrated management approach is proposed to address electricity crisis. • The proposed strategical energy forecast and planning is studied for Pakistan. • Prioritize the indicated strategies for sustainable energy planning and development. • Turning the country into renewable energy hub is suitable for Pakistan's economy. • Baluchistan has the potential to generate 3270 MW power from wind power. [ABSTRACT FROM AUTHOR]

[Display omitted] • An optimal DSM-based scheduling of energy distribution network is developed. • Strategical conversation of regulated mix-generation reduced 0.92–2.28% of deficit. • Self-production of installing PVs aided to increase beneficial cost consumption. • The energy distribution network S.IV satisfied top 5 appliance of consumer request. • Combined low-carbon energy in DSM-based distribution reduced 27.04 tons CO 2. Global transactive energy has become more complex due to the extension of its efficiency. Thus, multi-residential demand responses pose a new challenge in the critical infrastructure of power transition networks in energy planning and management. By encompassing optimal scheduling with strategic energy decentralization, a reliable distribution network can suggest a resolution that contributes to optimize energy efficiency. This research proposed a holistic bidirectional distribution network with optimal scheduling-based demand-side management (DSM) for superior power sharing and beneficial performance. A DSM was developed to maintain equal power sharing between various mix-energy sources, providing a sub-level residential demand response program. Among several scenarios considered, the DSM-based scheduling distribution network resulted in optimum and equivalent sharing of power loads for residential demands. Moreover, the application of self-production-based renewable energy source (RES) is a novel strategy to improve imbalanced power sharing. The energy deficit and surplus can be solved by establishing a conservation strategy with self-installation-based photovoltaic panels by end-users. CO 2 emissions were also estimated to elucidate the effect of the energy distribution network on the environment according to different category of energy sources. Considering satisfaction analysis based on appliance energy consumption, the energy distribution network was efficient in improving the end-user expenditure, sustaining a clean energy loading profile, and maximizing the benefit of cost. [ABSTRACT FROM AUTHOR]

A holistic analytical and smart management approach is proposed to investigate the performance of renewable-based tri-generation system to generate power, cooling, and domestic hot water with a simultaneous consideration of several operational, design, and system feasibility aspects in a framework. The proposed configuration consisted of a solar driven organic Rankine cycle, and double-effect absorption refrigeration cycle integrated with a Kalina cycle. To analyze environmental implications, life cycle assessments are performed, while further evaluations are conducted utilizing algebraic thermo-mathematical programming. Hazard study and thermal reliability analysis are also performed to analyze the safety and failure rate of the system. Additionally, four critical scenarios are defined: safe urban deployment, economic viability, reliable operation, and sustainable development. In accordance with the four specified scenarios the integrated system is globally optimized using a weighted multi-objective optimization. Following that, a suitable optimum system and fluid allocation is conducted based on hybrid deterministic decision-making technique under smart management. The optimization results showed that the total exergorisk, system reliability, and environmental impact can be simultaneously improved in the range of 4.08–28.3%, 4.14–13.9%, and 1.65–24.6%, in all scenarios employing various working fluids, respectively. Additionally, the system achieves lowest overall cost rate (4.17USD·s−1) with R113, while the highest energetic efficiency (46.3%) and system reliability of (91.2%) was associated with R365mfc. Finally, a comparative analysis indicates a CO 2 saving potential of 6646, 4883, and 2878 tons/year in comparison to coal, fuel oil, and natural gas based integrated energy systems. [Display omitted] • Solar integrated energy system for power, cooling, and domestic heating load. • Comparative economic, risk, reliability, and life cycle assessment were performed. • Real world policies were adopted for exergy models in four scenarios. • Weighted optimization and smart decision-making are utilized for fluid allocation. • System presents CO 2 emissions and CO 2 cost savings of 6646 ton/Yr and 87,360 USD/Yr. [ABSTRACT FROM AUTHOR]

Nowadays, the transportation sector occupies a vital role in current society. However, this sector is the second-highest greenhouse gas emitter worldwide due to fossil fuel combustion. Transitioning from conventional to renewable energy propulsion is a promising alternative to climate change mitigation. This study proposes a smart decision-making approach of an integrated system assisted with renewable energy sources to satisfy the dynamic railway electrification demand. The proposed energy system consists of a proton-exchange membrane electrolyzer, solid-oxide fuel cell, and lithium-bromide absorption chiller assisted with solar radiation and wind turbine to simultaneously generate power, hydrogen, cooling, and heating loads. A novel approach consists of power-pinch analysis and multi-criteria decision-making (MCDM) to determine the optimal sizing of renewable resources considering the system's thermodynamic, economic, and exergy performance. A total of five optimal scenarios with different renewable sources share were obtained. Accordingly, the scenario with a share of 70/30 of solar and wind energy showed the highest competitiveness based on the MCDM. This scenario showed an energetic and exergetic efficiency of 49% and 34%, respectively. Furthermore, it yielded acceptable subproducts generation, including the production of 312.25 kg H 2 /day, in an economical budget with a levelized cost of energy (LCOE) value of 0.079 $/kWh. • Smart management tool was developed for the dynamic railway electrification demand. • Power, hydrogen, cooling, and heating loads were produced simultaneously. • Power pinch analysis was developed to find optimal sizing of renewable energy share. • Energy and exergy analyses yielded efficiencies of 69% and 42%, respectively. • The optimal scenario generated a total of 312.25 kg H 2 /day. [ABSTRACT FROM AUTHOR]

Renewable energy resources have become important to strategies for meeting industrial demands for power due to their various benefits when coupled with government incentives and public support. To obtain a reasonable compromise between capital investment costs and system reliability, a method of determining the optimal size of hybrid renewable energy system (HRES) components is needed. This study proposes a smart management approach to optimal sizing and power management of hybrid photovoltaic-wind turbine generation with hydrogen and battery storage, considering contemporary economics, system reliability, and environmental policies to meet the dynamic energy demands of a wastewater treatment plant (WWTP). A multi-objective approach based on a fuzzy–decision-making method is proposed to solve the optimization problem. Extended power-pinch analysis was applied to optimize the size of components and determine feasible electrical-storage capacity to tackle the dynamic power loads of the WWTP. A year of observations showed that an HRES has a high reliability level for energy loading up to 86% when supplying a dynamic demand, with acceptable environmental emissions and an economical budget. • An optimal hybrid renewable energy system configuration is proposed for a WWTP. • The power strategy is managed by reliability, economic and environmental factors. • The multi-objective criteria decision is targeted at dynamic demand and supply. • An optimal design comprises 165 photovoltaic panels and 5 wind turbines. • Reliability performance is 80%, with acceptable environmental and economic results. [ABSTRACT FROM AUTHOR]