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India has seen rapid increases in GDP, energy access, and population in recent decades, more than doubling its overall energy consumption since 2000. Meanwhile, India produces approximately 70% of its electricity from coal. With electricity demand only projected to grow in the coming years, the Government of India has pledged to install 450 GW of renewable energy by 2030. The Gulf Cooperation Council (GCC) countries[1], meanwhile, have comparatively small populations with excellent renewable energy resources, particularly solar. The ability to trade power between these two regions could potentially provide India with a highly reliable carbon-free power source. At the same time, it can motivate the shift to low carbon economy in the GCC and add a new market for its solar power. The provided data in this article relate to the current makeup of the energy systems of both regions, renewable resource potentials, and projections of future demand. The data have been compiled from numerous sources, mainly government and international agencies.[1] GCC countries are Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates

In an under-resourced environment, the optimal energy management of the off-grid system under the stochastic generation and load is an open technology challenge. To design the least-cost system whilst meeting the reliability requirement, this work develops a predictive control framework based on a real-world microgrid pilot design11This work is supported in part by the Engineering and Physical Sciences Research Council under Grant EP/R030111/1 Robust Extra Low Cost Nano-grids (RELCON). Considering users' preferences and various weather conditions, it employs model predictive control (MPC) and demonstrates superior performance in reliability improvement compared with the day-ahead case. Given the reliability requirements ranging from 70% to 90%, the MPC can achieve the 5.23% improvement with the same system cost, and close to the performance under the perfect foresight.

Transition to low carbon electricity generation is key to meet the global emission targets. This requires a drastic shift from the current energy mix dominated by coal and gas to renewables especially wind and solar. Due to the intermittent nature of renewable generation, the probability of generation-demand mismatch is high. This mandates the need for storage of the excess generation in order to prevent curtailment. Utilisation of domestic hot water tanks to absorb this excess provides us with an economical option at a nominal incremental cost. This paper develops a method to quantify the capacity of hot water tanks required and the potential savings in a low carbon future. The results are explained with the UK as a case study. The results indicate that between one and ten Terra Watt hours of curtailment can be expected in the UK in the year 2040. Eighty percent of this energy can be captured if one-fifth of all houses in the UK are equipped with smart hot water tanks.

Decarbonising electricity systems is essential for mitigating climate change. Future systems will likely incorporate higher penetrations of intermittent renewable and inflexible nuclear power. This will significantly impact on system operations, particularly the requirements for flexibility in terms of reserves and the cost of such services. This paper estimates the interrelated changes in wholesale electricity and reserve prices using two novel methods. Firstly, it simulates the short run marginal cost of generation using a unit commitment model with post-processing to achieve realistic prices. It also introduces a new reserve price model, which mimics actual operation by first calculating the day ahead schedules and then letting deviations from schedule drive reserve prices. The UK is used as a case study to compare these models with traditional methods from the literature. The model gives good agreement with and historic prices in 2015. In a 2035 scenario, increased renewables penetration reduces mean electricity prices, and leads to price spikes due to expensive plants being brought online briefly to cope with net load variations. Contrary to views previously held in literature, a renewable intensive scenario does not lead to a higher reserve price than a fossil fuel intensive scenario. Demand response technology is shown to offer sizeable economic benefits when maintaining system balance. More broadly, this framework can be used to evaluate the economics of providing reserve services by aggregating decentralised energy resources such as heat pumps, micro-CHP and electric vehicles.

Off-grid systems have emerged as a sustainable and cost-effective solution for rural electrification. In sub-Sarahan Africa (SSA), a great number of solar-hybrid microgrids have been installed or planned, operating stand-alone or grid-tied to a weak grid. Presence of intermittent energy sources necessitates the provision of energy storage for system balancing. Reliability and economic performance of those rural microgrids strongly depend on specific control strategies. This work develops a predictive control framework dedicated to rural microgrids incorporating a temperature-dependent battery degradation model. Based on a scalable DC PV-battery microgrid, the realistic simulation shows its superior performance in the reliability improvement and cost reduction. Compared with the day-ahead control without the temperature-dependent battery degradation model, this control strategy can improve the reliability by 5.5% and extend the lead-acid battery life time by 26%, equivalent to lowering the levelised cost of electricity (LCOE) by 13%., Comment: There are several faults in this pre-print

This paper presents OPEN, an open-source software platform for integrated modelling, control and simulation of smart local energy systems. Electric power systems are undergoing a fundamental transition towards a significant proportion of generation and flexibility being provided by distributed energy resources. The concept of ‘smart local energy systems’ brings together related strategies for localised management of distributed energy resources, including active distribution networks, microgrids, energy communities, multi-energy hubs, peer-to-peer trading platforms and virtual power plants. OPEN provides an extensible platform for developing and testing new smart local energy system management applications, helping to bridge the gap between academic research and industry translation. OPEN combines features for managing smart local energy systems which are not provided together by existing energy management tools, including multi-phase distribution network power flow, energy market modelling, nonlinear energy storage modelling and receding horizon optimisation. The platform is implemented in Python with an object-oriented structure, providing modularity and allowing it to be easily integrated with third-party packages. Case studies are presented, demonstrating how OPEN can be used for a range of smart local energy system applications due to its support of multiple model fidelities for simulation and control.

Higher penetration of renewable sources of energy is essential for mitigating climate change. This introduces problems related to the balance of supply and demand. Instances in which the generation from intermittent and inflexible sources is in excess of system load are expected to increase in low carbon futures. Curtailment is likely to involve high constraint payments to renewable sources, and failing to curtail threatens the stability of the system. This work investigates a solution that makes use of residential heating systems to absorb the excess generation. Consumers are incentivised to increase consumption via a demand turn up mechanism that sets the electricity price to zero when excess generation occurs. The reduction in electricity price significantly weakens the economic case of dwelling-scale micro-cogeneration units. But technologies that use electricity are able to charge the thermal store when free electricity is available and discharge it when electricity prices are high. Such actions reduce the equivalent annual cost by 50 percent for a resistive heater and by 60 percent for a heat pump. Without disincentives, resistive heaters are likely to be chosen over heat pumps since they are easy to install, do not involve high upfront costs and can provide significant economic benefits.

This article evaluates the impact of a range of dynamic performance parameters on the techno-economics of fuel cell based micro co-generation. The main novelties in methodology are: (1) Analysis in the context of future power system decarbonisation, (2) Use of the Long Run Marginal Cost of electricity, (3) Combination of the above with dynamic aspects such as start-up cost, ramping limit, turn down ratio, minimum up time and minimum down time and (4) Identification of sensitive parameters for future research. To this end it combines a national level energy systems model with an individual heating system model. A case study of the United Kingdom is considered for the year 2035. Economic viability of fuel cell based micro co-generation hinges upon the use of an optimized control strategy. With such a control strategy, a hot start-up approach offers much greater economic potential than a cold start-up approach. The best case ratio of maximum allowable hot standby power to the nominal value is 4.2 while the ratio for cold start is only 1.1. Combinations involving low ramping limits less than 70 W/min and limited turn down ratios above 35% need to be avoided as they seriously hinder economic performance.

This paper aims to design a system that can enable optimal operation of the solar powered Membrane Distillation Bio-Reactor (MDBR) water recycling plant. Optimal operation is described as maximization of the clean water produced while being a self sufficient entity in terms of energy. During periods of adequate solar radiation, the system will optimize production levels. When faced with inadequate sunlight, the system will focus on reserving sufficient energy for the survival of the essential micro-organisms in the MDBR. Hence, uninterrupted plant operation during periods of unfavorable weather entails the management of a back up reserve. These engineering objectives are translated into mathematical functions that can be incorporated into convex optimization problems. The effectiveness of the control framework is demonstrated through simulation.

Bilateral congenital mid ureteric stenosis is a very rare entity causing hydroureteronephrosis. The pathophysiology and aetiology of this condition is uncertain. Congenital functional obstruction of the mid ureter has only 17 reported cases, that too of unilateral pathology. We report a case of an 11-year-old male child who was presented with left sided lump in abdomen since one year. On bilateral retrograde ureteropyelography (RGP), bilateral mid ureteric stenosis was documented at the level of pelvic brim. Tc99m Diethylene Triamine Pentacaetic Acid (DTPA) scan showed non functioning left kidney and decreased function and retention on right side. We did a left nephroureterectomy and uretero-ureterostomy without tapering over a Double-J stent (DJ), with excision of stenosed segment on right side. Pathological review of the ureteric segments of both sides revealed proximal dilatation with non-specific thickening of the muscular wall of the stenosed segments of ureter. The differential diagnosis must additionally include ureteral valves and fibro epithelial polyps. Important role of intravenous pyelography in such cases must be emphasized to localize the pathology site. In addition, retrograde ureteropyelography is essential in management of this anomaly to delineate the stenosed segment of the ureter preoperatively, so that the surgeon can be well prepared with final plan of management.

The objective is to develop a control system that will enable the Membrane Distillation Bio-Reactor (MDBR) water recycling plant to become self sufficient and fully automatic. In order to ensure continuous operation, the control system must maintain conditions required for the micro-organisms to survive. These requirements need to be met even when solar radiation and weather conditions are not conducive for water production. Hence, maintenance of a back up reserve is necessary. A balance has to be struck between minimization of power consumed and maximization of output produced to facilitate smooth operation. Control is implemented through a hierarchical framework that keeps track of the different plant objectives. Operational set points are determined through convex steady state optimization. Current set points are based on predictions regarding variation in solar radiation within the planning horizon.

Laboratory scale batch studies were performed to test the diesel oil biodegradation ability of ES1 cultures isolated from Arabian Sea sediments obtained from the vicinity of an oil field. This culture could utilize diesel as the sole source of carbon and energy. Under aerobic conditions, 39% loss of diesel oil was observed over 8 days where 80% of the loss was due to aliphatic constituents. Under anoxic nitrate reducing conditions the rate and extent of degradation was significantly lower, i.e., 18% over 50 days. Salt acclimatized cultures could tolerate salinities up to 3.5% and demonstrated optimal performance at a salinity of 0.5%. The optimum N/P ratio for these cultures was found to be in the range of 2:1–5:1. Addition of two trace elemental substance formulations exhibited a significant inhibitory effect on culture growth. This culture has good potential for decontamination of oil-contaminated marine and subsurface environments., © Elsevier