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In this study, a M W -scale fuel-cell-based multi-energy hub system is simulated to maximize microgrid flexibility. The system was designed to deliver electricity, heat, and H 2 with a high energy efficiency, which can be realized through the integration of the exothermic phosphoric acid fuel cell and endothermic turboexpander generator modules. To extract additional useful work during the depressurization process in the natural gas supply chain, this multi-energy system is currently under construction on a pilot basis in South Korea. Based on a natural gas flow rate of 28,000 k g / h , we analyze the performance of the system and its economic effects under different load demands and operating conditions. The system simulation results show that the total electrical power generated by the turboexpander generator and phosphoric acid fuel cell modules is approximately 3.395 – 3.539 M W e , while the H 2 yield is 19.94 – 40.00 k g / h. In addition, an economic assessment of the multi-energy hub system is conducted based on the current natural gas, electricity, and H 2 prices in South Korea. Assuming a life span of 20 years for the turboexpander generator and phosphoric acid fuel cell modules, the payback period is estimated to be between 7.09 and 10.05 years. • MW-scale fuel-cell-based MEH system is modeled and simulated. • MEH system exhibits flexible hydrogen production and electricity generation. • Energy efficiency of the PAFC system has a tradeoff with hydrogen production. • Economic assessment is made based on current NG, electricity, and hydrogen prices in Korea. [ABSTRACT FROM AUTHOR]

Developing carbon-neutral bioenergy sources and bioproducts is an extraordinary opportunity for achieving an environmentally friendly economy. However, the overconsumption of resources in bioenergy and bioproduct production causes severe environmental concerns. The green biorefinery concept is one of the most attractive solutions for sustainably producing bioenergy sources and bioproducts. Seaweed is well-known as a promising green resource for biorefineries. Biorefineries based on seaweed not only produce various products but can also help solve macroalgal bloom issues. Nevertheless, a comprehensive environmental investigation should be performed before implementing seaweed-based biorefineries. Thus, using an environmental life cycle assessment, the current study examines three seaweed-based biorefineries. These scenarios include biogas production and waste valorization (Sc-1), bioethanol production and waste valorization (Sc-2), and biogas + bioethanol production and waste valorization (Sc-3). The results indicate that all the proposed scenarios offer environmentally friendly solutions for utilizing seaweed as a source of bioenergy and bioproducts. Sc-1 demonstrates the best environmental performance compared to the other two scenarios. Specifically, Sc-1 achieves a 99% and 97% reduction in total weighted environmental impact compared to Sc-2 and Sc-3, respectively. This finding is attributed to the avoidance of mineral fertilizers in Sc-1, resulting in a significant reduction in environmental impact. The electricity generation based on Sc-1 results in 1.91E-08 DALY/MJ of damage to human health and 1.65E-03 PDF.m2.yr/MJ of damage to ecosystem quality. Furthermore, the net weighted environmental impact of electricity generation based on Sc-1 results in 1.65E-03 EUR2003/MJ of damage, compared to 1.07E-01 EUR2003/MJ for grid electricity in the region. Therefore, replacing grid electricity with electricity generated from biogas in Sc-1 can reduce 98% of environmental damage. [Display omitted] • Seaweed-based biorefineries are environmentally scrutinized by life cycle assessment. • Waste valorization under the biorefinery has a key role in lowering environmental impacts. • Avoiding mineral fertilizers due to seaweed valorization reduces environmental impacts. • Biogas production under the biorefinery significantly reduces damage to the environment. • Seaweed-based biogas for electricity can reduce up to 98% of environmental impacts. [ABSTRACT FROM AUTHOR]

In spite of the fact that the solar power tower system is considered as one of the most valuable power generation facilities, it still faces challenges such as insufficient utilization of the solar salt temperature range and the dependence on high solar radiation intensity. To address this issue, an integrated recompression Brayton cycle and trans -critical regenerative organic Rankine cycle in parallel layout is proposed. The comparison with other literature shows that the specific work of the integrated system (147.8 kW/kg) outperforms the partial cooling Brayton cycle (130.1 kW/kg) under the same solar salt temperature range. In order to forecast future electricity generation and serve as a reference for plant operation, a power prediction strategy using neural networks is developed. Findings indicate that the integrated system can increase power production and maximize solar salt temperature utilization by adjusting the physical constraint strategy based on the changing temperature interval. Its equivalent work and thermal efficiency reach 12.7 MW and 38.36%, respectively, and it can recover the cost in 8 years. These results suggest that the proposed integrated system is a promising solution to enhance the performance of solar power tower systems with significant economic benefits. [Display omitted] • A two-stage power cycle to fully utilize SPT solar salt temperature range is offered. • Proposed system increases power production by adopting physical constraints. • The power cycle adopts low GWP and zero ODP working fluid. • The total specific work of the combined system surpasses the partial cooling cycle. • A BI-LSTM-based power generation prediction strategy of the system is developed. [ABSTRACT FROM AUTHOR]

The generation forecast helps to develop the scheduling plan of power sources, build a power balance system and ensure the adequacy of power supply to the power system at the macro level. Therefore, a novel structurally adaptive discrete grey Bernoulli model, called DHGBM(1,1), is proposed in this paper for the prediction of power generation. Firstly, the Hausdorff fractional order cumulative generation operation makes it possible to achieve new information prioritisation. As for the structure of the model, we have extended the nonlinear grey Bernoulli model with the introduction of a nonlinear dynamic structure term, which allows the model to simulate variable generation data and improves the adaptability of the model. In a comparative test of the algorithms, the well-performing differential evolution algorithm was used for hyperparameter optimisation of the model to obtain better predictive performance. Monte Carlo simulations and probability density analysis verified the excellent robustness of the model. In addition, through the simulation tests, we obtained a reasonable range of parameters for the structural terms, thus limiting the complexity of the model, and the phenomenon of model overfitting was effectively prevented. Finally, five actual cases of China's hydro, China's thermal, China's nuclear, China's wind power generation and China's electricity exports are predicted. • A novel nonlinear dynamic structural term is proposed. • A novel structural adaptive discrete grey Bernoulli model is developed. • The robustness analysis of the novel model is established. • Comparative study shows that the novel model is superior to other six models. [ABSTRACT FROM AUTHOR]

Coke oven gas is a by-product of the process of producing coke from coal and contains valuable compounds such as hydrogen and methane. In this study, an improved process was proposed for co-generation of power and LNG from COG with low CO 2 emissions and high energy and exergy efficiency. This proposed process includes: LNG Recovery Unit, Organic Rankin Cycle, and the power plant. The results of simulation showed that the exergy and energy efficiencies for this proposed process are 77.9% and 70.29%, respectively, which are considerably higher than other studies. It is found that the total exergy destruction of the proposed process is 4272.95 kW, and the power plant with 3118.1 kW exergy destruction has the largest share in total exergy destruction. Additionally, outcomes showed that ORC recovered 1205 kW of waste heat from compressor exhaust gases and produced 167.4 kW of power. Environmental analysis shows indirect carbon emissions for the proposed process is zero. The CO 2 emissions for the total energy and electric power generation were 0.0034 k g C O 2 / M J and 406 g C O 2 / k W h e l , respectively which are lower than coal or natural gas power plants. • A novel structure was proposed to produce power and LNG from Coke oven gas. • This proposed process includes LNG Recovery Unit, Organic Rankin Cycle and the power plant. • Using ORC made cooling utility consumption reach its minimum value. • The proposed process has low carbon dioxide emission. • The energy and exergy efficiencies are 70.29% and 77.9%. [ABSTRACT FROM AUTHOR]

The dynamic performance (or flexibility) of the combined heating and power (CHP) unit operating in a heat-led mode is restricted by the strong interdependence between electricity generation and thermal generation. This paper proposes a method that balances the flexibility and the heating quality using a coupled two-timescale model predictive control (MPC) scheme. The indoor temperatures of thermal users are regulated in a comfort region by a slow timescale MPC using zone control; a fast MPC is used as the coordinated control system (CCS). The two controllers are coupled in that both controllers use the extraction steams as their controlled variable. In this way, the dynamic flexibility of the CHP unit is improved by utilizing energy buffers from district heating systems and buildings. The proposed scheme is verified using a simulation study on a real heating system with 2 CHP units, 28 thermal nodes, and 58 pipelines. The result shows that the dynamic performance of the system is improved considerably while the temperatures of thermal users remain in their comfort regions. [Display omitted] • An MPC scheme is proposed to optimize the dynamic flexibility of CHP systems. • Two coordinated MPC controllers are used to solve the problem. • Zone control is used in order to give more room for electrical power control. • The method is verified using simulations of a CHP system. [ABSTRACT FROM AUTHOR]

Owing to slowly lessening of fossil fuel, economical use of obtainable fuel for electric power and heat generation has turn out to be an important worry of utility industries. In this manuscript, fuel constrained combined heat and power unit commitment incorporating renewable energy sources and electric vehicle parking lot is undertaken for addressing the optimum generation scheduling of the committed units. Here thermal generating units (TGUs), cogeneration units (CGUs), heat only units (HOUs), cascaded hydro power plants (CHPPs) and solar PV plants (SPVPs) and wind turbine generators (WTGs) are considered. A number of plug-in electric vehicles (PEVs) with charging and discharging behaviours is also considered. The problem is solved with and without fuel constraints. The UC problem is solved by using binary differential evolution (BDE) along with priority list (PL). Numerical results of the test systems are included to provide valued minutiae for operational and planning problems. [Display omitted] • Fuel constrained combined heat and power commitment scheduling has been studied. • Cascaded hydro power plants, solar PV plants, wind turbine generators are considered. • 50 000 PEVs have been incorporated with both G2V mode and G2V/V2G modes. [ABSTRACT FROM AUTHOR]

A good knowledge of power system dynamics is necessary for the implementation of efficient demand-side-management strategies. This article proposes a model of Unit-Commitment and Economic Dispatch of a power system that can be used to assess the marginal mix for different demand-response events. The model is based on two calibrated merit-orders to reproduce the daily and intra-daily dynamics, including the conservation of hydroelectric energy and electricity exchange, coupled with a simplified model of the European grid. This method is then applied to the French use case for year 2018. The validation protocol includes yearly and weekly timescales. Finally the French model is used to assess the impact of three demand-response strategies: peak clipping, valley filling and load shifting. These strategies turned out to increase the utilization rate of the French nuclear fleet and decrease the French generation electricity from fossil fuels. Moreover, they also impacts the interconnected power systems, in particular Germany, Portugal, Switzerland and Netherland. This model could be used to assess the environmental impact of demand-side-management, if completed with models evaluating the marginal emission factor of the electricity generation in the other European countries and the national power plants. [Display omitted] • The impact of demand-response strategies can be assessed with priority lists. • Models based on two priority lists instead of one better replicate intra-day dynamics. • Demand-response strategies increase the utilization rate of the French nuclear. • Demand-response strategies applied in France strongly impact cross border exchanges. [ABSTRACT FROM AUTHOR]

Low-temperature cold source conditions can significantly improve the thermal performances of organic Rankine cycle (ORC) systems. In this study, the thermal performances of an ORC system operated in Harbin at different working-fluid mass flow rates (0.037–0.188 kg/s) were experimentally investigated, and they were compared with the performances of the same ORC system operated in Taipei which had much higher cold source temperature (30.4 °C vs. 9.6 °C). The results showed that the thermal efficiency and electricity generation efficiency of the ORC system in Harbin increased initially and then decreased (3.1%–6.4% and 2.8%–4.5%, respectively) with the increases in the liquid working-fluid mass flow rates. As compared with the system operated in Taipei, the system operated in Harbin had higher thermal efficiency (4.7% vs. 4.5%, increased by 5.2%) and electricity generation efficiency (3.1% vs. 2.9%, increased by 8.6%) because the lower cooling water temperature resulted in a lower condensation pressure. The results obtained from this study not only compare the thermal performances of the same ORC system operated in different regions but also demonstrate the potential applications of ORC systems in cold areas. [Display omitted] • Thermal performances of the same system in Harbin and Taipei were compared. • The Harbin ORC was operated at a low-temperature cold source condition (9.6 °C). • The Harbin ORC had a higher thermal efficiency of 6.4%. • The Harbin ORC had a higher electricity generation efficiency of 4.5%. [ABSTRACT FROM AUTHOR]

An axial hydraulic turbine mounted on an inclined gate structure aims to extract energy from ultra-low head sites that were previously considered unfeasible and uneconomical for electricity generation. These include canals, waterways, industrial channels, etc. having an untapped potential of 151 GW of clean energy globally. The objective of this study is to provide an efficient and economical ultra-low head turbine technology to contribute to renewable energy demands. An inclined Gate Turbine is designed to extract power by exploiting both the kinetic energy of the flowing water and the gravitational potential energy generated by the gate structure. The turbine design is tested using computational fluid dynamic (CFD) simulations to predict the hydraulic performance and to study the internal flow characteristics. An unsteady multiphase free-surface open-channel CFD model, mimicking the physical-world scenario is employed to simulate the turbine. The hydraulic performance and areas of loss are identified. The turbine runner shape is then optimized to improve the turbine characteristics by diminishing the losses. The efficiency of the optimized turbine increased by 2.72% compared to the initial design. The economic analysis of the turbine showed promising outcomes from the low-head inclined gate turbine. • A novel hydro turbine technology to generate clean energy from ultra-low head sites with head less than 2m. • Areas of flow losses identified at the runner leading edge. • Multi-objective optimization employed to diminish the flow losses and to enhance the turbine hydraulic performance. • The optimized turbine improved the hydraulic efficiency by 2.72% by decreasing losses. [ABSTRACT FROM AUTHOR]

One feature in the ongoing energy transition is that the energy is more often produced close to its final utilizer. The operated device should be reliable to use and it should not annoy the people. Also, the size of the power production module may have limits that are not to be exceeded. One of the solutions is to use vaned Savonius turbines with a low-solidity vane design. It provides a relatively small physical size with low flickering and noise emissions, in addition to its improved starting behaviour in low winds. However, the performance of such a turbine is not well documented in the relevant literature and its internal flow physics are not well known. From this background the current study presents an experimental test case, coupled with validated numerical simulations, for a vaned Savonius turbine and performs what is so far the most complete fluid dynamic analysis of its performance and flow phenomena. The key novelties are that separate experimental and numerical results are presented with and without the stator in order to study the stator-rotor interaction, including accurate static pressure measurements inside the turbine. In addition, a general flow model is presented. [ABSTRACT FROM AUTHOR]

Solar energy application in a wider spectrum has the potential for high efficiency energy conversion. However, solar cells can only absorb photon energy of the solar spectrum near the solar cell band-gap energy, and the remaining energy will be converted into thermal energy. The thermoelectric generator is a good choice to utilize this thermal energy. This paper analyses the feasibility of photovoltaic-thermoelectric (PV-TE), and reviews the current types and performance of PV-TE. Furthermore, it presents the optimization and development of PV-TE. In addition, this paper presents the challenge and efficient improvement of PV-TE in actual application. Therefore, this paper would provide a valuable reference for further research into the field of PV-TE and its applications. [ABSTRACT FROM AUTHOR]

This study is aimed at investigating wind field effect on the power generation and the aerodynamic performance of offshore floating wind turbines. For this purpose, three comparative wind fields are generated: a uniform wind field, a steady wind field with wind shear, and a turbulent wind field. Aero-hydro-servo coupled analysis is performed in time-domain to estimate how a referenced semisubmersible offshore floating wind turbine behaves in the three wind fields. The results reveal the importance of wind shear and inflow turbulence to the performance of the floating wind turbine. Thrust force and power generation become very unstable in the presence of inflow turbulence. Due to the control strategy of the wind turbine, the power generation is also correlated with operational state and turbulence frequency. Although wind shear has a tiny effect on the rotor performance, the local aerodynamic load applied at a single blade experiences fluctuation with the presence of wind shear. It is also shown that the ultimate structural and fatigue damage loads at blade root are augmented by inflow turbulence and wind shear. [ABSTRACT FROM AUTHOR]

This paper presents a framework for expansion planning studies of distributed energy storage systems (DESSs) in high wind penetrated power systems. The main objective is to find optimal location and capacity of DESSs in the viewpoint of independent system operator (ISO) while ensuring the maximum usage of wind farms output generation. Three different criteria are introduced for expansion planning studies. Minimizing wind curtailment cost together with transmission congestion cost are considered to properly deal with the issues associated with the curtailment of wind energy and constraints of transmission network. Furthermore, the minimum normalized profit for all DESSs' owners needs to be maximized to model the requirements of DESSs' owners in the studies. These all the crucial aspects of the DESSs expansion problem are treated via a well-organized posteriori multi-objective (MO) optimization algorithm, i.e. the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The proposed method is applied to the modified IEEE 24-bus test system, and the results are presented to verify the applicability and efficiency of the proposed DESSs planning in a renewable-based power system. [ABSTRACT FROM AUTHOR]

Unlike other traditional energy resources, wind power outputs depend on natural wind resources that vary over space and time. Accurate wind power forecasting can reduce the burden of balancing energy equilibrium in electrical power systems. In this paper, we propose the short-term probabilistic forecasting of wind energy resources using the enhanced ensemble method. The enhanced ensemble forecasting methods are grouped into two main categories: temporal ensemble and spatial ensemble forecasting. The temporal ensemble forecasting is implemented by autoregressive integrated moving average with explanatory variable model, polynomial regression with time-series data, and analog ensemble for a probabilistic approach. The spatial ensemble forecasting is implemented by geostatistical model and interpolation with geographical property data. In addition, the stochastic approach, analog ensemble is applied to reduce the uncertainty in wind power forecasting and use of Numerical Weather Prediction models for accurate wind power forecasting is considered. We conduct stochastic wind power forecasting using practical data of Jeju power system and evaluate the system reliability on wind power generation variations. As a result, the proposed model shows better performances than single models, while at the same time providing probabilistic forecasts. Based on these forecasts, the grid operators can identify critical operating time points to prepare for problems that can occur in the system due to wind power variations in advance. [ABSTRACT FROM AUTHOR]

Energy demand and production of neighbourhoods are central issues in the development of integrated spatial-energy strategies in the framework of recent European Policies. This study provides a comprehensive tool that combines spatial and energy issues with optimization methods to support urban planners in the decision-making process for urban energy strategies. By adopting an integrated approach, optimized urban energy scenarios aimed at reducing CO 2 emissions are developed and results are shown in spatial-energy maps. Through the application of the proposed method, current urban energy demand is determined and potential local production of electrical energy due to the introduction of renewable energy systems is assessed. The insertion of renewable energy systems allows configuring a network of energy exchanges where buildings are considered able to share energy through physical connections. The optimization of energy exchanges among buildings is carried out by using a model based on complex networks and is represented in maps, developed in GIS, allowing the integration between energy evaluations and spatial planning. As case study, the method has been applied to a neighbourhood of the municipality of Catania in Southern Italy. [ABSTRACT FROM AUTHOR]

The difference in electricity pricing based on the time of power use has led to load shifting from peak to off-peak hours in hybrid power systems (HPS). Apart from optimising electricity cost, shifting of the load may also change the capacity of storage in the system. Power Pinch Analysis has been recently applied to guide load shifting aiming to minimise the cost of electricity, considering the peak and off-peak electricity pricing. The HPS was assumed to be ideal with 100% efficiency, which is not achievable in actual operational condition. This work extends the study by scrutinising the effects of peak-off-peak load shifting on the capacity of storage in HPS. The effects of energy losses due to the inefficiency during power conversion, transfer and storage in the HPS are considered in developing shifting heuristics to ensure optimal storage size is achieved. Implementation of the proposed load shifting strategy on a case study demonstrates that a reduction of up to 30% in the storage size can be achieved, which led to a minimum storage cost. The distribution of peak hours' demand to off-peak hours also successfully provide significant savings in the electricity bill. [ABSTRACT FROM AUTHOR]

The trend of global energy demand forecasts a continuous increase in the forthcoming years together with a diversification and differentiation of energy sources. In order to ensure the energy systems transition towards a sustainable functioning mode while avoiding early depletion of energy resources, industrial activities need to foster process improvement. Among energy efficient process design methodologies, pinch analysis and exergy analysis are two powerful methods but each one shows drawbacks. This paper introduces a new methodology that uses the Jacobian Matrix of exergy destruction as a mathematical indicator to couple the Pinch and the exergy analysis and overcome their individual limitations. In the proposed approach, exergy analysis is used not only to assess the exergy losses but also to guide the changes needed in industrial processes structures and operating conditions. And while the pinch analysis considers only heat integration, the proposed methodology allows including other recoverable exergy in a process through thermodynamic conversion. In this paper, the guidelines of the methodology are first detailed. When applied on a basic natural gas liquefaction process, the proposed approach will numerically result in a new improved process comparable to the existing, most widely used natural gas liquefaction process. The main advantage of the methodology is time saving compared to holistic operating conditions improvement as in the traditional process design methods and automatic process structure modification leading to better heat integration. [ABSTRACT FROM AUTHOR]

One of the primary challenges of the power industry, worldwide, is making the capacity investment appropriate for the achievement of security of supply. This challenge is becoming even more relevant as power generation is increasingly based on renewables that are intermittent and seasonally dependent. In this context, policy makers and regulators implement capacity mechanisms that seek to overcome the intrinsic shortcomings of renewables. Failing to do so, given the uncertainty and complexity involved, means either that excessive overcapacity will become persistent and remain idle, or that under-capacity will prompt blackouts and high electricity prices. To help manage the uncertainty and complexity, this paper contributes to a better understanding of the effects of the capacity mechanism on electricity markets with a high share of hydropower – by using a system dynamics modelling approach applied to Colombia. In the past, though the capacity mechanism induced large reserve margins, the system has been at serious risk of experience blackouts and has resulted in extremely high electricity prices over a prolonged period. In the future, worse scenarios are possible: historically-familiar events – when backup plants were not available – may recur when new capacity is delayed, posing an even greater threat to the system. [ABSTRACT FROM AUTHOR]

The main purpose of a Transmission System Operator is to ensure stabile, reliable and efficient operation of its power system. Large-scale integration of renewable energy sources has introduced additional challenges to active control of transmission power systems. Traditionally, generation adequacy has been achieved through investments in generating units and transmission adequacy through investments in transmission lines. However, energy storage can be regarded as both the generation asset, as it reduces peak load and acts as a generator when injecting electricity into the network, and transmission asset, as it can move electricity in time thus reducing congestion and curtailment of renewable energy sources. This paper examines the role of energy storage in increasing power system adequacy and security. A method is proposed to define the charging/discharging schedule of energy storage after a contingency in order to preserve the system within the operating limits and to provide the system operator enough time to redispatch the system and relieve the overloaded lines. The method is applied to an actual part of the Croatian power system using scenarios that describe representative network states. The simulations are performed in a transmission operations and planning software using actual operating data. The results are analysed in details and conclusions on the role of the energy storage in providing transmission system adequacy and security is assessed. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

There are various approaches to developing a 100% renewable energy system and choosing the optimal one depends on a series of factors. This article tackles that problem by comparing two possible ways of developing a 100% renewable energy system, using Zagreb, the capital of Croatia, as a case. The first one is a traditional non-integrated renewable energy system, where each energy sector is developed independently, while the second is based on the smart energy system concept, where different sectors are linked together in order to exploit synergies and increase the efficiency of the system. Scenarios for Zagreb according to these two approaches are developed and modelled in EnergyPLAN. The results show that a smart energy system can reach up to 49% of the total electricity production from intermittent sources on a yearly basis, while a traditional non-integrated system utilizes 50% more biomass than what is assessed to be sustainable. Therefore, a smart energy system is a beneficial option for Zagreb in terms of technical feasibility, while from an economic perspective, the total costs of the two scenarios are essentially at the same level. [ABSTRACT FROM AUTHOR]

Thermo-electric generation represents 70% of Europe's electricity production and 43% of water withdrawals, and is therefore a key element of the water-energy nexus. In 2003, 2006 and 2009, several thermal power plants had to be switched off in Europe because of heat waves, showing the need to assess the impact of climate change on cooling constraints of thermal power plants. An integrated water-power model of the Iberian Peninsula was developed in this study. It includes a physical hydrologic representation, spatially and temporally resolved water demands, management of water infrastructure and a simple power system model. The system was evaluated under present and future climatic conditions using different climate change scenarios. The cost of cooling constraints is found to increase by 220–640 million €/year, for the period 2046–2065 depending on the climate change scenario. Average available capacity of freshwater-cooled thermal power plants is reduced by 16–30% while production is reduced by 5–12% in summer. The power production is shifted from plants equipped with once-through cooling systems (−5 to −14%) towards plants using closed-circuit cooling systems (+41 to +95%). [ABSTRACT FROM AUTHOR]

Burnable off-gases generated in engineering process plants are regularly utilised as energy sources. A common use is for steam production, where excess steam is allocated to power generation turbines. Fluctuating off-gas productions may, however, result in power generation losses from turbine trips, due to insufficient steam. Numerous power co-generation investment models exist, which are typically based on cost minimisations or meeting energy demands. These models do not, however, incorporate plant-specific historic steam profiles and typically use average-based patterns for decision making. This paper presents a novel stochastic mixed integer linear programming model that utilises historic steam profiles to determine optimal turbine investments in terms of the net present value. A further advantage is the ability to investigate the investment and procurement of a, typically very expensive, supplementary energy resource to assist during low off-gas flow periods. The proposed model is solved to optimise over 10 years for an engineering factory seeking to invest into an energy recovery plant. Optimal results demonstrate how natural gas in a fluctuating off-gas environment can increase power generation profits and should be invested in, together with a 30 MW turbine. Furthermore, an average-based approach yields sub-optimal investments and overestimates the net present value beyond 22%. [ABSTRACT FROM AUTHOR]

Optimal operation and production planning are important problems for electric power generation systems. Optimal operation of an energy generation system conventionally refers to the minimization of total thermal fuel cost (TTFC). However, the presence of thermal and hydraulic generation units in a power system requires that hydraulic as well as thermal constraints be added to a problem, which is referred to as a short term hydrothermal coordination problem (STHCP). STHCPs assume that the amount of water in the reservoirs of a hydraulic generation unit has no effect on power generation when its net heads are fixed. This study applied a gravitational search algorithm (GSA) for the solution of a STHCP with fixed head. The probable electrical and hydraulic constraints of the problem have been provided by punishment function method. Line losses of the power system were calculated using the Newton-Raphson load flow method. Two different cases, where transfer capacities of transmission lines were neglected and included, were set up, and the problem was solved for both cases. Transfer capacities of transmission lines were included to make the problem more complex and realistic. Solutions for both cases were discussed. [ABSTRACT FROM AUTHOR]

Bangladesh, currently a low middle-income economy aspires to become a high middle income country by 2021. To achieve such aspiration, the country will have to ensure adequate power supply for its fast growing economy. Bangladesh lacks energy resources for power generation. This paper explores some of the power supply scenarios with special focus on power imports and higher use of renewables. Using the technology rich, least cost optimization model 'The Integrated MARKAL-EFOM System (TIMES)', the authors developed four possible future power supply scenarios for Bangladesh. These scenarios include an energy security framework (based on the Power System Master Plan (PSMP) 2016 report), a high power import scenario, a scenario with higher use of renewables and a combined high power import - high renewables development scenario. The analysis indicates that the present energy security framework ensures energy security with diversifying fuels used for power generation, however, scenarios with high power imports and a high share of renewables (including the combined scenario) bring down the cost of supplying power along with a reduction in expensive fossil fuel imports while maintaining energy security as fuel sources for power generation still remain diversified. [ABSTRACT FROM AUTHOR]

Increasing interest in the successful coordination of electric vehicles and renewable energy sources has recently been shown by researchers and power generation companies, in large part due to its impact on de-carbonization of urban areas and its capability of contributing towards ancillary services. Nevertheless, this coordination requires a bi-directional communication infrastructure, between combined electric vehicles, renewable energy systems, and power plants since one of the main reasons of this combination is to address the temporal fluctuations in renewable power generation. This bi-directional communication enables the power grid to adapt to different power source structures and improves the acceptability of intermittent renewable energy generation. Whereas electric vehicles equipped with lithium-ion batteries appear to be feasible options for stationary energy storage systems, known as a new distributed generation, the flexibility of electric vehicles in vehicle-to-grid connections is completely dependent on the maximum practical capacity and state of charge of each vehicle. Hence this infrastructure for the integration of electric vehicles as new distributed generation and renewable energy systems with electrical grids, emphasizes the need for an off-board state estimation of electric vehicles in aggregators. Moreover, an accurate estimation of the state of health and state of charge when electric vehicles are not charged or discharged by a constant current profile is required to overcome the challenges of existing methods. Each of introduced methods has different limitations, which are presented in this article. This article proposes a novel off-board state estimation technique for such parameters as state of charge and maximum practical capacity by employing a metaheuristic algorithm and an adaptive neuro-fuzzy inference system to overcome the limitations of existing methods. Due to drawbacks of filtering techniques, inverse theory is used in this article to convert the filtering problem to an optimization problem in order to take advantage of its capability. The results exhibit not only a high convergence rate (low settling time) but also a high robustness. [ABSTRACT FROM AUTHOR]

The electricity sector in Malaysia is dominated by fossil fuels. This has immensely increased the amount of CO 2 emissions and other pollutants. The objective of this paper is to investigate the potential for inter-fuel substitution between the four major fuels of coal, gas, oil, and hydropower that are currently being used in the generation of electricity in Malaysia. Using a translog production function, the study adopted a ridge regression procedure to estimate the parameters. The results suggest a potential for substitution among the fuels. Hydropower is observed to be a substitute for other fossils fuels which is an indication that the country can gradually move towards adopting a cleaner fuel in the generation of electricity. We also extended the analysis to Thailand and China to show the consistency of the method when applied to different countries. [ABSTRACT FROM AUTHOR]

A solar thermal system for steam generation was built in the city of San Carlos, Salta province, Argentina. This system is a Linear Fresnel Collector (LFC) used for producing steam for many applications, such as vegetable drying, water desalination, and power generation. A steam engine was coupled to this LFC for power generation. This paper shows the steam engine simulation, where thermal and dynamic equations were developed and written on the Simusol program. Mechanical power output and other parameters of the engine were also simulated as well as steam consumption, in order to establish laws in relation with mechanical load on axis and regulate the rpm regime and inlet pressure for optimal steam engine operation. The results of the simulation of power output are compared with experimental measurements. The steam engine was tested, and the obtained experimental results demonstrate the feasibility of generating power (i.e. 2 kW ± 5% (288 rpm) or 8 kW ± 2% (400 rpm)). Furthermore, it is found that the experimental measurements are in an acceptable agreement with the simulation outcomes of the analytical model. Finally, knowing the steam engine behavior allows to optimize the solar energy resource use for power generation. [ABSTRACT FROM AUTHOR]

In recent years, the energy crisis severally appears due to the enormous human development. The renewable energy is a new source for world energy demand nowadays, especially the wind energy. Generally, wind energy is the most promising source for electric power demand in world because of the availability of the high wind speed around the year in several locations. This work investigates the drag type wind turbines, which have strong potential in small electric power generation demands. The scenario of this work is divided into two sections; the first one is the numerical analysis for the conventional Savonius with fully optimizing for the shape of the blade using a genetic algorithm. This optimization is performed to maximize the power coefficient with the same dimension of the conventional Savonius turbine. The second part is conducted experimentally to measure the performance of the conventional Savonius with the two and three blades; in addition, the optimal blade design (S shape) is tested to compare the performance of this new design with the conventional one or standard semi-circular blade. The results indicated that the captured efficiency of the optimal shape blade has the optimum value with 28% in contrasts to 14 and 10% for the two and three blades respectively. [ABSTRACT FROM AUTHOR]

With the scale of wind turbine increasing, the obstructing effect of wind turbine to the surrounding flow of local terrain is getting more remarkable. This influence is seldom considered in current micro-siting of complex-terrain wind farms. The present paper investigates the flow around hills with different Height/Width (H/W) ratios, as well as the interactions between the surrounding flow using three dimensional numerical simulations. A 2 MW wind turbine is placed on five different locations. The simulation results show that the power production could be over-predicted by more than 10% if the wind turbine is not modeled in the computational processes. The H/W ratio which has significant influence on the flow structure around the hill. For the hill with a small H/W ratio, the surrounding flow has little variation with and without wind turbine. For the hill with a large H/W ratio, large scale flow separation occurs on the lee side under the wind turbine disturbances. The flow separation on the lee side also occurs when the wind turbine is located upwind in certain distance to the hill. The results indicate that the mutual interactions between wind turbine and terrain must be considered in the micro sitting of complex-terrain wind farms. [ABSTRACT FROM AUTHOR]

Nuclear superheated-steam supply systems (Su-NSSS) produces superheated steam flow for electricity generation or process heat. Although the current Su-NSSS control law can guarantee satisfactory closed-loop stability, which regulates the neutron flux, primary coolant temperature and live steam temperature by adjusting the control rod speed as well as primary and secondary flowrates, however, the control performance needs to be further optimized. Motivated by the necessity of optimizing the thermal power response, a novel multi-layer perception (MLP) based model predictive control (MPC) is proposed in this paper, which is constituted by a MLP-based prediction model and the control input designed along the direction opposite to the gradient of a given performance index. It is proved theoretically that this MLP-based MPC guarantees globally-bounded closed-loop stability. Finally, this newly-built MLP-based MPC is applied to the thermal power control of a Su-NSSS, whose implementation is given by forming a cascaded feedback control loop with the currently existing Su-NSSS power-level control in the inner loop for stabilization and with this new MPC in the outer loop for optimization. Numerical simulation results verify the correctness of theoretical result, and show the satisfactory improvement in optimizing the thermal power response. [ABSTRACT FROM AUTHOR]

We consider an energy-only electricity market where some generation and/or load is uncertain, and where there are flexibility costs, i.e. some conventional power plants have to be scheduled well before real time in order to participate in the dispatch, while for others, additional cost incurs if generation plans have to be adjusted close to real time. In practice, electricity markets are often organized with sequential market clearing, and in this paper, we consider two sequential markets, for instance representing a day-ahead and a real-time market. We compare the outcomes of 1) a stochastic market clearing model, i.e. an integrated model that takes into account both markets and the uncertainty, to 2) a myopic market clearing model, where the first market is cleared based only on given bids, and not taking into account neither the uncertainty nor the bids to the second market. Compared to previous literature, our main contribution is that we compare the two different market models with respect to both efficiency and allocation of surplus, and thus the incentives they imply for the market participants. We discuss what information is needed in market agent bids and how that information can be manipulated. While the stochastic market clearing gives a solution with a higher expected social welfare, it poses several challenges for market design. The stochastic dispatch may lead to a dispatch where the day-ahead prices deviate from the bid curves to the first market. This can lead to incentives for self-scheduling, in that it may require market participants to accept prices that deviate from the marginal costs or benefits corresponding to the scheduled quantities. Our analysis shows that the intermittent producer has an incentive to deviate from the system optimal plan in both the myopic and stochastic model, and this incentive is particularly strong under the myopic model. We also discuss how the expected social welfare of the market outcome under stochastic market clearing depends on the quality of the information that the system operator will base the market clearing on. In particular, we show that an intermittent producer may have an incentive to misreport the probability distribution for its generation. [ABSTRACT FROM AUTHOR]

In response to the Fukushima nuclear accident, Switzerland has targeted to phase out nuclear power by 2050. Two diametrically opposite pathways to accomplish Switzerland's nuclear phase-out are quantitatively investigated for the year 2035 using a novel high-resolution power systems simulation framework. The first pathway, “Island in Europe”, installs new natural gas power plants to ensure a self-sufficient Swiss energy system. The second pathway, “Battery of Europe”, increases Switzerland's engagement with central Europe with new pumped hydro storages and increased cross-border electricity trade of European renewable energy. The results show that the “Battery of Europe” scenario enables a threefold increase in financial surplus of cross-border electricity trade compared to the “Island in Europe” scenario. This surplus translates to 15–23% lower domestic Swiss electricity prices, thereby enhancing the competitiveness of the Swiss marketplace; however, Switzerland is then exposed to more technical and political engagement with its neighbours. Additionally, successful implementation of the “Battery of Europe” scenario requires reinforcing 5% of the Swiss transmission grid, which necessitates more streamlined legal processes for new transmission infrastructure. Along a different political dimension, electricity price reductions of up to 22% are possible if the targeted increase of efficiency in Switzerland's energy policy is accomplished. [ABSTRACT FROM AUTHOR]

As wind power provides an increasingly larger share of electricity supply, the challenges caused by wind power intermittency have become more and more prominent. A better understanding of wind power intermittency would contribute to mitigate it effectively. In the present study, the definition of wind power intermittency is given firstly. Based on the definition, wind power intermittency is quantified by duty ratio of wind power ramp (DRWPR). This index provides system operators quantitative insights into wind power intermittency. Furthermore, some characteristics of wind power intermittency can be extracted by the index, such as the differences between wind speed intermittency and wind power intermittency, the differences of wind power intermittency between different scales and so on. The wind power intermittency of a Chinese wind farm is studied in detail based on the proposed index and historical data. [ABSTRACT FROM AUTHOR]

In the last decades, the weight of renewable energies sources (RES-E) in the electricity generation mix of most European countries has considerably increased, constituting an important contribution to the transition towards a low-carbon economy. Until very recently, RES-E were supported by favorable investment mechanisms specially designed to endorse investment in RES-E. More recently, as RES-E are becoming increasingly more competitive (especially wind and solar photovoltaic), RES-E are starting to be remunerated according to market mechanisms. This has generated a lively debate on the economic pros and cons of dispatching RES-E in the market. This paper contributes to this debate by developing a game theoretical model in the context of which we analyze how the inclusion of RES-E in the electricity wholesale market affects equilibrium outcomes under demand and supply uncertainty. Then, we examine how the inclusion of RES-E in the electricity wholesale market impacts firms' incentives to invest in conventional energy sources, characterizing the optimal investment under demand and supply uncertainty. We find that, when RES-E capacity and asymmetry in firms' marginal production costs are sufficiently high, RES-E producers may strategically reduce the market price, in order to evict the less efficient conventional source in that period. Although, in the short-run, this strategy may actually favor energy consumers (since prices are lower), the expectations of inactivity periods (regardless of whether they arise for strategic or market reasons) may negatively affect investment in back-up capacity, possibly leading to an increase in future prices (since less back-up capacity is available). Finally, we provide an analytical characterization of optimal investment levels in conventional energy sources under demand and supply uncertainty. [ABSTRACT FROM AUTHOR]

This paper proposes a novel hybrid technique for prediction of power generation in wind farm. Using this technique, the effective number of input parameters is determined by data correlation analysis. Then, the type of the effective number of parameters are selected from current parameters via neural network. The WT (wavelet transform) is used for filtering input data related to wind power; while, neural network ‘RBF (Radial basis function)’ is utilized as a preliminary predictor. Main predictor motor is combined three neural networks of MLP (Multilayer perceptron) with learning algorithms: BR (Bayesian regularization), RP(Resilient back propagation), and LM(Levenberg Marquardt). The heuristic technique ‘WIPSO (Weight improved particle swarm optimization)’ is used to improve the accuracy of predictions and escape from local minimum to optimize weights of neural networks. Input data is realistic data of wind farms in Southern Alberta, Canada for recent years. The data is a complete set of wind power and five meteorological characteristics including wind speed, wind direction, temperature, air pressure and humidity. Simulation results verify appropriate selection of the number and type of input parameters and heuristic algorithm application. Additionally, the absolute superiority of this technique is validated compared with the other methods. Prediction error is also reduced perceptibly. [ABSTRACT FROM AUTHOR]

With the rapid development of cascade reservoirs, the joint operation chart of cascade reservoirs and its optimization methods have been widely researched. Aimed at the defects of the conventional two-stage Progressive Optimality Algorithm (POA) in the optimization of energy storage operation chart, this paper proposed a new multi-stage POA optimization model. It took the traditional reverse calculation result as the initial solution, and expanded the two-stage optimization mode of conventional POA to three-stage mode, four-stage mode, or higher stages mode, and implemented the iterative calculation by taking the result of lower stages POA as the input of higher stages POA, until the result converged. In addition, enumeration method was used to iterate over all the possible combinations in local optimization to improve the efficiency of local search. In order to test and verify the rationality and validity of the proposed model, two cascade reservoirs had been taken as the instances of case study, compared with conventional two-stage POA, results showed that the power generation of Li Xianjiang and Three Gorges cascade reservoirs by the proposed multi-stage POA can respectively increase by 0.055% ($32000) and 0.077% ($3900000). So the economic benefits are remarkable, and the proposed model is reasonable and effective. [ABSTRACT FROM AUTHOR]

This paper examines the costs of electricity generation by the power projects under the Clean Development Mechanism (CDM) of the Kyoto Protocol. Using the CDM project-specific data, the levelized cost of electricity (LCOE) for each project is calculated. Based on the calculated LCOEs, an electricity cost function is estimated and the average cost curves for different renewable technologies, project locations, and time are derived. The results show that LCOE decreases, at a decreasing rate, with the scale and duration of the projects while the degree of economies of scale and time significantly vary across different technologies and locations. Results further show that the distribution of power projects in the CDM energy portfolio or a given location does not quite follow the relative cost structure for different technologies. Also, the distribution of different types of projects across different regions or host countries does not strictly follow the relative average costs for different locations. As the power projects under the CDM earn additional revenues from the sales of Certified Emissions Reduction credits (CERs), the CDM enables renewable electricity to be more competitive which crucially depends on CER prices, costs of CER issuance, and the length of crediting period. [ABSTRACT FROM AUTHOR]

Electrical power system (EPS) forecasting plays a significant role in economic and social development but it remains an extremely challenging task. Because of its significance, relevant studies on EPS are especially needed. More specifically, only a few of the previous studies in this area conducted in-depth investigations of the entire EPS forecasting and merely focused on modeling individual signals centered on wind speed or electrical load. Moreover, most of these past studies concentrated on accuracy improvements and usually ignore the significance of forecasting stability. Therefore, to simultaneously achieve high accuracy and dependable stability, a hybrid forecasting framework based on the multi-objective dragonfly algorithm (MODA) was successfully developed in this study. The framework consists of four modules—data preprocessing, optimization, forecasting, and evaluation modules. In this framework, MODA is employed to optimize the Elman neural network (ENN) model as a part of the optimization module to overcome the drawbacks of single-objective optimization algorithms. In addition, data preprocessing and evaluation modules are incorporated to improve forecasting performance and conduct a comprehensive evaluation for this framework, respectively. Empirical results reveal that the developed forecasting framework can be an effective tool for the planning and management of power grids. [ABSTRACT FROM AUTHOR]

Gas/steam combined cycle power plants are being extensively used for power generation due to their better performance as compared to gas turbine based or steam turbine based power plants operating in isolation. These combined cycle power plants have natural aspiration in compressors where the state of ambient air entering it, significantly affects the work requirement of compressors and thus affects the overall combined cycle power plant performance. It is felt that in tropical countries with significant seasonal variations, when the atmospheric temperatures become quite high during some months in a calendar year, the cooling of ambient air before entering compressor using the energy available in combined cycle power plant may help in improving the overall plant performance. In view of this a combined cycle with ability of producing power and provision of simultaneous cooling of air entering the compressor and cooling of gas turbine blades through ammonia water mixture and steam using closed loop cooling scheme has been studied in this paper. A comparative analysis of the combined cycle's considered shows that for a cycle pressure ratio of 40 and turbine inlet temperature of 2000K maximum work of 2093 kJ/kg of compressed air is obtained for ammonia mass fraction of 0.6 for the combined cycle using only ammonia water mixture as coolant where as maximum first law efficiency and second law efficiency of 62.6% and 59.67% are being achieved for ammonia mass fraction of 0.7, for the same configuration and at an ambient temperature of 30 °C. Cooling load of 22 kW is observed to be maximum for the configuration using steam and ammonia water mixture as coolant and for an ambient temperature of 50 °C at the cycle pressure ratio of 40, turbine inlet temperature of 2000K and ammonia mass fraction of 0.6. [ABSTRACT FROM AUTHOR]

Forecasting oil prices is an important and challenging matter, because of its impact on many economic and non-economic factors. Because factors such as economic growth, political events, and psychological expectations affect oil prices, forecasting oil prices has great uncertainty. There is no consensus among researchers about the techniques and models used to predict oil prices; hence, methods of forecasting with higher accuracy and lower error should be developed. It is important to combine different models and investigate different approaches, especially time-varying forms. In this paper, the exponential smoothing model (ESM), autoregressive integrated moving average model (ARIMA), and nonlinear autoregressive (NAR) neural network are combined in a state-space model framework to increase the accuracy of forecasting that accounts for problems in accurate diagnosis of linear and nonlinear patterns in economic and financial time series such as for crude oil prices. In the proposed hybrid model (PHM), time-varying weights for each model are determined by Kalman filter. The PHM is used on monthly OPEC crude oil prices and WTI crude oil spot prices. The numerical results show a decrease in forecasting error using the PHM compared to its constructive models, the equal weights hybrid model (EWH), the genetic algorithm weights hybrid model (GWH), and the Zhang's hybrid model (ZHM). [ABSTRACT FROM AUTHOR]

Distributed energy resources within local energy systems can be reorganized into a single entity, namely, into an integrated community energy system. This integration provides adequate scale to participate in wholesale markets. This paper proposes a day-ahead scheduling strategy for the integrated community energy system in a joint energy and ancillary service markets. The uncertainty of energy market prices, ancillary service market prices, wind power, and photovoltaic power are taken into account. The proposed integrated community energy system organizes combined cooling, heating, and power systems in different areas, and aggregates diverse distributed energy resources. Meanwhile, regulation up, regulation down, spinning, and non-spinning reserves are simultaneously employed in the proposed model. The robust optimization approach is adopted to handle uncertainty, and confidence intervals of uncertain parameters are predicted by a Gaussian process method. Finally, simulations of a real regional multi-energy system demonstrate the effectiveness and applicability of the proposed model. [ABSTRACT FROM AUTHOR]

This research analyzes proposed determinants of electricity consumption in Jordan during the period 1986–2015. For the upcoming years, Jordan's electricity consumption projections expected to exceed electricity generation capacities. Therefore, to understand electricity consumption key determinants, six independent variables were used: Gross Domestic Product (GDP), electricity prices, population, urbanization, structure of economy, and aggregate water consumption. A multivariate model was constructed using annual data to examine the influence of the independent variables on electricity demand. Johansen Cointegration test is used to examine the long-term relationships in the model, and Vector Error Correction Model (VECM) is utilized then. VECM regression results show that GDP, urbanization, structure of economy and aggregate water consumption are significant and positively related to electricity consumption, while electricity prices are significant and negatively related to electricity consumption. Population showed significant positive effect on electricity consumption in the short run. The result of VECM implies that there is a need to invest more in green energy projects, ban importing low efficiency electrical appliances and review refugee reception policy in place. [ABSTRACT FROM AUTHOR]

The power generation from renewable sources is an interesting alternative to the diversification of the energy matrix of a country. This paper presents a probabilistic valuation method for power generation projects from renewable sources. It focuses on biomass plants that use sugarcane bagasse. The main objective is to bring a wider knowledge surrounding projects for investors that participate in energy auctions. Therefore, the highlight is for the net present value that allows us to analyze the financial viability of projects. Two stochastic variables are involved in the problem, the power generation and the energy price in the short-term market. Monte Carlo Simulation and Discounted Cash Flow methods are employed. A case study is carried out for a biomass plant. Sensitivity analysis is presented for different values of investment, bid, and minimum attractive rate of return. For each simulated scenario, the probability distribution of the net present value, the average net present value, and the internal rate of return are calculated. For the analyzed case study, the return of the project is more sensible to the bid value than the investment cost. The proposed method can be used as a tool to assist investors in energy auctions from renewable sources. [ABSTRACT FROM AUTHOR]

A constraint to represent maximum likelihood of occurrence for coexistent variable demand and variable generation is proposed for inclusion in the conventional static load dispatch. The constraint allows direct representation of cross-correlations between variable power levels, which makes the dispatch appropriate for scenarios with high penetration of renewable power generation. At optima, the augmented dispatch converges to utility generation cost that is “most likely to occur”; and can therefore provide useful support for generation resource planning by accommodating demand and generation variability. Formulation of the maximum likelihood load dispatch, as well as Karush-Kuhn-Tucker conditions for its optima, are presented in the paper. Features of the optima are established by three-generator and twenty-generator case studies that represent both centralised and distributed variable generation scenarios. [ABSTRACT FROM AUTHOR]

Coal-fired thermal power plants (TPPs) had been generally designed to cover base loads of electricity consumption. Nowadays, they should be flexible to participate in the primary frequency control of electric system, especially because of increased number of wind and solar plants with intermittent electricity production. In this paper a new method for the primary power control in TPPs is presented, based on the feedwater flow rate changes between the feedwater heaters (FWHs) and an additional high pressure economizer. The achieved primary power control reserve is demonstrated by measurements at the lignite-fired 650 MWe TPP after its retrofit by the installation of the high pressure economizer in parallel with FWHs. In addition, the TPP transient operation during the primary control are simulated and analyzed with the developed thermal-hydraulic model of the steam turbine heat regeneration system. The control reserve of approximately 10 MWe is shown both by measured data and results of numerical simulations. The control reserve is originally provided by the fresh steam throttling in front of the turbine, but this throttling can be reduced by the application of the new method. The rates of change of wall temperatures of FWHs tubes are within allowed limits during the transients. [ABSTRACT FROM AUTHOR]

This paper presents an assessment of alternative, long-term energy supply and low-carbon strategies for the Philippine power sector from 2014 to 2040 using TIMES model. It examines the potential contribution of renewable energy to diversify the Philippine energy supply-mix to meet future electricity demands. The reference scenario compares the impact of four alternative policy goals: (1) carbon tax, (2) targeted renewable-based power generation, (3) limited coal share in supply-mix, and (4) renewables subsidy. The reference scenario shows a significant increase of the share of coal-based power generation and import dependency of fossil-fuel increases from 227 PJ in 2016 to 1073 PJ in 2040. The model results for the alternative policy scenarios show a large potential for renewable energy-based power generation. The alternative policy options show a significant decrease of import dependency in the energy supply-mix for power generation. Most alternative policy scenarios project a higher total system cost, with the exception of the subsidy scenario. System cost increases only 2.6% in the renewables target scenario relative to the reference scenario. However, long-term benefits from investing in the alternative policy options would need to be considered, including diversification of energy supply-mix, improved energy security, and progress toward a low-carbon society. [ABSTRACT FROM AUTHOR]

The main aim of this study is to present an energy transition roadmap for Pakistan in which the total energy demand by 2050 is met by electricity generated via renewable sources, in particular, solar photovoltaic. Efforts have been made to assess the energy and cost required for the transition towards a sustainable energy supply covering the demand for power, desalination and industrial gas sectors. Hourly resolved model was used and optimization was carried out for each time period (transition is modeled in 5-year steps) on the basis of assumed costs and technological status till 2050 for all energy technologies involved. Solar PV dominates the installed technologies and contributes 92.7% and 96.6% in power and integrated scenarios. Seawater desalination sector dominates the integrated scenario and clean water demand is found to be 2.8⋅10 11 m 3 by 2050. The levelised cost of electricity declines from 106.6 €/MWh in 2015 to 46.2 €/MWh in 2050 in power scenario. In country-wide scenario, gas storage rules from 2040 to 2050 in terms of total storage capacities while battery storage is prominent in terms of storage output. The results indicates that, 100% renewable system is cost competitive and least cost option for Pakistan's future energy transition. [ABSTRACT FROM AUTHOR]

Organic Rankine Cycle (ORC) is promising in utilizing low-medium thermal energy, and solar energy is widely considered as the most attractive renewable energy for the future. Consequently, electricity production by coupling ORC and solar energy can reduce the fossil fuel consumption and lower the CO 2 emissions over the world. However, the intensity of solar radiation keeps changing throughout the daytime, so it is important to study the daytime performance of solar-ORC system to guarantee a proper operation. Based on the discretized parameter model built in Dymola, dynamic performances of a small-scale power plant driven by parabolic trough collector (PTC) under clear sky and cloudy sky conditions are analyzed in this paper, respectively. The results show that degree of super heat, evaporation pressure and output power are relevant to direct normal irradiance (DNI) and follow the variation of DNI from morning to afternoon. Particularly, this paper pays attention to analyze the system's responses to the cloud blockage using the dynamic model. It shows that short period (5 min) of cloud blockage of the sun poses no severe influence, while the cloud occurring at morning can cause the system to break down easily. In addition, a conventional PID control strategy is considered for the PTC-ORC system under the weather condition of cloudy sky. The optimized system can generate 105.54 kWh and the system without control can generate 84.95 kWh. The generation can improve 24% compared to the system without control. [ABSTRACT FROM AUTHOR]