Search

Seasonal climate variations affect electricity demand, which in turn affects month-to-month electricity planning and operations. Electricity system planning at the monthly timescale can be improved by adapting climate forecasts to estimate electricity demand and utilizing energy models to estimate monthly electricity generation and associated operational costs. The objective of this paper is to develop and test a computationally efficient model that can support seasonal planning while preserving key aspects of system operation over hourly and daily timeframes. To do so, an energy system optimization model is repurposed for seasonal planning using features drawn from a unit commitment model. Different scenarios utilizing a well-known test system are used to evaluate the errors associated with both the repurposed energy system model and an imperfect load forecast. The results show that the energy system optimization model using an imperfect load forecast produces differences in monthly cost and generation levels that are less than 2% compared with a unit commitment model using a perfect load forecast. The enhanced energy system optimization model can be solved approximately 100 times faster than the unit commitment model, making it a suitable tool for future work aimed at evaluating seasonal electricity generation and demand under uncertainty. • An energy system optimization model is repurposed for seasonal planning. • Results are compared with a unit commitment model under two demand forecasts. • The enhanced energy system model can generate results nearly 100 times faster. • This model performance makes it possible to do seasonal planning under uncertainty. [ABSTRACT FROM AUTHOR]

Transition to low carbon energy system requires number of metals that are required in other sectors, have limited availability, produced mainly as byproducts in limited countries, and classified critical, which may shift energy system traditional geopolitics. China is main producer of several metals and one of their main consumers, which may have implications on their use in other sectors and in low carbon technologies in other countries. We aim at analyzing electricity generation technologies (EGT) in China, their metals requirements, and their global implications. Metals included are Ag, Te, In, Ge, Se, Ga, Cd, Nd, Dy, Pr, Tb, Pb, Cu, Ni, Al, Fe, Cr, and Zn. Dynamic material flow-stock model and seven energy scenarios are used, combined with material scenarios. Results indicates that most critical metals for energy system are Te, Cr, Ag, Ni, In, Ge, Tb, and Dy, however, technology advancements are expected to reduce risks associated with Ag, In, Dy, and Tb. Energy scenarios are difficult to realize without adequate supply of metals from primary sources, combined with increasing resources efficiency, recycling, and careful selection of technologies. Energy models used to produce these scenarios should include energy-material nexus. Biggest global implications expected for Ge, Te, Tb, and Dy. • Electricity technologies and their metals requirements in China are analyzed. • A dynamic material flow-stock model and seven energy scenarios are used in the analysis. • Te, Cr, Ag, Ni, In, Ge, Tb, and Dy are the most critical metals for Chinese energy system. • China high metals demands in energy sector may constrain their use in other countries and sectors. • Metals availability should be included in energy models due to their impacts on scenarios realization. [ABSTRACT FROM AUTHOR]

Growth of electricity generation from variable renewable resources like wind and solar has raised questions about future grid stability. This paper used several renewable energy penetration scenarios to determine when an electric grid might be more vulnerable to frequency contingencies, such as a generator outage. Unit commitment and dispatch modeling was used to quantify system inertia, an established proxy for grid stability. A case study of the Electric Reliability Council of Texas grid was used to illustrate the method. Results from the modeled scenarios showed that the Texas grid is resilient to major grid changes, even with relatively high penetrations (∼ 30% of annual energy generation compared to 18% in 2017) of renewable energy. However, retiring nuclear power plants and private-use networks in the model led to unstable inertia levels in our results. When the system inertia was constrained to meet a minimum threshold in our model, multiple coal and natural gas combined-cycle plants were dispatched at part-load or at their minimum operating level to maintain stable system inertia levels. This behavior is expected to expand with higher renewable energy penetrations and could occur on other electric grids that are reliant on synchronous generators for inertia support. [ABSTRACT FROM AUTHOR]

Our world's future is strongly connected to energy consumption trends. There are bi-directional relations between energy consumption and the average temperature of Earth, leading to positive causal loops. Increasing temperatures cause activity of more cooling systems most of which are electrified by burning hydrocarbons that consequently yield more carbon dioxide concentration and warmer climates. This paper is a trial to estimate the loop gain by employing a bottom-up regional model. The model is a spreadsheet containing sets of parameters and variables to estimate electricity used for cooling buildings in the residential and commercial sectors of 12 regions all around the world. The share of fossil-fuel based power plants determines each region's contribution to CO 2 emissions. Then, by processing data on the global emission trend and land temperature anomaly, a linear ARMAX relationship is estimated to compute the loop gain. The results show that, even in the optimistic scenario of IPCC (A1B), emission from cooling electricity will double up by the end of the century. With the estimated 1 + 1.4 × 10-6 loop gain, even if fossil-fuel electricity generation is gradually reduced to 40%, after a short fall, it will start growing again in the mid-century. • Electricity need for cooling buildings in summers is estimated for 12 world regions. • Carbon emitted by fossil-fuel power plants for the cooling electricity is estimated. • A linear model is used to relate emissions to the land temperature anomaly. • Loop-gain is estimated then by multiplying the two estimated coefficients. • The positive loop will bring up acceleration again even in optimistic scenarios. [ABSTRACT FROM AUTHOR]

Long term time series of variable renewable energy (VRE) generation and electricity demand (load) provide important insights into the feasibility of fully renewable power systems. The coverage of energy statistics is usually too short or the temporal resolution too low to study effects related to interannual variability or the impact of climatic extreme events. We use time series simulated from climate data to assess the frequency, duration, and magnitude of extreme residual load events of two fully renewable power scenarios with a share of VRE generation (wind and solar PV) of about 50% for the case of Sweden. We define residual load as load – wind – PV – nuclear generation. Extreme residual load events are events that exceed the balancing or ramping capacities of the current power system. For our analysis, we use 29 years of simulated river runoff and wind and PV generation. Hourly load is derived from MERRA reanalysis temperature data by applying statistical models. Those time series are used along with historic capacity and ramping restrictions of hydro and thermal power plants in an optimization model to minimize extreme residual load events. Our analysis shows that even highly flexible power systems, as the Swedish one, are affected by climatic extreme events if they increase their VRE shares. Replacing current nuclear power capacities by wind power results on average in three extreme residual load events per year that exceed the current power system's flexibility. Additional PV generation capacities instead of wind increase the number of extreme residual load events by about 4%, as most events occur during the winter month when solar generation is close to zero and thus not able to counterbalance low wind events. Contrarily, overproduction and the need to curtail VRE generation become more pressing with higher shares of PV. In the discussion we highlight measures that could provide additional balancing capabilities to cope with the more frequent and severe residual load events in a fully renewable power system with high shares of VRE generation. • Load during winter is negatively correlated with wind power and natural river runoff. • Annual residual loads vary between 51 and 72 TWh in a fully renewable power system. • Two out of three years exceed the balancing capacities of the current power system. • The longest extreme residual load event lasts 18 h with a maximum lack of capacity of 4 GW. • Additional flexibility measures can avoid loss of load events in fully renewable power systems. [ABSTRACT FROM AUTHOR]

This work demonstrated the possibility of bioelectricity generation using microbial fuel cell technologies from sugarcane molasses by a bacterial strain isolated from molasses. The strain identified according to 16S rRNA as Brevibacillus borstelensis STRI1. Sugarcane molasses could be used as a substrate in MFC, because of its high sugar content. When the bacterial strain was used as biocatalyst and sugarcane molasses as a substrate in MFC. The voltage increased rapidly over time recording 990 ± 5 mV in open circuit voltage (OCV), and 453 ± 6 mV in closed circuit voltage (1000 Ω) after 10 days of operation. The power density (P max) determined from the polarization curve, and it was 188.5 mW/m2 with an initial concentration of sugarcane molasses 1 ml (1632 mg/L as COD). While the coulombic efficiencies (CEs) ranged from 59.8 to 28.03%, related to initial concentrations of 0.3 ± 0.05 to 2.0 ± 0.15 g/L. The COD removal was determined and it was 11.7% after 5 days and reached to 81.7% by the end of the operation (30 days). These results suggested that bioelectricity could be generated from sugarcane molasses by Brevibacillus borstelensis STRI1. • Electricity can be produced from sugarcane as a substrate. • Brevibacillus borstelensis STRI1 could be used as a catalyst in MFC. • The power density increased by increasing sugarcane concentration. • Sugarcane degradation were elucidated through COD removal & electricity generation. [ABSTRACT FROM AUTHOR]

Standalone solar photovoltaic systems are increasingly being distributed in Ethiopia, but these systems are sub-optimal due to their intermittent power supply. A hybrid system that integrates and optimizes across solar photovoltaic and complementary energy sources, such as wind and diesel generation, can improve reliability, and reduce the unit cost of power production. This study assesses the potential of a hybrid system to electrify a remote rural village in Ethiopia. The Hybrid Optimization of Multiple Electric Renewables model is used to assess primary data, develop a load profile and identify the optimal least-cost system option for the village. A sensitivity analysis was performed to determine the effect of variations in solar radiation, wind speed, and diesel price on optimal system configurations. The results show that a hybrid system with a combination of photovoltaic array, wind turbine, battery and diesel generator is the best option from an economic point of view. To meet the village's daily peak demand of 19.6 kW, energy generation cost is estimated at 0.207 dollars per kilowatt hour and net present cost at 82,734 dollars. The optimal system allows for a reduction of 37.3 tons of carbon dioxide emissions per year compared with diesel-only electricity generation. • Feasibility of photovoltaic-wind-diesel based hybrid system is carried out. • Questionnaire survey based primary data used for load calculation. • Optimization model is used for system optimization and sensitivity analysis. • Model result shows the unit cost of electricity at $0.207 for a feasible system. • Optimal system allows a significant reduction of carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

In this paper we propose an equilibrium model that allows to analyze subsidization schemes to affect locational choices for generation investment in electricity markets. Our framework takes into account generation investment decided by private investors and redispatch as well as network expansion decided by a regulated transmission system operator. In order to take into account the different objectives and decision variables of those agents, our approach uses a bi-level structure. We focus on the case of regionally differentiated network fees which have to be paid by generators (a so called g-component). The resulting investment and production decisions are compared to the outcome of an equilibrium model in the absence of such regionally differentiated investment incentives and to an overall optimal (first-best) benchmark. To illustrate possible economic effects, we calibrate our framework with data from the German electricity market. Our results reveal that while regionally differentiated network fees do have a significant impact on locational choice of generation capacities, we do not find significant effects on either welfare or network expansion. • Analysis of network/generation investment and operation in a bi-level equilibrium model. • Investment and production under regionally differentiated network fees (g-components). • Comparison of the market solutions to a first-best benchmark. • Quantification of economic effects with data for the German electricity market. • G-components significantly affect locational choice but not welfare or network expansion. [ABSTRACT FROM AUTHOR]

This article presents a life-cycle sustainability assessment of electricity generation systems in Portugal, namely coal, natural gas, hydro (large and small), wind, and photovoltaic systems, and evaluates their environmental and socioeconomic impacts. The environmental life-cycle assessment methodology was used to quantify impacts in metal depletion, fossil fuel depletion, global warming, ozone depletion, terrestrial acidification, freshwater eutrophication, aquatic acidification, water scarcity footprint, and toxicity (towards freshwater ecosystems and humans). Socioeconomic impacts were estimated for employment provision, dependence on fossil fuels, capacity factor, and levelised cost of electricity. The results show that electricity based on coal has the highest environmental impacts in all categories except: metal depletion (wind had the highest impacts), ozone depletion (natural gas), water scarcity footprint (large hydro), and freshwater ecotoxicity and human toxicity, non-cancer (photovoltaic). For socioeconomic categories, there was a greater variability. Photovoltaic generated the most employment and wind-based generation was estimated to have the lowest levelised cost, while coal generated the second-highest total employment and the third-lowest levelised cost. Overall, the life-cycle sustainability assessment shows small hydro as the most environmentally and socioeconomically sustainable system. By exposing the trade-offs amongst technologies and sustainability dimensions, this work provides an informed basis for future energy policy in Portugal. • First life cycle sustainability assessment of electricity systems in Portugal. • Coal, natural gas, hydro, wind, and photovoltaic systems were assessed. • 11 environmental indicators and five socioeconomic indicators were analysed. • Non-renewable systems had the worst performance in the majority of indicators. • Trade-offs for renewable systems were identified and discussed. [ABSTRACT FROM AUTHOR]

Abstract Current global environmental challenges require vigorous and diverse actions in the energy sector. One solution that has recently attracted interest consists in harnessing high-quality variable renewable energy resources in remote locations, while using transmission links to transport the power to end users. In this context, a comparison of western European and Greenland wind regimes is proposed. By leveraging a regional atmospheric model specifically designed to accurately capture polar phenomena, local climatic features of southern Greenland are identified to be particularly conducive to extensive renewable electricity generation from wind. A methodology to assess how connecting remote locations to major demand centres would benefit the latter from a resource availability standpoint is introduced and applied to the aforementioned Europe-Greenland case study, showing superior and complementary wind generation potential in the considered region of Greenland with respect to selected European sites. Highlights • Wind resource assessment in Greenland and Western Europe. • Reanalysis and climate modelling data used for wind resource assessment. • Better and complementary wind in Greenland relative to Western Europe. • Potential of enhanced yields in Greenland with development of novel wind converters. [ABSTRACT FROM AUTHOR]

In today's China, the reverse distribution of electricity resources and electricity demand makes large-scale and long-distance transmission of electricity inevitable, resulting in the problem of electricity allocation optimization. To address this problem in the region covered by the China Southern Grid (CSG), the paper establishes an optimized model for electricity generation and interprovincial trading strategies in southern China. Based on data from 2015, this paper simultaneously optimizes electricity generation and interprovincial trading strategies in each of the five provinces. The result shows that interprovincial trading in the CSG-served area can yield significant energy, economic, environmental and interconnection benefits. It can reduce the power supply cost and environmental pressure in Guangdong province, help make Yunnan province a hydropower base in China and a thermal power base in southern China, facilitate the completion of the "West-to-East Power Transmission" project, and partly resolve the issues raised in each province's 13th Five-Year Plan as well as the problem of optimizing electricity allocation in the region covered by the CSG. • We propose an annual total optimized model for electricity generation and interprovincial trading in Southern China. • The model optimizes the electricity trading and transmission routes across regions. • The model considers the generation cost and penalty cost of emitting CO 2 , SO 2 and NO x. • Corresponding policies and proposals are put forward for power grid and five regions in South China. [ABSTRACT FROM AUTHOR]

Abstract Enhanced geothermal systems using supercritical CO 2 (scCO 2 -EGS) as working fluid in place of water provides better heat extraction rate and sequestrates CO 2 in the formations for reducing atmospheric CO 2 content and the greenhouse effect. This paper proposed a numerical three-dimensional fully coupled thermo-hydro-mechanical (THM) model to simulate and evaluate the performances of heat mining and geological carbon sequestration in scCO 2 -EGS embedded in complex discrete fracture networks. The variable thermophysical properties of supercritical CO 2 in response to pressure and temperature are taken into account during the reservoir development. Verification, sensitivity analysis, and convergence for the model are accomplished. The three-spot layout of the practical EGS project at Soultz-sous-Forêts is then simulated using a stochastic DNF model under different operation pressures. The efficiencies and quantities of heat mining, carbon sequestration, and production of electric power for a period of 30 years have been studied and discussed. By verification against analytical solutions, the results demonstrate that the current nuermical model is effective to investigate the details of the multi-physical interactions in scCO 2 -EGS. Highlights • A 3D thermo-hydro-mechanical coupled model for supercritical CO 2 circulated enhanced geothermal systems is proposed. • Temperature-dependent and pressure-dependent thermophysical properties of supercritical CO 2 are taken in account. • Complex discrete fracture network is modelled. • Process of heat mining and carbon sequestration is simulated and investigated. • EGS project at Soultz-sous-Forêts is numerically studied. [ABSTRACT FROM AUTHOR]

Abstract The increasing demand for electricity and concern about global warming mean that electric power generation is required to be more efficient, cleaner, and more cost-effective. Combined-cycle power plants have gradually replaced their simple-cycle counterparts to generate more useful power by adding a bottom cycle to recover more energy from prime mover exhaust gas. There are two types of devices used to produce steam—one is the conventional drum-type heat recovery steam generator, and the other is the once-through steam generator (OTSG). The performance simulation of the former is relatively mature but is more difficult for the later. In this research, a novel simulation method for the thermodynamic performance of a parallel dual-pressure OTSG under both design and off-design operating conditions has been developed. The method has been applied to an OTSG operating in a combined-cycle gas turbine power plant at Manx Utilities, Isle of Man in the UK to demonstrate the effectiveness of the method. Meanwhile, the OTSG performance variation caused by inlet gas energy variation and downstream steam turbine erosion are demonstrated. The simulation results of the OTSG show good agreement with field data. The proposed method may be useful for both researchers and engineers in relevant area. Highlights • A novel performance simulation method for parallel dual-pressure OTSGs is proposed. • A comparison between simulation results and test data for an OTSG shows good agreement. • Impact of gas turbine power setting and steam turbine erosions are demonstrated. • The simulation method can assist preliminary designs and performance analysis of OTSGs. [ABSTRACT FROM AUTHOR]

Abstract The paper proposes a novel improved social spider optimization algorithm (NISSO) for solving optimal power flow (OPF) problem to independently optimize electricity generation fuel cost, power loss, polluted emission, voltage deviation and L index. The proposed NISSO method is first developed in the paper by performing three modifications with intent to improve optimal solution quality and speed up convergence of conventional social spider optimization (SSO). The first and the second modifications are to focus on new solution generation by changing the movement strategy of female spiders and male spiders while the third modification is to fix the female spider rate to an appropriate ratio. The performance of the proposed method is evaluated by testing on three IEEE systems with 30, 57 and 118 buses. As a result, the proposed method has advantages over SSO such as simpler application, fewer number of control parameters, spend less time tuning control parameter values, faster convergence to optimal solutions and more stable search ability. In addition, the proposed method's results are also compared to other existing methods and the indications are that the proposed method can find better optimal solutions, use lower number of generated solutions and faster convergence. Highlights • Novel Improved Social Spider Optimization (NISSO) is first proposed in the paper. • Optimal power flow (OPF) problem is one of the most complicated problems. • NISSO is executed for OPF problem with three IEEE systems with 30, 57 and 118 buses. • NISSO can find high quality solutions of OPF problem with fast search ability. • NISSO is superior to approximately all compared methods for all study cases. [ABSTRACT FROM AUTHOR]

Abstract Waste-fired CHP plants are largely contributing to the base load supply of heat and electricity sectors of several European countries. In such systems, about two-third of the production is heat and about one-third is electricity. In this study, the utilization of a certain portion of the heat production of a waste-fired CHP plant as the heat source of an Organic Rankine Cycle (ORC) is proposed. The main objective is to maximize the share of electricity production of waste-CHP plants instead of a higher heat production rate in a cost-effective way. The inspiration for this idea is that not only electricity is extremely more valued in most of the European energy markets, but also their heat sectors are to be occupied with efficient electricity-driven technologies, e.g. heat pumps. This work presents a detailed thermodynamic analysis of the proposed combined system and the best share of heat supply for driving the ORC unit is investigated. The results show that an electricity efficiency improvement of up to 25% is achievable via this integration while the heat production capacity of the power plant still remains significant. It is shown that the integration picks up of exergy efficiency of the power cycle. Highlights • The combination of a waste-CHP plant with an Organic Rankine Cycle is proposed. • The aim is to maximize power output of the system instead of a higher heat output. • The combined configuration is designed and analyzed thermodynamically. • The power output may increase up to 25% via the proposed integration. • A power-to-heat value of 4.8 is needed to make the system feasible economically. [ABSTRACT FROM AUTHOR]

Abstract Using projections of surface solar radiation and temperature from 23 CMIP5 global climate models for two climate change scenarios (RCP4.5 & 8.5) we quantify the average change in PV electricity production expected in the years 2060–2080 compared to the present (2007–2027). We upsample daily radiation data to hourly resolution with a sinusoidal diurnal cycle model and split it into direct and diffuse radiation with the semi-empirical BRL model as input to a PV electricity generation model. Locally, changes in PV potential from −6% to +3% in annual and −25% to +10% in monthly means are shown. These projections are combined with a PV deployment scenario and show countries benefitting from increased PV yields include Spain, France, Italy and Germany. We also calculate uncertainties when calculating PV yield with input data at daily or lower resolution, demonstrating that our method to derive synthetic hourly profiles should be of use for other researchers using input data with low temporal resolution. We conclude that PV is an attractive and no-regrets investment in Europe irrespective of future climate change, and can continue to play a key role in energy system decarbonisation. Highlights • We simulate future PV potential based on daily CMIP5 radiation and temperature data. • PV output varies locally by −6% to +3% on annual and −25% to +10% on monthly scales. • Southern Europe sees increased PV output, while northern Europe sees a decrease. • Synthetic hourly irradiance based on daily data is necessary for accurate results. • PV is a no-regrets investment in Europe irrespective of climate change. [ABSTRACT FROM AUTHOR]

Abstract Tidal energy is one of the most abundant renewable energy sources. Due to its intermittent nature, the integration of tidal energy within a Microgrid (MG) requires appropriate energy management strategies. Some important considerations are tidal energy generation prediction, energy storage requirements, load profile and demand within the Microgrid, and energy pricing structures. This paper considers an MG scenario that includes a small scale tidal farm near Darwin in north of Australia. A tidal power prediction model is introduced using tidal current speed data. Then, for a fixed-size energy storage system (ESS), an optimal scheduling strategy is devised using Particle Swarm Optimization (PSO) to achieve minimum operating costs in the MG. The work presented in this paper provides a framework for the planning of MGs that include tidal generation in their energy mix. Highlights • Visibility of tidal power in the North of Australia. • Tidal power prediction based on tidal current speed observation. • Optimal scheduling for a tidal Micro-grid using Particle Swarm Optimisation. [ABSTRACT FROM AUTHOR]

Abstract Demand response has proven to be a distributed energy resource of great potential over the last decades for electrical systems operation. However, small or medium size facilities generally have a very limited ability to participate in demand response programs. When a facility includes several generation resources, energy storage systems, or even demand flexibility, the decision-making becomes considerably harder because of the amount of variables to be considered. This paper presents a method to facilitate end users' decision-making in demand response participation. The method consists of an algorithm that uses demand and generation forecasts and costs of the available resources. Depending on the energy to be reduced in a program, the algorithm obtains the optimal schedule and facilitates decision making, helping end users to decide when and how to participate. With this method, end users' capability to participate in these programs is clearly increased. In addition, the method is contrasted by simulations based on real programs developed at the Campus de Vera of the Universitat Politècnica de València. The simulations carried out show that the developed method allows end users to take advantage of the potential of their facilities to provide demand response services and obtain the maximum possible benefit. Highlights • A method to facilitate decision-making in demand response is proposed. • The proposed algorithm enables facilities to participate in demand response programs. • The proposed method maximises the benefits that can be obtained with demand response. • A method to optimise demand response participation is tested. • Participation in demand response with distributed energy resources is facilitated. [ABSTRACT FROM AUTHOR]

Abstract Estimation of the variability in the electrical power production and performance over the life-time of wave energy converters (WEC) is paramount for the economic viability of potential wave farm projects. In this research, the significance of the inter-annual variability in the potential production performance (PPP) is demonstrated, using power conversion matrices of ten pre-commercial WEC devices and an existing 31-year wave hindcast case study from the central shelf of New South Wales, Australia. The variability in the PPP over the intra- and inter-annual time scales is found to be comparable, hence indicating that making predictions merely based on annual and monthly averages could be misleading and that inter-annual fluctuations should be considered in future analysis. The results also show that inter-annual variations in WEC production performance can be significantly higher than that of the wave energy resource (WER) owing to the efficiency of different WECs relative to the local sea state conditions. We also demonstrate that optimization of WEC performance for the local sea state cannot only potentially lead to improved power yields but also a decrease in the intra- and inter-annual variability in PPP. [ABSTRACT FROM AUTHOR]

Abstract Many countries are implementing energy policies that focus on the transformation of national power generation mixes into highly efficient and sustainable systems. In the case of the Spanish electricity sector, regulations applicable to existing coal thermal plants and the proximity to the end of the lifetime of nuclear power plants arise as critical concerns to be addressed. In this respect, a sensible energy strategy is required in order to fill the future gap of coal and nuclear power plants. Within this context, this work applies a novel methodological framework for the prioritisation of 15 energy scenarios formulated for power generation in Spain. In addition to a business-as-usual scenario, alternative ones are built based on potential restrictions on fossil-based technologies and lifetime extensions of coal and nuclear power plants. The novel multi-criteria decision analysis approach for enhanced, sustainability-oriented energy planning is based on the combined use of energy systems modelling, life cycle assessment, and data envelopment analysis. Besides conventional techno-economic results, the evolution of life-cycle indicators endogenously integrated into the energy system model of Spain is provided. The subsequent use of a dynamic data envelopment analysis model leads to identify and rank the most suitable energy scenarios according to sustainability criteria. Graphical abstract Image 1 Highlights • Joint Life Cycle Assessment, Energy Systems Modelling and Data Envelopment Analysis. • 15 scenarios on coal and nuclear extension and penetration of CO 2 capture systems. • Thorough prioritisation of 15 prospective scenarios for power generation in Spain. • Modification of the original ranking according to short/long-term prioritisation. • Proven feasibility of the methodological framework for enhanced energy planning. [ABSTRACT FROM AUTHOR]

Abstract Electricity users are the major players of the electricity systems, and electricity consumption is growing at an extraordinary rate. The research on electricity consumption behaviors are becoming increasingly important to design and deployment of the electricity systems. However, the acquisition of data related to the electricity consumption behaviors is still a major challenge. Data synthesis is among the best approaches to solving the issue, and the key is the model that preserves the real electricity consumption behaviors. In this paper, we propose a hierarchical multi-matrices Markov (HMM) model to synthesize scalable electricity load curves that preserve the real consumption behaviors on three time scales: per day, per week, and per year. To promote the research on the electricity consumption behaviors, we use the HMM approach to modeling two distinctive raw electricity load curves. One is collected from the resident sector, and the other is collected from the non-resident sectors, including different industries such as education, finance, and manufacturing. The experiments show our model performs much better than the cluster-based Markov model. We publish two trained models online, publicly available from http://www.benchcouncil.org/electricity , and researchers are allowed to directly use these trained models to synthesize scalable electricity load curves for further research. Highlights • An adaptive K-Means algorithm was developed to cluster electricity load curves. • A novel hierarchical multi-matrices Markov (HMM) model was proposed. • The HHM model preserved the properties of the electricity load curves. • Two trained HMM models was published to synthesize scalable electricity load curves. [ABSTRACT FROM AUTHOR]

Abstract In this research paper, a novel solar-based integrated energy system with a thermoelectric generator (TEG) is proposed to provide cooling and hydrogen production. The energy integration is performed by establishing a TEG unit instead of the condenser of the double effect LiBr-H 2 O absorption cooling system. The proposed system is comprehensively investigated and compared with the conventional cogeneration system from energy, exergy, and exergoeconomic point of view. To enhance the understanding of the effect of major design parameters on system exergy efficiency, net output work, total cost rate and hydrogen production, a comprehensive parametric study is carried out. In addition, using a developed MATLAB code, multi-objective optimization method based on genetic algorithm is applied to optimize the proposed model and determine the optimal design parameters. The results of exergy and exergoeconomic analysis show that PVT has the highest exergy destruction rate and the cooling set has the lowest exergoeconomic factor. Results of the parametric study indicate that the proposed system with TEG has higher exergy efficiency, higher hydrogen production rate, lower total cost rate, and lower pay back period. Multi-objective optimization results show that, at the optimum point, exergy efficiency and total cost rate of the proposed system are 12.01% and 0.1762 $/h, respectively. Examining scatter distribution, further shows that the high-pressure generator temperature and PV module area are the most sensitive parameters and should be kept at their lowest value. Higher performance indicators and lower economic indicants reveal that the proposed integration method is more suitable from the exergy/exergoeconomic standpoints. Highlights • Developing a new solar based integrated system with thermoelectric generator. • A newly proposed system to provide electricity, cooling and hydrogen. • Comparing performance of the newly proposed model to the condenser based model. • Applying a Multi-objective optimization to determine the optimal parameters. [ABSTRACT FROM AUTHOR]

Abstract Due to slow response of conventional micro gas turbine(MGT) generator system, pulse power load(PPL) will cause large voltage sags and overshoot of direct current(DC) bus voltage, and even lead to instability. In this paper, super capacitor(SC) energy storage system(ESS) is applied to MGT to form a hybrid power generation system. Then the two cooperative control methods of hybrid generation system are proposed. One is the PI-based control algorithm, and the other is the fast power coordinated control method through MGT output power forecast. The fast power dynamic response of SC ESS can compensate for low dynamic response of MGT, which makes the hybrid generation system in equilibrium state of transient power in real time. Voltage of DC bus is smooth, and adaptability of MGT to PPL is enhanced. The second control algorithm is proposed according to power output characteristics of MGT, and has the advantages of fast and balanced power distribution. The algorithm of fast charging and exiting of SC ESS is proposed based on load conditions, and the charging process will not cause any impact. Finally, simulation model is established to verify the effectiveness of the two control algorithms, and the results are compared. Highlights • Supercapacitor energy storage system is applied to MGT to form hybrid generation system. • PI-based cooperative control algorithm of hybrid generation system is proposed. • Instantaneous power cooperative control based on power prediction of MGT is proposed. • Hybrid power generation system is designed seamlessly in frequency domain. • Soft operation of hybrid power generation system under pulse power load is ensured. [ABSTRACT FROM AUTHOR]

Abstract Based on weather and electricity demand data for the period 1984–2013, we develop a system model based on energy balance to determine the size of photovoltaic and wind generation combined with energy storage to provide a firm power supply for Great Britain. A simple graphical methodology is proposed where the required wind and PV generation capacities can be read off from a "system configuration diagram" as a function of the available storage size. We show, by way of illustration, that a reliable supply would be produced by a system based on PV and wind generators generating some 30% more electrical energy (approximately 100 TWh p.a.) than the current electricity supply system if supplemented with 30 days of storage. In terms of generation capacities, the current 82 GW of principally thermal generation would then be replaced by about 150 GW of wind turbines and 35 GW of PV arrays. Highlights • Great Britain power system consisting of wind turbines, photovoltaics and storage. • 100% renewable system producing 30% more electrical energy than the demand. • 30 storage days (25 TWh) for uninterrupted power supply over a 30 year design period. [ABSTRACT FROM AUTHOR]

Abstract Owing to no free lunch theorem, meta-heuristic search algorithms, behaviour and performance are different for solving specific class of optimization problems than another. Further, search algorithms are conceptualized of exploration and exploitation aspects. Ameliorated grey wolf optimization algorithm is proposed to solve economic power load dispatch problem that synergizes between exploration and exploitation aspects. Ameliorated grey wolf optimization procedure coordinates the behaviour of grey wolves, random exploratory search, local random search and opposition learning heuristics. Grey wolf optimization algorithm is considered to perform global search and random exploratory search applied to perform a search in the neighbourhood of already visited search locations. To maintain good solutions and diversity among solutions, opposition based learning has been implemented. The practical aspects i.e. value-point loading effect, avoidance of prohibited operating zones and ramp rate limits, generation limits of generators and satisfaction of power demand constraint are undertaken to solve economic power load dispatch problem. Heuristic search is exploited to handle equality constraints. The proposed algorithm is validated on standard benchmark functions and medium to large electric power systems. Results reveal that proposed technique is a potential method to solve economic load dispatch problems as it competes with recent algorithms undertaken for comparison. Highlights • Economic power load dispatch problem is solved considering practical aspects. • Algorithm performs search in neighbourhood of already visited search locations. • Opposition based learning maintains good solutions and diversity among solutions. • Heuristic search handles equality constraints and inequality constraints of POZ. • Verified on benchmark problems for medium to large electric power generator systems. [ABSTRACT FROM AUTHOR]

Abstract Evaluating which electric power generation technologies should comprise the electricity matrix of a country has become a worldwide issue. Multiple factors should be taken into account and issues such as those to do with social, economic and environmental aspects have to be considered in the decision process. In this paper a decision model based on the FITradeoff method is proposed in order to aid multicriteria decision making in the energy planning context. The originality of the paper comes from accommodating, in the proposed model, situations in which the available information is incomplete, when evaluating electric power generation technologies. In order to illustrate the applicability of the model, eight different electrical energy technologies that form the current Brazilian electricity matrix are evaluated under four dimensions: financial, technical, environmental and socio-economic. A sensitivity analysis was performed in order to check the robustness of the results obtained. The application of the proposed model provides information that could be used in Brazil when drawing up energy policies, thus showing the potential use of the method to solve related problems. Highlights • In this paper a multicriteria model based on the FITradeoff method is proposed. • The preferences of different groups are represented by means of decision profiles. • A sensitivity analysis was conducted and this showed the results obtained are robust. • The evaluation performed could be used when drawing up energy policies. [ABSTRACT FROM AUTHOR]

Abstract This paper describes statistical quantification tools for predicting photovoltaic (PV) production considering uncertainty in PV production at same irradiation levels and PV panel temperatures. When analysing measured data, it is observed that there are different PV power production levels for the same irradiation levels and panel temperatures. These PV power spread out can be caused by different causes, such as dust deposition over the panel, non-ideal working of maximal power point tracking devices, device efficiencies' dependence on power, different temperatures over the PV panel, and others. Due to the stochastic character of these occurrences, they can be challenging when considered in the deterministic mathematical models usually used for PV power prediction. The probabilistic method for PV power production is proposed based on the probability density function with respect to the solar irradiation and the panel temperature. The simulation results are compared among the different models based on the probability density function with respect to the solar irradiation and panel temperature. The best overlapping between measured and calculated PV power production gives the proposed stochastic models dependent only on irradiance. The proposed stochastic model gives a PV energy prediction on a yearly basis with an error of less than 1%. Highlights • The statistic models considering different PV production under same irradiance and panel temperature values are researched. • The model parameters are determined from historical data of PV generation. • Dependence on radiance and temperature of probability distribution functions is proposed. • The probabilistic models are based on the normal distribution have irradiance and temperature dependent parameters. [ABSTRACT FROM AUTHOR]

Abstract The effectiveness of Salinity Gradient Power - Reverse Electrodialysis (SGP-RE) in real practice is still not clearly defined due to the lack of specific studies in literature, being investigations in large part limited to pure NaCl solutions or aqueous mixtures of two salts. In this work, we experimentally assessed the impact of natural feed streams (collected from Licetto river and Tyrrenian sea in Amantea - Italy) in terms of Open Circuit Voltage (OCV) and power density (P d) measured on a lab-scale SGP-RE stack prototype; results have been compared to those obtained when using NaCl solutions having equivalent ionic strength. Highest OCV (3.68 V and 4.09 V) and P d values (0.46 and 1.41 W∙m−2) were observed at temperature of 60 °C for real and synthetic feeds, respectively. The extent of electrical resistances (ion exchange membrane/electrical double layer/diffusion boundary layer) was elucidated by electrochemical impedance spectroscopy (EIS); in particular, a critical effect of real solution on cation exchange membrane (CEM) resistance was detected. Additionally, ionic characterization of process effluents revealed the occurrence of uphill transport of multivalent ions Mg2+, Ca2+ and SO 4 2−. Highlights • Loss of power density is observed for SGP-RE operated with natural feeds. • Electrochemical Impedance Spectroscopy shows a major impact on CEM resistance. • A negligible impact of non-ohmic resistances is observed. • Uphill transport of multivalent ions Mg2+, Ca2+ and SO 4 2− is detected. [ABSTRACT FROM AUTHOR]

Abstract A new cycle combining a heat pump-transformer and a turbine is proposed to simultaneously produce electric power and useful heat. The system was modeled using the ammonia-lithium nitrate mixture. Plots of power, useful heat, energy and exergy efficiencies are shown against the main system operating temperatures. The heat supplied to the system at a relatively low temperature was upgraded by 40 K to a higher useful level, whilst the proposed cycle was able to produce up to 300 kW of electric power at the same time depending on the operating system temperatures. The modeling showed that the overall energy and exergy efficiencies can reach values of up to 61% and 92%, respectively. Comparing the proposed system with an organic Rankine power cycle and an absorption heat transformer operating separately under the same operating conditions reductions in energy use and irreversibilities of up to 32.3% and 21.6%, respectively, could be achieved. In addition, a case study of the integration of the proposed cycle into a cogeneration pulp and paper mill is presented and it is shown that up to 25% of the gas natural supplied to the boilers could be saved together with 210 kW electric power production. Highlights • A new cycle integrating a heat-pump transformer with a turbine has been proposed. • The cycle has the capability to upgrade waste heat and produce mechanical power. • Overall energy and exergy efficiencies reached maximums of 61% and 92%, respectively. • The system can achieve up to 32.3% energy savings compared with separate heat and power cycles. • The AHPTP was integrated into a pulp and paper mill plant with considerable savings. [ABSTRACT FROM AUTHOR]

Abstract An overview of recent developments, trends and challenges in the synthesis, design and operation optimization of energy systems is presented in this manuscript. The static and dynamic optimization problems are stated mathematically, solution methods are mentioned in brief and classification of optimization problems based on the presence and treatment of time is presented. Examples of objective functions in single-objective optimization are given and the need for multi-objective optimization is highlighted. Special reference is made to Prof. Szargut's early statement about the need for optimization with ecological concerns. Emphasis is given to optimal synthesis of energy systems, a subject that is still between (or combines) art and science/technology. Furthermore, it is interesting to note that optimization is applied also during the development of models of systems. Hints are given on further considerations and research needs in subjects such as global optimization, as well as optimization with uncertainty, reliability, maintenance and social aspects. Examples of algorithms appearing in recent publications are given as an indication of the related strong activity. The manuscript closes with general remarks and a rather comprehensive, even though not exhaustive, list of references. Highlights • A variety of methods and algorithms for optimization of energy systems is available. • Optimization problems become more and more complex. • Development of effective and efficient algorithms for global optimization is still needed. • Synthesis optimization is challenging. • Introduction of reliability, maintenance and social aspects in optimization is needed. [ABSTRACT FROM AUTHOR]

Abstract Electricity generation expansion planning models determine the optimal technology-capacity-investment strategy that minimizes market costs including investment costs, and fixed and variable operating & maintenance costs over a long-term planning horizon. From a market cost perspective, fossil fuels are among the most economical sources of electricity, and thus are the primary sources of energy for electricity. However, these energy sources create by-products that have harmful health effects upon exposure. In this paper, a simulation-based, metamodeling approach is leveraged to quantify health damages associated with power grid expansion decisions by linking the outputs of generation expansion planning simulations with a screening tool that quantifies the human health damages from the electricity sector. Using this as a surrogate function for health damages, these costs are included in the objective function of a generation expansion planning model, in addition to market costs and the social damages of carbon emissions and methane leakage to minimize societal damages. Applying an improvement algorithm, candidate data points are selected to enhance metamodel prediction capability. Finally, using an updated metamodel, a new expansion plan is found. This framework enables researchers to better understand the health implications of long-term capacity expansion decisions. Highlights • A generation expansion planning model that minimizes societal costs is presented. • Simulation-based optimization is used to find a capacity expansion plan. • A case study for the Northeastern United States is presented. • The results are compared with various deterministic cases. [ABSTRACT FROM AUTHOR]

Abstract The research presented in this paper aims to assess the technical effectiveness of demand response as a demand-side flexibility option to mitigate variability in the energy system in Finland in 2030. The results show that heating loads can provide a significant long-term technical potential for demand-side resource capacity. This demand-side resource capacity is not always available, as it varies according to the season and time of the day. The temporal availability of demand-side resource capacities varies between 80 and 5600 MW. Furthermore, the results show that the utilisation of demand-side resource capacity decreases significantly when the shifting time interval becomes more constrained. The utilisation of demand-side resource capacity results in balancing of residual demand in the day-ahead market, and thus more efficient utilisation of wind power generation in the Finnish power market. This smoothing effect reduces operating hours of thermal power production and the need for cross-border balancing by electricity imports during the peak hours. According to the sensitivity analysis, the ramping occurrences of district heating CHP units increase significantly with increased share of inflexible baseload nuclear power, while some of the efficiency gains can leak to the neighbouring countries. Highlights • Demand response can be utilised in VRE integration. • Demand response can substitute peak production capacity. • Demand response can reduce the need for cross-border balancing. [ABSTRACT FROM AUTHOR]

Abstract Optimal control and design of energy systems in some instances require the fast exergoeconomic optimization. Fuzzy inference systems (FIS) were previously employed for either the computerized iterative exergoeconomic optimization or fast optimization of the energy system. The shortcoming of the FIS system was that the requirement to have numerous fuzzy rules and fuzzy membership function that must be collected based on experts' knowledge and usually with try and error steps. On the other hand, conventional optimization methods such as genetic algorithm consume significant calculation time that makes them unsuitable for the fast optimization. In this paper, the adaptive neuro-fuzzy interference system known as the ANFIS was introduced for fast exergoeconomic optimization of energy systems. The ANFIS system automatically developed the required fuzzy items and used them for fast optimization of energy systems. It was employed on two case studies, one for exergoeconomic design and optimization of a benchmark energy system known as the CGAM problem. It was shown that the ANFIS could achieve the optimal solutions of systems with reasonable accuracy, very low computation time, and without dependency on experts' knowledge to develop fuzzy data. The ANFIS was found as an optimistic alternative for the fast optimization of energy systems. Highlights • A methodology based on adaptive neuro-fuzzy inference system, ANFIS, is developed. • The developed ANFIS method is introduced for exergoeconomic optimization. • It was found that the ANFIS could be used for real-time optimization. • It has superior features over the conventional optimization and fuzzy methods. • It has no requirement for knowledge of experts to develop fuzzy data. [ABSTRACT FROM AUTHOR]

Abstract As the increasing penetration of wind and PV generations in island microgrids, the intermittent nature of renewable energy resources and randomness of load demands are inevitable, therefore, maintaining system stability and reliability has become a challenging issue for microgrid operators. In addition, energy storage unit and demand side management technology are widely utilized in the island microgrids to alleviate the passive impacts introduced by renewable energy resources. Nevertheless, they produce uncertainties as well. To accommodate the combined uncertainties, a two-stage robust model predictive control based optimization approach is proposed in this paper. The mixed integer quadratic programming model is established in the first operation stage to minimize the operation cost under the joint worst case of uncertainty, then an economic dispatch model is used to minimize the adjustment cost after obtaining actual data in the second operation stage. Robust linearization methods with the consideration of three types of uncertainty scenarios and uncertainty budgets are utilized in the first operation stage. Finally, the case study indicates that the proposed approach is more robust and economical than the conventional two-stage robust optimization approach, then the sensitivity of typical parameters and important units are analyzed and discussed. Highlights • A comprehensive isolated island microgrid energy management model is proposed. • A two-stage robust model predictive control optimization based microgrid operation model is proposed. • Three types of data uncertainty are considered in the robust optimization model. • Several sensitive analysis cases are implemented to evaluate the performance of the proposed model. [ABSTRACT FROM AUTHOR]

Abstract The Brazilian electricity system is an important example of a large country relying on a high renewable energy matrix with a major focus on hydropower, which has historically allowed for low carbon electricity production. However, the increase in the demand and climate change impacts on the availability of these renewable resources represent important challenges for long-term power planning. The contribution of this paper is twofold: Firstly, a first attempt to use the EnergyPLAN model for the analysis of the Brazilian electricity sector and in particular to study future scenarios is presented. Secondly, the possibility of achieving a 100% RES system is also addressed. The 100% RES scenario is found to be theoretically possible but a substantial increase in the overall installed capacity would be required, to support the grid mainly during the spring and summer season. The results underline the importance of seasonal complementarity of hydro and wind power and reveal how an increase in RES would add exportation potential, reducing also the Brazilian external energy dependency. The study identifies risk factors for these high RES scenarios and outlines several avenues for future research to address cost, environmental and technical uncertainties of the system. Highlights • The Brazilian power sector is analysed with EnergyPLAN computer model. • Renewable scenarios are compared for technical, cost, emissions and risk parameters. • The importance of seasonal complementarity of hydro and wind power is outlined. • The 100% RES scenario results in full decarbonization of the system at higher cost. • The 100% RES scenario results in higher exportation and lower importation potential. [ABSTRACT FROM AUTHOR]

Abstract District energy systems are a central element in transforming the energy system towards a low-carbon system. Simulation is regarded as key method for concept development and assessment as well as for operational optimization to address the growing complexity of these systems and to derive quantitative feedback e.g., as input for decision-support or operational processes. In this paper we present a comprehensive comparison of four widely used general-purpose modelling tools for district-scale energy systems, including a detailed discussion of modelling paradigms and co-simulation capabilities. This comparison is based on an extensive literature review, a comprehensive questionnaire that was conducted by tool and library developers, as well as a comparison of pipe model behavior of various libraries against measured data. The results including the experimental data are openly available and can support users in academia and industry with the selection of suitable modelling paradigms and associated tools and libraries. [ABSTRACT FROM AUTHOR]

Abstract This paper formulates an electricity market dominated by price-making hydro-thermal generation. Generation companies optimize their unit commitment, scheduling and bidding decisions simultaneously as a Mixed Integer Programming problem and participate in a market under quantity competition, giving rise to a discontinuous Nash-Cournot game. Both hydropower and thermal units are considered as price-makers. The market equilibrium under uncertainty is computed via time stage decomposition and nesting of a Continuous Nash game into the original Discontinuous Nash game that can be solved via a search algorithm. To highlight applicability of the proposed framework, a case study on the Scandinavian power market is designed and suggests positive welfare effects of large scale storage, whereas the implications on scheduling of conventional units are subsequently discussed. Reformulation allows computationally efficient scaling of the problem and possible extensions to allow large scale applications are discussed. Highlights • A stochastic game model for hydro-thermal power market with price-maker hydropower producers. • A computational method to locate all Nash equilibria for the proposed non-convex game model with integer variables. • A decomposition approach to cope with periodical inflows. [ABSTRACT FROM AUTHOR]

Abstract Several influential energy systems models (ESMs) indicate that renewable energy must supply a large share of the world's electricity to limit global temperature increases to 1.5 °C. To better represent the costs and other implications of such a transition, it is important that ESMs can realistically characterise the technical and economic potential of renewable energy resources. This paper presents a Geospatial Information System methodology for estimating the global offshore wind energy potential, i.e. the terawatt hour per year (TWh/yr) production potential of wind farms, assuming capacity could be built across the viable offshore area of each country. A bottom-up approach characterises the capacity factors of offshore wind farms by estimating the available wind power from high resolution global wind speed data sets. Temporal phenomena are retained by binning hourly wind speeds into 32 time slices per year considering the wind resource across several decades. For 157 countries with a viable offshore wind potential, electricity generation potential is produced in tranches according to the distance to grid connection, water depth and average annual capacity factor. These data can be used as inputs to ESMs and to assess the economically viable offshore wind energy potential, on a global or per-country basis. Highlights • Offshore wind energy potentials according to distance to the coast and water depth. • Generation potential is time-explicit to be used in energy system models. • Capacity potential depends on local capacity factors, water depth and available area. • 329,600 Terawatt hours per year of offshore wind energy is feasible, globally. [ABSTRACT FROM AUTHOR]

Abstract Compared with wind and solar power, biomass power has grown relatively slowly in China. With abundant biomass resources, the development of biomass electric power in China has potential advantages. This paper analyzed the environmental impact of biomass power in the construction and operation stages in comparison with wind and solar power. The results showed that biomass power produced relatively less emissions in the system construction stage at around 1700 ton CO 2 -e/MW. In the operation stage, biomass power projects achieved an average of 131462 ton CO 2 -e per year, which is greater than wind and solar power of equal installed capacity. Biomass power plants could achieve net emission reductions in a shorter time (0.39 year) after operation. The life cycle GHG emissions of biomass power projects are between 42 and 85 g CO 2 -e/kWh. The evidence pointed out that biomass power is worth supporting in China, from the perspective of environmental performance. Local governments should promote the sustainable supply of biomass materials and the development of renewable energy industry should depend on local conditions. Highlights • The unit emissions of biomass power from construction is around 1700 ton CO2-e/MW. • Biomass power projects achieved net emission reductions less than half year. • The life cycle GHG emission of biomass power projects are between 42 and 85 g CO2-e/kWh. [ABSTRACT FROM AUTHOR]

Abstract The transition to a 100% renewable energy system based on variable renewable energy raises technical but also institutional questions. The smart energy system concept integrates variable renewable energy by addressing the technical challenges through the integration of different energy sectors, but integration of variable renewable energy also entails a change in the cost structures, especially related to electricity. The effect of this change in cost structures on market prices is investigated. This is done through simulation of a 100% renewable energy system that utilises a large degree of cross-sector integration but maintaining the current electricity market structure. The paper uses a 100% renewable energy system scenario for a 2050 Danish energy system. This is reflected in the use of wind energy as the primary renewable energy source. It is concluded that the current electricity market structure is not able to financially sustain the amounts of wind power necessary for the transition to a 100% renewable energy system. Since earlier research shows that neither electricity production costs nor the total system costs is higher for the renewable path than the fossil-based alternatives, the conclusion in this paper points towards a need for reshaping the institutional structure of electricity trade. Highlights • Calculates electricity prices in a renewable energy system with current market design. • Calculates private profitability of wind power investments within such system. • The market design cannot financially sustain wind power in a renewable energy system. [ABSTRACT FROM AUTHOR]

Abstract Sustainable island energy systems have been a subject of academic research for some time. Real-life examples of highly renewable and sustainable island energy systems can be found all over the World. Islands on small geographic proximity provide the potential for the development of 100% renewable island energy systems by exploiting their grid interconnections. This paper proposes that interconnections of a group of islands can be used to integrate the production from locally available renewable energy sources. Besides interconnection, electric vehicles were used as a demand response technology to provide storage for electrical energy from variable sources. Electric vehicles were connected to the grid using smart charging systems (vehicle-to-grid). In addition, stationary batteries were explored in sub-scenarios for the year 2035. This enabled to analyse the influence of the battery location through two main different scenarios, i.e. one big central battery and several smaller distributed batteries. Scenarios with different integration dynamic of variable renewable energy sources and electrical vehicles were modelled with EnergyPLAN model, while the interconnection analysis was carried out with the MultiNode tool expansion. The results showed that the interconnections increased the share of energy from renewable energy sources in the final energy consumption and declined the total critical excess electricity production, while vehicle to grid technology enabled exploitation of synergies between sectors. Highlights • The energy system of grid connected islands is built with EnergyPLAN model. • Island models connected in the archipelago by using MultiNode tool. • Impact of RES integration with DR technologies and stationary batteries is observed. • No fossil fuel powered generators were used. • Influence of distribution of stationary batteries on energy flows is studied. [ABSTRACT FROM AUTHOR]

Abstract The imbalance between the distribution of coal resources and electricity demand makes the transport of energy a significant challenge for China’s electricity system. Moreover, with China’s air pollution control policies, more clean energy resources will be used to generate electricity, which will change regional power generation structures and influence the energy transport among regions. In this paper, a multi-regional model is developed to optimize the long-term generation and transmission structure of China’s electricity system by minimizing the accumulative system cost and considering regional resource endowments and air pollution control polices in four key areas. Results indicate that 1) the share of power generation from clean energy will increase from 24% in 2015 to 62% in 2050, 2) the structure of power generation in each region will be influenced by local water resource availability, and the total CO 2 emission will be reduced by around 16% in 2030 owing to the air pollution control policies, and 3) by 2050, coal will be mainly transported from the North to the Central, the South, the East and the Northeast, while the electricity will be transmitted to the Central, the South and the East from the Northwest, the North, the Southwest and the Central. Highlights • A multi-regional optimization model of China’s electricity system is developed. • The share of clean energy generation will increase from 24% in 2015 to 62% in 2050. • Resource endowment and environmental policy will affect regional energy structure. • The energy transport between regions are mapped from 2020 to 2050. [ABSTRACT FROM AUTHOR]

Abstract It is a frequent practice nowadays to use mean annual conversion factors (CF s) when performing life-cycle assessment (LCA) of processes and products that use electricity supplied by the grid. In this paper, we conduct an hourly assessment of the greenhouse gas (GHG) emission factor, along with the conversion factors for the cumulative energy demand (CED) and its non-renewable part (CEDnr), of electricity supplied by the Swiss grid and its direct neighboring countries (France, Germany, and Austria; Italy being neglected). Based on an hourly inventory of energy flows during a one-year period (2015–2016), this attributional approach allows performance of various certification procedures of process or product manufacturing, and comparison of energy and carbon intensities of different national mixes. Hourly calculation allows evaluation of the order of magnitude of errors made when considering an annual mix. Visualization techniques are used to better understand the obtained data and to detect when strategies involving timing optimization of electricity use may be efficient. A case study is chosen to illustrate the relevance of hourly CF s when performing LCA associated to the exploitation of a given building. Moreover, mean annual CF s of interest are discriminated by electricity end-use sectors. This could be of great help for system designers willing to improve the assessment accuracy when hourly CF s are not readily available. Highlights • Energy and carbon footprints of the Swiss mix are assessed hourly. • Surrounding national grids are also assessed with a lower accuracy. • Each national mix exhibits unique temporal features of energy use and GHG emissions. • The coefficient of variation is used to assess the relevance of hourly time step. • Assessment accuracy performed with hourly footprints depends on the grid mix. [ABSTRACT FROM AUTHOR]

The objective of this paper is to investigate the effect of simultaneous using of nanofluid and selective absorber on the improvement of work extraction by a solar flat-plate collector (FPC). Applying a precise model for the exergy factor of solar incident, it is found that the maximum power generation is higher and lower than that by the Petela-Landesberg-Press (PLP) and Carnot model, respectively. Results showed that the influence of temperature ratio ( a ) and geometry factor ( f ) on the exergy efficiency is not such significant when a FPC is working on the Earth's surface. It is also revealed that the key role of the ratio of the absorber plate's emittance to its absorptance must be given attention since only the values lower than 0.174 are allowed by the second law requirements. Furthermore, the exergy efficiency and energy efficiency would experience 10.5% and near 8% enhancement for a 7.5% increase in collector's optical efficiency. Boosting the exergy efficiency by almost 4.1% at 4% volume concentration, demonstrated that nanofluid exploitation instead of plain water would be capable of improving the power generation by the collector. [ABSTRACT FROM AUTHOR]

Due to increasing penetration of the renewable energy resources in modern power systems, the uncertain nature of these resources should be managed in real and near real-time scheduling. This paper investigates the benefits and applicability of look-ahead scheduling of integrated system including conventional generation units, wind power and compressed air energy storage (CAES). Different scenarios have been generated to model the uncertain parameters in the scheduling problem. To control and evaluate this stochastic process, the conditional value at risk (CVaR) framework has been implemented. Demand response programs have applied on the model to minimize the total cost and increase the flexibility requirement. This problem is formulated as mixed integer non-linear programming (MINLP) model with consideration of technical constraints of conventional generation, wind and CAES units. According to the numerical results, the operating profit could be maximized by the use of look-ahead approach and implementation of DR program. [ABSTRACT FROM AUTHOR]

An investigation of premixed H 2 /air combustion in a nozzle inlet micro tube has been carried out. The effects of inlet shape on combustion characteristics, flow field, specie distribution and thermal performance are presented and discussed. Also, effects of inlet mass flow rate and equivalence ratio on the entropy generations of combustion in the micro tubes are analyzed. The results show that the mean outer wall temperature and the emitter theoretical radiant efficiency of the nozzle inlet micro tube is higher than that of the straight micro tube. The total entropy generation rate of the nozzle inlet micro tube is lower than the straight micro tube. Moreover, the Inlet 2 and Inlet 3 nozzle inlet micro tube obtain a higher mean outer wall temperature and a lower exergy destruction, which are more appropriate for the application of the micro thermophotovoltaic (TPV) system. [ABSTRACT FROM AUTHOR]

Many wind farms in northern China have faced a worrying phenomenon “wind curtailment” during the heating seasons. The limited operating flexibility of combined heat and power (CHP) units is one of the major barriers to integrating wind energy. In this study, wind power integration is enhanced by using the free heat storage of the primary district heating network (DHN) and introducing extra heat pumps (HPs). A novel short-term dispatch model is proposed to minimize the total primary energy consumption (TPEC) of the district energy system (DES). After necessary linearization processes, the unit commitment problem can be solved efficiently and analytically by the interior point method. A test DES that contains a real large-scale DHN is utilized to verify the feasibility of the proposed dispatch model. In case studies, comparisons are made to evaluate the improvement of wind power integration and TPEC reduction under different operating scenarios. The results show that both heat storage utilization and electric HP introduction can reduce wind curtailment considerably, however, exhaust heat recycling has a better performance. In addition, using the existing heat storage of the primary DHN could reduce the TPEC of DES further even if electric HPs have already been used. [ABSTRACT FROM AUTHOR]

Combined cooling, heating and power(CCHP) system can meet the diversified demand of users. To investigate the performance of CCHP system based on advanced adiabatic compressed air energy storage(AA-CAES) under different operation strategies, four operation scenarios of compressor-expander, which are respectively constant-constant, constant-sliding, sliding-constant, and sliding-sliding, are proposed in this paper. By employing the numerical simulation method, system performance of four scenarios is compared via energy analysis and exergy analysis. Meanwhile, a parametric analysis is conducted to evaluate the influence of key parameters on system performance. The results show that cycle efficiency, thermal efficiency and exergy efficiency of sliding-sliding scenario are all the highest, 48.31%, 91.04% and 56.48%, respectively. And exergy density of constant-sliding scenario is the biggest, 7.69 × 10 6  J m −3 , when design parameters of system are the same. In addition, second heat exchanger makes the largest contribution to the overall exergy destruction of system. For the four operation scenarios, with heat exchanger effectiveness increasing, cycle efficiencies exist optimal values, whereas thermal efficiencies, exergy efficiencies and exergy densities gradually augment. The influence of ambient temperature on different performance indexes is different. The increase of ambient pressure has negative effect on exergy densities, but it has positive effect on other performance indexes. [ABSTRACT FROM AUTHOR]

Geothermal energy is a constant and independent form of renewable energy and plays a key role towards the world's future energy balance. In particular, deep geothermal resources are largely available across continents and can help countries become less dependent on energy imports and build a broader base in their future energy mix. However, despite its significant potential, the total contribution of the geothermal sector to global power generation remains relatively small. The International Energy Agency has recommended devising plans to address technology-specific challenges to achieve faster growth and improving policies tackling pre-development risks for geothermal energy. Reaching considerable depths is a requirement to exploit deep geothermal resources, but experience gained to date from the implementation of complex, engineered deep geothermal projects has unveiled technical and economic challenges, lower-than-expected performance and poor public image. There is therefore an urgent need for alternative, more sustainable well designs. This paper critically assesses conventional and unconventional deep geothermal well concepts, focusing on the basic Borehole Heat Exchanger (BHE) concept. The discussions are supported by numerical simulations of a BHE design that includes heat conductive fillers to enhance the heat exchange with the surrounding formation, while avoiding direct fluid interaction with the latter. [ABSTRACT FROM AUTHOR]

We discussed the influences of colloidal particles on ion transport in nanofluidic power generation system, which is an unavoidable issue for actual membrane-based power generation systems. By introducing negatively charged colloidal particles (∼100 nm) with different concentrations, power generation by reverse electrodialysis in a porous anodic alumina membrane was analyzed. The power was enhanced in a colloid concentration of ( 2.6 – 4.2 ) × 10 - 5 g / ml . The maximum power was acquired when the colloid ( ∼ 3.05 × 10 - 5 g / ml ) was on the same side as the salt solution (1 M KCl). Modifying the surface of the porous anodic alumina membrane by using an ultra-thin metal layer (10 nm of platinum) achieved almost the same maximum power, but the colloid concentration range of the power enhancement broadened. The electrokinetic interplay between colloidal particles and nanofluidics is complex. The appearance of colloidal particles in water bodies does not always result in a reduction in power generation, and their effects can be effectively regulated by engineering parameters. [ABSTRACT FROM AUTHOR]