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Abstract: Alarmingly low pulp prices in early 2009 left pulp and paper mills across North America desperate for any way to improve thin profit margins. One solution that continues to gain popularity among the industry is improved energy management systems for cogeneration systems, which use steam for two purposes – to provide heat for the pulping process and to generate electricity for sale to regional providers. This paper presents an energy optimization algorithm for use in a pulp and paper mill cogeneration system. The algorithm is applicable to a number of popular mill configurations, power sale contracts, and fuel purchasing scenarios. The method is also extended to address weather-dependent cooling limitations encountered by a mill cogeneration facility, in which case an iterative solution is proposed in order to maintain convexity of the optimization problem. Results are presented in the form of three case studies. [ABSTRACT FROM AUTHOR]

The collection of sawmill residues is an important logistic activity for the pulp and paper industry, which uses the biomass as a source of energy. We study a vehicle routing problem for a network composed of a single depot and several sawmills. The sawmills serve as potential suppliers of biomass residues to the depot, which in turn processes and distributes the residues to the pulp and paper mills. This problem consists of identifying the best daily routing schedule for a fixed number of trucks. The objective is to maximize the ratio of energy returned on energy invested, while satisfying a minimum daily amount of dried biomass residues. There are several random components in the problem, including the availability and moisture content of the biomass residues. We use a combination of scenario analysis and heuristics to solve this stochastic vehicle routing problem. A performance comparison of the proposed method reveals an estimated daily energy savings of 6 GJ over the benchmark method. [ABSTRACT FROM AUTHOR]

Electricity management systems are experiencing significant challenges due to the increased penetration of distributed energy resources. Electricity flows in distribution networks are transforming from unidirectional to bi-directional form. Consumers are transitioning to prosumers with different characteristics, where they take more active roles in electricity generation and consumption. Aggregators are vital financial intermediary agents in the power system transitions, as they could aggregate energy profiles of prosumers. The market competition between aggregators and interactions between prosumers and aggregators are complex and dynamic, which requires a holistic framework to model the market competition. This paper proposes an intelligent aggregation framework with edge computing, enabling decentralized competition for multiple aggregators and prosumers, which can be solved with a graph-based consensus algorithm. This study mathematically proves the proposed algorithm's convergence guarantee and convergence rate. In addition, the proposed framework is applied to an open-source dataset to demonstrate its applicability. Lastly, a benchmark analysis is conducted to show that the proposed algorithm has better communication complexity than the benchmark algorithms. • A dynamic market competition model for prosumer aggregation. • The solution state for the market to reach equilibrium is unique. • A graph-based algorithm for the market model with edge computing. • A proposed algorithm with a linear convergence rate. [ABSTRACT FROM AUTHOR]

Building integrated photovoltaic thermal (BIPV/T)-energy pile ground source heat pump (GSHP) system effectively maintains the soil thermal balance and improves the photovoltaic efficiency by recovering the waste solar heat from the BIPV/T collector to charge the ground. However, due to the strict carbon emission restriction and economic consideration for system application, multi-objective optimization should be implemented for the system design to further enhance its overall performance. Therefore, a complete optimization framework is proposed in this paper, which is based on the NSGA-II algorithm and functions by coupling TRNSYS and jEPlus+EA. Using the proposed optimization frame, a comprehensive optimization is conducted for the system, which optimizes five main design variables and adopts the total power consumption (TPC), life cycle climate performance (LCCP), and life cycle cost (LCC) to reflect the system's energetic, environmental, and economic performances. Seven optimization cases are included in the optimization project to identify design schemes that meet all possible proposed performance requirements for the system application. The optimized results show that the system optimization improves its performance greatly compared to the design condition, with a range of 38.03% ∼ 50.05% for the TPC, 24.52% ∼ 25.86% for LCCP, and 56.74% ∼ 61.66% for LCC. The energetic, environmental and economic performances of the system can be maximized by minimizing the TPC to 357.29 MWh in Case 1, LCCP to 596.15 tCO 2 in Case 2, and LCC to 17.03 × 104 CNY in Case 3. By breaking down the objective functions, it is found that the heat pump unit holds paramount importance in all aspects of system performance, and the BIPV/T collector proves advantageous in enhancing the system's long-term performance due to its massive electricity generation. Accordingly, one important finding is that it is advisable to incorporate as many BIPV/T collectors as feasible while maintaining soil heat balance. The optimal energy pile number varies among the seven optimization cases, resulting in different heating capacities for the heat pump unit. Research outcomes in this work offer references for designing the energy-pile GSHP system to enhance the penetration of renewable energy into buildings. • A multi-objective optimization is proposed for the PV/T coupled energy-pile system. • The optimal system design is crafted to meet all possible performance requirements. • The effect of different optimization objectives on system performance is explored. • The optimal energy pile number varies for different optimization objectives. • Integrating more BIPV/T collectors is better while maintaining soil heat balance. [ABSTRACT FROM AUTHOR]

• Graphical approach to assess matching between photovoltaic electricity and loads. • Combines the conventional measures self-sufficiency and self-consumption. • Possible to visualize improved matching with energy storage and load shifting. • Contribution of photovoltaic electricity for Swedish nearly zero energy buildings. For on-site renewable energy supply, such as photovoltaic (PV) electricity generation, an important issue is the daily and seasonal matching between on-site supply and demand. The matching potential is frequently expressed using the load matching indicators such as self-sufficiency and self-consumption. This paper presents the Energy matching chart, which is a novel graphical approach to visualize the PV-load matching. The chart uses self-sufficiency and self-consumption to provide information regarding the matching in both size and time. Using the Energy matching chart, the matching between PV production and load presented in previous studies is graphically analyzed and compared. Furthermore, the potentials for the two most common measures for improving the matching, namely energy storage and load shifting, are investigated. The results show that energy storage has, on average, a significantly higher potential for increasing the PV-load matching than load shifting. The second part of the paper, illustrates the benefits of the Energy matching chart by evaluating the Swedish implementation of the EU legislation on nearly Zero Energy Buildings (nZEBs). The assessment is performed for detached houses and evaluates the feasibility to use PV and battery systems for Swedish nZEBs. The results show that on-site PV production can help buildings to meet the nZEB regulations, but there are limitations due to the poor time-dependent matching. With a combined PV-battery system, the potential to meet the regulation is significantly larger. To summarize, the Energy matching chart has the potential to become a useful tool in the assessment of PV system and the evaluation of load matching measures. [ABSTRACT FROM AUTHOR]

Highlights • We analyze the economic value of participating in multi-stage electricity markets. • The party submitting bids is a wind power producer with generic energy storage system. • The market analyzed as a case analysis has eight sub-markets. We condensate them into one. • We consider uncertainty in power production and prices. We propose a common modeling basis. • We analyze a number of scenarios comprising power and price differences. Abstract This paper provides a methodology to compute the optimal bidding by a wind power producer in a multi-stage market. The methodology is not restricted to the two-stage markets often reported in the literature—a day-ahead bid submission followed by an adjustment in the imbalance market. Instead, it allows studying any number of markets operating on the same dispatch hour. Particularly, this paper analyzes part of the Spanish market, covering the day-ahead, the six intraday, and the imbalance market. They are markets with different schedules, but this paper shows that by simply rearranging the market prices into a single equivalent market and employing the increments of power as bids, the calculations are visibly simplified; despite the different scope and gate closures. The methodology also includes a dynamic programming approach that relies on the equivalent market data to provide an optimal bidding sequence and its economic value when (i) uncertain prices and wind power production are considered, and (ii) energy storage is employed. As an application, the proposed methodology is employed to analyze the revenues derived by a wind power producer using ESS in the Spanish market. [ABSTRACT FROM AUTHOR]

Highlights • Environmental control is enormously costly for the U.S. military, especially in remote locations. • Environmental control units (ECUs) are currently powered by generators and are unmanaged. • We propose an optimization-based approach to coordinate multiple ECUs and generators. • By operating generators at higher loads, we achieve significant fuel savings (28% for the configuration considered). Abstract This paper examines efficiencies achieved by optimal scheduling of power generation equipment and electrical loads in a hybrid smart micro-grid under conditions where load activity may be delayed or advanced with negligible impact to system performance. We model military expeditionary energy systems to analyze the performance of existing unmanaged components and estimate potential savings obtained by coordinated management of battlefield heating and cooling systems. We employ rolling horizon optimization models to examine performance under varying degrees of uncertainty about future load demand and renewable production. We propose a novel mechanism to reduce power production costs through optimal prescriptive scheduling of loads, reducing peak demand and generator peak-to-average power ratios and facilitating a persistent shift to higher fuel efficiencies. In contrast to existing methods that employ either supply-side or demand-side management, we propose intelligently coordinating both sides to achieve greater efficiency. Using sensitivity analysis, this paper quantitatively demonstrates how grid composition, temperature band tolerance, and energy storage capabilities contribute to fuel efficiency under this approach. [ABSTRACT FROM AUTHOR]

Highlights • This paper presents enhanced modeling of gas network within planning models. • Solves the gas-electricity planning problem appling Dantzig-Wolfe decomposition. • Presents a scalable planning problem under long-term uncertainties. • Highlights the importance of multi-stage-stochastic gas-electricity planning problem. Abstract Planning networks within a multi-stage stochastic framework is becoming critical for improving the economic performance of investment decisions against the present levels of uncertainty. This problem, however, has been proved extremely challenging to be solved on real networks, especially when considering the interactions among various energy vectors. In this context, this paper proposes the use of Dantzig-Wolfe decomposition and parallel asynchronous column generation to solve a multi-stage stochastic planning of an integrated power and natural gas system, including non-linear effects of gas compressors reformulated in a mixed integer linear programming fashion. We compare the computational performance of the proposed approach against two alternatives: a parallel synchronous column generation approach and the counterfactual, monolithic approach, where the mixed integer linear program (without decomposition) is directly solved by a commercial solver. Our sources of long-term uncertainty are the locations and volumes of (i) new renewable generation (which may depend on policy objectives, regulatory incentives, etc. that are constantly evolving) and (ii) new demands. The model also ensures that the planned energy infrastructure can effectively be operated reliably against a large array of operating conditions originated by high variability of renewable generation outputs, multiple demand levels and hydro inflows. Through various case studies, we discuss and demonstrate the importance of stochastic and integrated planning of electricity and natural gas systems along with the benefits of asynchronous algorithms and decomposition techniques that can be parallelized. [ABSTRACT FROM AUTHOR]

Although hydrogen is increasingly seen as a crucial energy carrier in future zero-carbon energy system, a profitable exploitation of electrolysers requires still high amounts of subsidies. To analyze the profitability of electrolysers, attention has to be paid not only to the costs, but also to the interaction between electricity and hydrogen markets. Using a model of internationally integrated electricity and hydrogen markets, this paper analyses the profitability of electrolysers plants in various future market circumstances. We find that in particular the future supply of renewable electricity, the demand for electricity as well as the prices of natural gas and carbon strongly affect the profitability of electrolysis. In order to make massive investments in electrolysers profitable with significantly lower subsidy requirements, the amount of renewable electricity generation needs to grow strongly and the carbon prices should be higher, while the demand for electricity should not increase accordingly. This research underscores the critical role of market conditions in shaping the viability of hydrogen electrolysis, providing valuable insights for policymakers and stakeholders in the transition to a zero-carbon energy system. • Hydrogen's importance grows, but electrolysers need substantial subsidies. • Model of electricity and hydrogen markets is used to assess profitability. • Driving factors are renewable electricity, electricity demand, gas and carbon prices. • More renewables and higher carbon prices are required for profitable electrolysers. [ABSTRACT FROM AUTHOR]

The increasing adoption of electric vehicles driven by government plans to strongly electrify mobility will challenge the current distribution grid infrastructure. The related electricity demand increases the risk of overloads and will require significant grid enhancements and infrastructural investments. Our paper evaluates the potential of reducing investment needs through decentralized photovoltaic electricity generation and battery energy storage systems. We use power-flow analyses on representative grid models to test rural, urban, and suburban grids' resilience to higher electric vehicle penetration. We find significant societal benefits with a simultaneous uptake of decentralized generation and estimate savings of up to €3.2 billion solely within the German grid. In rural areas, photovoltaic and battery systems are especially effective for electric vehicle penetrations up to 20%, reducing grid costs by up to 39%. Suburban and urban grids could achieve significant savings for electric vehicle penetrations up to 60%, with cost-saving potentials of up to 51% and 46%, respectively. We recommend that policymakers facilitate decentralized electricity generation to unlock additional benefits from a societal cost perspective, increase the share of sustainable electricity consumption, and improve energy security. [Display omitted] • Estimation of savings potential in EV-related grid cost via PV and battery systems. • Residential generation and storage can significantly reduce grid investments. • Infrastructure cost savings could amount to almost €3.2 billion within the German grid. [ABSTRACT FROM AUTHOR]

• Electricity, the most direct and effective use of RES, is in center of energy transition. • An interdisciplinary procedure suitable for the planning of RES is presented. • Key points and procedures for the assessment of large-scale RES installation is presented. • Simulation on Eygiption case shows the technical and economical viability. Due to the environmental impacts brought by current energy schemes, the energy transition, a new paradigm shift from fossil fuels to renewable energy, has been widely accepted and is being realized through collective international, regional, and local efforts. Electricity, as the most direct and effective use of renewable energy sources (RES), plays a key role in the energy transition. In this paper, we first discuss a viable pathway to energy transition through the electricity triangle, highlighting the role of RES in electricity generation. Further, we propose methodologies for the planning of wind and solar PV, as well as how to address their uncertainty in generation expansion problems. Finally, by using a web-based tool, "RES-PLAT" 1 1 https://res-plat.est.polito.it. , we demonstrate the scheme in a case study in Egypt, which evaluates the impacts and benefits of a large-scale RES expansion. 2 2 The short version of the paper was presented at Applied Energy Symposium: MIT A+ B, August 13–14, Boston. This paper is a substantial extension of the short version of the conference paper. [ABSTRACT FROM AUTHOR]

Transitioning electricity generation sectors to renewable energy is a necessary element of climate change mitigation but a challenging one with years of technical and social lock-in creating considerable inertia and a pace of change insufficient to meet the task. Transition management has emerged as a promising approach to proactively manage and accelerate transitions in sectors like energy and water and has the potential to do so in manner that would help secure energy justice. However, the approach has been criticised for ignoring the political dynamics of transitions, risking procedural and recognition injustice for traditional energy production regions while increasing opposition to a transition. This paper uses a qualitative case study approach to understand how a transition to renewable energy generation could be achieved in a way that secures energy justice for traditional energy production regions like those of Gladstone in the Australian state of Queensland. The paper augments the transition management approach with the “just transitions” concept, which has emerged from labour movements as a means to mitigate negative impacts on workers and communities in traditional energy production regions, to create a “Just Transition Management” framework that is applied as a diagnostic tool to the case study. While results suggest a transition is imminent within Queensland, a lack of: consistent, supportive federal policy; long-term visions, and a clear process leaves it at risk of being captured by the powerful incumbent resources sector utilising an “environment vs. jobs” narrative. Yet, the results also suggest that adopting a just transition management approach has the potential to successfully resist the influence of the resources sector, by providing cheap, secure renewable energy and supporting affected workers into roles in the renewable energy sector using a reflexive, representative network governance approach. Data analysis reveals how the application of just transition principles has already engaged communities and unions that were previously sceptical of renewable energy. Overall, this study suggests that the just transition management framework assists in identifying the political barriers to transitions and energy justice more broadly, while also providing a management approach which creates powerful niche actor-networks to counter the narratives and influence of the incumbent resource sector. Thus it could support successful transitions that achieve the distributional, recognition and procedural justice needed for energy justice globally. [ABSTRACT FROM AUTHOR]

Past studies of hybrid power cycles using multiple heat sources of different temperatures focused mainly on case studies and almost no general theory about this type of systems was developed. This paper is a first comprehensive study of their general thermodynamic performance, with their comparison to their corresponding single temperature heat source reference system, focusing on three types of power cycles: simple Rankine cycle, Rankine cycle with reheat and Rankine cycle with heat regeneration. The generalized expressions for the energy and exergy efficiency differences between the hybrid and the corresponding single heat source system were developed. A number of simulation case studies were performed to help the understanding and confirm the thermodynamic generalization of the results. The results show that the energy and exergy efficiencies of the hybrid systems are higher than those of their corresponding single heat source reference systems if and only if the energy andexergy conversion efficiency (defined in the paper) of the additional heat source (AHS) is larger than that of the original heat source. The conditions that defined the effects of the AHS temperature and heat addition rate on the energy and exergy efficiencies of the hybrid systems as convex or concave curves were described. Comparisons across the first two types of hybrid power cycles were made, showing that the energy and exergy efficiencies of the reheat Rankine cycle is generally higher than that of the simple Rankine cycle as AHS is changed. Recommendations were made for obtaining the maximal energy and exergy efficiency as a function of the AHS temperature, of the heat addition rate by the AHS, and of the AHS position in the power cycle flow sheet. For the hybrid power generation systems with heat regeneration it was found that when using an AHS to raise the net system power by a given amount, using it to replace the higher-pressure extracted steam will result in a higher system energy efficiency than when using it to replace lower-pressure extracted steam. Hybrid cycles can have significantly lower emissions, cost, and fuel depletion. [ABSTRACT FROM AUTHOR]

In recent times, there has been a significant increase in intermittent renewable electricity capacity additions to the generation mix. This, coupled with an aging electrical grid that is poorly equipped to handle the ensuing mismatch between generation and use, has created a strong need for flexible, advanced bulk energy storage technologies. In this paper, one such technology recently invented and demonstrated at Oak Ridge National Laboratory is introduced and characterized. Similar to compressed-air energy storage, the Ground-Level Integrated Diverse Energy Storage (GLIDES) technology is based on gas compression/expansion, however, liquid-piston compression and expansion are utilized. In common with pumped-storage hydroelectricity, hydraulic turbomachines (pump/turbine) are utilized for energy storage and recovery, however, pressure vessels are utilized to create artificial elevation (head) difference, allowing pressure head of several thousands of feet to be reached. This paper reports on the experimental performance of the first GLIDES proof-of-concept prototype, and presents formulation and results from a validated physics-based simulation model. [ABSTRACT FROM AUTHOR]

Along with the technical feasibility of microgrids, the importance of supervisory communications, computing, and control (CCC) systems that are necessary to operate a microgrid in a stable and economically feasible manner have been firmly established in the literature. While several investigators have proposed and demonstrated algorithms and applications of CCC, the functional entities and responsibility centers for realizing CCC within microgrids in the context of multiple independent customers and distribution system entities have not been situated and/or studied. In this context, the term emergent microgrid may be used to define an electrical network that consists of local generation, loads, and storage. Such a grid has the potential to be clustered as a microgrid, but does not have all the CCC features to become a full-fledged microgrid. In this paper, a simple electric utility platform (SEUP) that is an end-to-end solution with all the hardware/software interfaces and components necessary for augmenting emergent microgrids with CCC into full-fledged microgrids is presented. SEUP abstracts the details of sensing and CCC for the microgrid developers, installers, operators and end-users to provide a seamless system. SEUP is distinctive from other CCC platforms in that it is entirely based on publicly available infrastructure resources (wireless cellular networks, internet and cloud computing) without any intellectual property restrictions. The paper introduces the functional roles, main architecture, components and security features of SEUP along with the results from a sample application case of a laboratory-scale power system. [ABSTRACT FROM AUTHOR]

Based on real options theory, this paper builds a model for analysing Chinese NG (Natural gas) power generation costs, cost reduced due to the substitution of original thermal power generation with NG power generation and the carbon value in this process. This study presents a mathematical representation of the cost savings of NG. It is the first model to introduce market linkage mechanism in order to discuss the problems with the analyses of the costs of China’s NG power generation. On the basis of considering many uncertain factors, this article attempts to unravel the market linkage effect based on the model analyses with and without the consideration of market linkage mechanism, as well as the impact analyses of the cost-savings in NG power generation project. From the perspective of power generation businesses, the paper model and analyse cost reduced brought by the substitution of original thermal power generation with NG power generation and the carbon value. Government subsidies and carbon values are added to the simulation section. The article provides the change curves of NG power generation, thermal power generation and carbon prices under random paths through path simulation and compares multiple uncertain factors under a single path. Five scenarios are proposed with different assumptions and the results indicate that the market linkage of nature gas price can help to decrease the cost of nature gas-fired power generation. Furthermore, it addresses the scenario of obtaining government subsidies to reduce the cost of NG power generation when carbon value exists. The conclusions of the study will help power companies assess the value of natural gas power generation projects and help them decide whether to invest in the project. [ABSTRACT FROM AUTHOR]

The electrification of the transportation sector poses an opportunity for reducing greenhouse gas (GHG) emissions from passenger vehicles. Electric vehicle (EV) charging through dynamic wireless power transfer (DWPT), known as roadway electrification, could shift EV demand profiles to better coincide with renewable electricity generation. However, this would be a very large new load and few studies evaluate the regional impacts of DWPT charging in a power transmission system. This paper defines methods that address dataset generation for passenger vehicle trips and models to evaluate regional impacts for this emerging technology. Household vehicle miles traveled (VMT) data form localized EV demand profiles through discrete-event simulation. This data serves as exogenous inputs for a Production Cost Model (PCM) of a synthetic transmission system based on the Electric Reliability Council of Texas's (ERCOT) network. EV charging methods are compared for both a 2018 baseline generation mixture and a high-renewable generation case incorporating 20 GW of installed solar photovoltaic (PV) capacity. The PCM employs unit commitment and economic dispatch (UC&ED) models to compare financial, environmental, and grid reliability impacts from EV charging across passenger EV adoption levels. In-transit charging could reduce grid operational costs by as much as 1.49%, with up to $13.7B saved in annual vehicle operational costs for consumers compared to gas-powered vehicles. Health impacts analysis from power plant and vehicle tailpipe emissions from this study show net health benefits increase by 40% for in-transit charging coupled with high renewable generation. Renewable resources provide an avenue for cost-effective in-transit charging with reduced emissions. The combination of dataset generation and open-source power system modeling establish a foundation for the holistic evaluation of regional DWPT impacts. • PEV dynamic charging with increased renewable generation has positive system impacts. • Public data informs vehicle-miles traveled datasets for energy consumption analysis. • In-transit wireless charging from PEVs decreases power system peak demand hours. • In-transit PEV charging aligns with solar power to reduce curtailment and total cost. • Net health benefits from PEVs improve with in-transit charging and renewable sources. [ABSTRACT FROM AUTHOR]

This paper delves into an econometric analysis to uncover the differences between Nordic European Countries - NEC (Norway, Denmark, Finland, Sweden) and South-East European Countries - SEEC (Greece, Bulgaria, Romania, Hungary). The focus is on exploring the interplay among electricity generation from Renewable Energy Sources (RES), CO 2 emissions, urban population and GDP per capita in these two European regions. The study employs cross-sectional dependence, first and second-generation panel unit root tests, Pedroni panel and Westerlund panel cointegration tests, ARDL, Dumitrescu-Hurlin causality test to establish the relation among variables. The findings reveal that in both regions, CO 2 emissions are significantly influenced by GDP per capita, urbanization and RES generation. Furthermore, urbanization plays an important role. When examining causality in SEEC, three bidirectional relationships are observed: urbanization and CO 2 , urbanization and GDP, urbanization and generation from RES, and two unidirectional causalities: CO 2 and GDP, generation from RES and CO 2. In contrast, for the NEC, there are two bidirectional causalities: urbanization and CO 2 , urbanization and generation from RES, and two unidirectional causalities: GDP and CO 2 , generation from RES and CO 2. These results highlight the nuanced and varied nature of environmental and economic dynamics across various European regions. • Relationship between CO 2 emissions, GDP per capita and electricity production from RES. • Investigating two groups of EU countries located in the North and SE Europe. • Estimations with Fully Modified and Dynamic Ordinary Least Squares. • Causality and cointegration between variables. [ABSTRACT FROM AUTHOR]

• Shadow pricing is a popular method for abatement cost estimation. • Most previous studies ignore the materials balance condition. • Materials balance consistent Convex Nonparametric Least Squares estimator developed. • Shadow prices for 160 US power producers from stochastic and deterministic models. • Abatement costs severely understated when the materials balance is ignored. Marginal abatement cost is an essential input to optimal environmental policies. Shadow pricing has become a popular method for estimating abatement costs subject to parsimonious data requirement. This paper provides a novel contribution to the literature on shadow pricing by considering the implication of the materials balance principle for shadow prices. To that end, the paper establishes a Convex Nonparametric Least Squares estimator for the weak G-disposable production model, which for the first time enables modeling a composite error term and joint estimation of the production frontier and contextual variables within this production model framework. Applying the Directional Distance Function, environmental efficiencies and shadow prices for carbon dioxide emissions are estimated for a sample of power producers using both stochastic and deterministic frontier models. Average shadow price estimates for carbon dioxide range between 14,000 and 40,000 $/ton CO 2 for the weak G-disposable model and between 70 and 77 $/ton CO 2 for the conventional production model that ignores the materials balance. These findings cast doubt on previous shadow price estimates since a majority of comparable studies ignore the strict technical relationship among pollution-generating inputs and bad outputs under the materials balance condition. [ABSTRACT FROM AUTHOR]

The high penetration of renewable energy sources and the consequent integration of such distributed energy generation systems into the grid have significantly increased the interaction between power sources, which can result in low frequency oscillations. Different control techniques are proposed in literature to suppress low frequency oscillations, but the first step to attenuate such oscillations is to characterize them in terms of their dominant modes. This paper combines different results from literature to propose a unified two-step methodology for the mode characterization of low frequency oscillations based on the signals acquired by wide area measurement systems. Since the measured signals typically contain noise, the first stage of the proposed method uses the basis pursuit denoising method combined with a Tunable Q-factor wavelet transform to increase the signal-to-noise ratio and improve the identification results. In a second stage, an improved version of the matrix pencil algorithm, as proposed in this paper, is used to identify the parameters of low frequency oscillation dominant modes. Both simulation and experimental results show that the proposed method has better characterization accuracy than traditional methods, especially when Gaussian noise is considered in the measurements. In addition, the processing time has proven to be reasonable for online identification and characterization of low frequency oscillations. [ABSTRACT FROM AUTHOR]

The process industry in general is very energy-intensive, and therefore models focusing on energy can be very important in order to reach higher profitability. In this study, an optimization model of the supply chain in a pulp company, where energy is included with respect to its revenue generating capabilities, is used. Using real company data, and through an analysis of the model’s results, we show that higher profitability can be achieved when integrating energy into the planning process. Our findings show that when energy-intensive raw materials not only provide fibre to the pulp process but also generate an energy surplus, there is room for different planning approaches in order to maximize the total profit. This paper reveals promising changes that can be made for improving the current planning process. The scenarios considered involve market changes for energy demand and price, and also alternative production opportunities. A cross-analysis compares the scenarios in order to reveal additional relations that are important to consider. Depending on a price change of energy, the model prioritizes in its selection of pulp products to produce. From this we provide guidelines on where and when to increase or decrease pulp production. The model shows that the company can increase its total profit no matter which of the included energy parameters that increase in price. The paper contributes to previous research by enhancing the usefulness of this model for not only the case company as such, but also by illustrating and describing how the approach applied can be useful for other cases within the energy intensive industry. [ABSTRACT FROM AUTHOR]

Globally, a considerable amount of energy is consumed by the building sector. The building envelope can highly influence the energy consumption in buildings. In this regard, innovative technologies such as thermal energy storage (TES) can help to boost the energy efficiency and to reduce the CO 2 emissions in this sector. The use of phase change materials (PCM), due to its high heat capacity, has been the centre of attention of many researchers. A considerable number of papers have been published on the application of PCM as passive system in building envelopes. Researches have shown that choosing the PCM melting temperature in different climate conditions is a key factor to improve the energy performance in buildings. In the present paper, a simulation-based optimization methodology will be presented by coupling EnergyPlus and GenOpt with an innovative enthalpy-temperature (h-T) function to define the optimum PCM peak melting temperature to enhance the cooling, heating, and the annual total heating and cooling energy performance of a residential building in various climate conditions based on Köppen-Geiger classification. Results show that in a cooling dominant climate the best PCM melting temperature to reduce the annual energy consumption is close to the maximum of 26 °C (melting range of 24–28 °C), whereas in heating dominant climates PCM with lower melting temperature of 20 °C (melting range of 18–22 °C) yields higher annual energy benefits. Moreover, it was found that the proper selection of PCM melting temperature in each climate zone can lead to notable energy savings for cooling energy consumption, heating energy consumption, and total annual energy consumption. [ABSTRACT FROM AUTHOR]

This paper proposes that not only the size and component of carbon footprints are relevant to environmental policies but the border-crossing frequency associated with carbon footprints also has important policy implications, especially given that the fragmentation of production across national boundaries has been developing quickly in recent years. Based on the World Input Output Database, this paper traces carbon transfer along cross-border supply chains and proposes both the upstream and downstream decomposition of export rebates of the United States and the European Union. The carbon transfer from the United States and the European Union to other countries or regions is mainly through international trade in intermediate products, which may cross national borders multiple times. The multiple rebate revenue reaches 422.14 million dollars, and the problem of multiple rebates is much more serious for the sectors with a greater degree of global production fragmentation, such as the electrical and optical equipment sector. In addition, export rebates are mainly targeted at the carbon emissions that are generated in the electricity generation sector and embodied in exports. [ABSTRACT FROM AUTHOR]

In this paper, life cycle assessment (LCA) of waste to energy (WtE) treatment plants for electricity generation in twelve selected cities of Nigeria is studied with the aim of evaluating their electricity generation potential, global warming potential (GWP), acidification potential (AP) and dioxin/furan emission potential. The WtE plants are: landfill gas to energy (LFGTE), hybrid of incineration and anaerobic digestion (INC/AD) and hybrid of incineration and landfill gas to energy (INC/LFGTE). The benefits of the WtE plants are thereafter compared to the landfilling (waste management without intention of energy recovery) in each of the locations in order to determine the option that best fit the locations in an environmentally sustainable manner. To achieve this, the waste profile of each of the locations is determined using per capita waste generation and the population data obtained from national population commission (NPC). Some of the key results reveal that the hybrid of INC/AD is potentially viable compared to other methods in terms of GWP and ecosystem potential measured by AP. However, LFGTE technology is the best in terms of carcinogenic reduction potential measured by dioxin/furan emissions. The hybrid of INC/AD has the potential of reducing GWP in the range of 75.7–93.3% compared to land filling without energy recovery. Similarly, hybrid of INC/LFGTE provided a reduction in the range of 75.3–84.8% while LFGTE could reduce the GWP by 75%. This paper could serve as a source of scientific information for decision making on environmental sustainability in waste-to-energy projects in Nigeria. [ABSTRACT FROM AUTHOR]

Demand-side management (DSM) has the potential to reduce electricity costs and the carbon emissions associated with electricity use for industrial consumers. It also has an important role to play in integrating variable forms of generation, such as wind and solar, into the grid. This will be a key part of any grid decarbonisation strategy. This paper describes a method that can be used to develop a new production schedule for a wide range of manufacturing facilities. The new schedule minimises either electricity costs or electricity-derived CO 2 emissions. It does so by rescheduling production to low cost or low carbon periods, without loss of overall production, within the constraints of available inventory storage. A case study of a single cement plant in the UK was performed in order to determine the potential benefits of increased load-shifting DSM using this method. The alternative production scheduled showed the potential to decrease electricity costs by 4.2%. Scaled to values from a typical plant this would lead to a cost saving of £350,000, a substantial saving. A schedule optimised to minimise carbon emissions would save an estimated 2000 tonnes per year of CO 2 , a 4% decrease in electricity-derived emissions. It was also observed that the actual electricity consumption of the plant was considerably higher than the minimum consumption predicted by the model. This could indicate potential for significant savings in both cost and CO 2 due to improvements in energy efficiency. The potential savings from DSM doubled when the prices passed to the plant were replaced with a price that varied in proportion to the wholesale cost of electricity. This indicates that a potential mutual benefit exists for both industrial consumers and electricity generators by passing on more of the variation in price. A larger share of generation from wind and solar will also lead to increased variation in prices and grid carbon intensity in future. The value of applying the method described in this paper is therefore likely to increase further in future. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to explore applications of blockchain technology related to the 4th Industrial Revolution (Industry 4.0) and to present an example where blockchain is employed to facilitate machine-to-machine (M2M) interactions and establish a M2M electricity market in the context of the chemical industry. The presented scenario includes two electricity producers and one electricity consumer trading with each other over a blockchain. All participants are supplied with realistic data produced by process flow sheet models. This work contributes a proof-of-concept implementation of the scenario. Additionally, this paper describes and discusses the research and application landscape of blockchain technology in relation to the Industry 4.0. It concludes that this technology has significant under-researched potential to support and enhance the efficiency gains of the revolution and identifies areas for future research. [ABSTRACT FROM AUTHOR]

The current increase in the deployment of new renewable electricity generation systems is creating new challenges in balancing electric grids. Solutions including energy storage at small and large scales are becoming of paramount importance to guarantee and secure a stable supply of electricity. This paper presents a study about a hybrid solution including a large scale energy storage system coupled with power generation and fast responding energy storage systems. The hybrid plant is able to deliver the energy previously stored by using an air liquefaction process either with or without the contribution of additional energy from combustion. The paper also highlights how such hybrid plants may offer the chance of providing the grid with fast control services. An ideal energy storage technology should have a high power rating, a large storage capacity, high efficiency, low costs and no geographic constraints. The use of air as energy carrier has been studied since the 20th century with the first compressed air energy storage (CAES) systems. This technology is still considered to have a potential but it is geographically constrained, where suitable geological reservoirs are available, unless compressed air is stored in pressurized tanks with significant costs. Liquid Air Energy Storage (LAES) represents an interesting solution due to its relatively large volumetric energy density and ease of storage. Different process schemes for hybrid plants were modeled in this study with Aspen HYSYS® simulation software and the results were compared in terms of equivalent round-trip and fuel efficiencies. Equivalent round-trip efficiencies, higher than 80%, have been calculated showing that the proposed configurations might play an important role for power systems balancing in the near future. [ABSTRACT FROM AUTHOR]

Market based pricing of CO 2 was designed to control CO 2 emissions by means of the price level, since high CO 2 price levels discourage emissions. In this paper, it will be shown that the level of uncertainty on CO 2 market prices, i.e. the volatility of CO 2 prices itself, has a strong influence not only on generation portfolio risk management but also on CO 2 emissions abatement. A reduction of emissions can be obtained when rational power generation capacity investors decide that the capacity expansion cost risk induced jointly by CO 2 volatility and fossil fuels prices volatility can be efficiently hedged adding to otherwise fossil fuel portfolios some nuclear power as a carbon free asset. This intriguing effect will be discussed using a recently introduced economic analysis tool, called stochastic LCOE theory. The stochastic LCOE theory used here was designed to investigate diversification effects on energy portfolios. In previous papers this theory was used to study diversification effects on portfolios composed of carbon risky fossil technologies and a carbon risk-free nuclear technology in a risk-reward trade-off frame. In this paper the stochastic LCOE theory will be extended to include uncertainty about nuclear power plant construction times, i.e. considering nuclear risky as well, this being the main uncertainty source of financial risk in nuclear technology. Two measures of risk will be used, standard deviation and CVaR deviation, to derive efficient frontiers for generation portfolios. Frontier portfolios will be analyzed in their implications on emissions control. [ABSTRACT FROM AUTHOR]

CO 2 -based transcritical Rankine cycle (CTRC) can be used for the waste heat recovery due to its safety and environment-friendly characteristics, and also fits for the high temperature of exhaust gas and satisfy the miniaturization demand of recovery systems. It can provide a reasonable pathway toward thermal energy management of engine. This work proposes novel configurations selection maps of four CTRC configurations for waste heat recovery of engines. Except for considering a regenerator added to traditional CTRC (basic CTRC) recovering exhaust waste heat, a preheater driven by engine coolant will be also taken into account in this paper. Thus, the four configurations include the basic CTRC (B-CTRC), the CTRC with a preheater (P-CTRC), the CTRC with a regenerator (R-CTRC) and the CTRC with both of the preheater and the regenerator (PR-CTRC). As different CTRC configurations have advantage of performance indicators under different conditions, and the focused indicators may also be various with applications, this paper focuses on proposing a kind of selection maps, which is used for the selection of the four CTRC configurations in the field of engine waste heat recovery. Comprehensive performance comparison are researched in this paper from three aspects, net power output based on the first law of thermodynamics, exergy efficiency based on the second law of thermodynamics and electricity production cost ( EPC ) as an indicator of the economic performance. After the comparative analysis, three selection maps separately based on the three performance indicators are proposed to give the selection reference of the CTRC configurations under different design conditions, which refer to turbine inlet pressure and temperature in this paper. It is meaningful for the design and operating of the CTRC configuration used for waste heat recovery of engines. Besides, it can also be a new method that can be expanded to other recovery system selection (e.g. ORCs) in engine field or other fields (e.g. solar, geothermal). [ABSTRACT FROM AUTHOR]

Metals are energy-dense fuels that can react exothermically with water to produce hydrogen, and this hydrogen is useful as a propellant for rockets and underwater vehicles or as a fuel for engines and fuel cells. Propulsion systems usually rely on high-temperature combustion ( T > 3000 K) of metal-water propellants, while hydrogen-production systems typically employ low reactor temperatures ( T < 100 °C). This paper reviews the current state of knowledge of both low-temperature and high-temperature metal-water reactions. Low-temperature reactions allow only the chemical energy contained in the hydrogen to be used, with the thermal energy released during the metal-water reaction being wasted. Metal-water propulsion systems typically make use of only the thermal energy of the metal-water reaction, with the hydrogen being exhausted to produce thrust. This paper proposes several novel applications of high-temperature metal-water combustion that allow the full chemical energy within the metal fuel to be harnessed, including high-speed air-breathing engines and high-power, compact, low-emissions power-generation systems. These technologies promise improved performance by maximizing the conversion of the chemical energy, stored within the metal fuel, into useful work at sufficient rates for high-power applications. [ABSTRACT FROM AUTHOR]

Solar Thermal Electric (STE) plants can integrate Thermal Energy Storage (TES) in order to generate electricity when the energy source (Sun radiation) has vanished. TES technology has become a very important asset for this type of renewable energy source, but it has induced a rise in electricity cost in many cases. One of the reasons is the need of larger solar fields as the TES capacity increases because the solar field has to provide thermal power both to generate electricity and to charge the storage. The economic effects of improving the plant performance seem to have some internal complexities that must be investigated covering the internal relations among the main parts of a STE plant: the solar field, the power block and the energy storage. This paper presents an analytical study of these relations aimed at deriving a better understanding of the cost/performance behavior of STE plants. As the power block is a mature and commercial technology with well-established efficiencies and specific costs (in $/W, for instance), it has been taken as the reference element in modelling the plant. The other parts of the plant, i.e., the solar field and the energy storage, have been characterized in cost and energy management by a set of high-level parameters. Of course, a coarse definition cannot give very accurate results for a specific design, but it can be the guideline for the selection and sizing of a plant. It is worth noting that each type of solar thermal power plant has a different parametric scenario, corresponding to its essential design window. In this paper, comparisons among plants with different parametric scenarios are restricted to one-axis concentration solar fields, where the coarse model is easily characterized. The results show that the optimum plant configuration, in terms of TES capacity and solar field size, depends on the solar field and TES costs relative to power block cost. Moreover, it is shown that some parametric scenarios always lead to an increase in the cost of electricity when the energy storage capacity is enlarged. On the contrary, parametric scenarios associated to cheaper solar fields yield a much better economic result when TES is embodied in the plant. Additionally, TES efficiency is also identified as a parameter with high impact in the performance of the whole system. This result seems obvious, but the model gives numerical values that can help to optimize the selection process in a project. For instance, it is assessed that the lower the TES efficiency, the greater the relevance of reducing solar field costs is in order to obtain low electricity generation costs. As a general conclusion, the model points out that Fresnel-type solar fields are much better suited than parabolic trough collectors for integrating thermal energy storage. This implies that Fresnel plants present a higher potential to cover the peaks of electricity demand, which results into bigger profits. [ABSTRACT FROM AUTHOR]

• The proposed model presents an integrated modelling framework in day-ahead and real-time markets. • The solution method compromises two-stage optimization processes for the optimization horizons. • The impact of traffic in routes is modelled in the multi-stage multi-level optimization process. • The sectionalizing process of the distribution system is modelled. This paper presents an integrated framework for the optimal resilient scheduling of an active distribution system in the day-ahead and real-time markets considering aggregators, parking lots, distributed energy resources, and Plug-in Hybrid Electric Vehicles (PHEVs) interactions. The main contribution of this paper is that the impacts of traffic patterns on the available dispatchable active power of PHEVs in day-ahead and real-time markets are explored. A two stage framework is considered. Each stage consists of a four-level optimization procedure that optimizes the scheduling problems of PHEVs, parking lots and distributed energy resources, aggregators, and active distribution system. The distribution system procures ramp-up and ramp-down services for the upward electricity market in a real-time horizon. The active distribution system can utilize a switching procedure to sectionalize its system into a multi-microgrid system to mitigate the impacts of external shocks. The model was assessed by the 123-bus test system. The proposed algorithm reduced the interruption and operating costs of the 123-bus test system by about 94.56% for the worst-case external shock. Further, the traffic pattern decreased the available ramp-up and ramp-down of parking lots by about 58.61% concerning the no-traffic case. [ABSTRACT FROM AUTHOR]

Transformation of the energy sector’s power generation mix is needed to contain global mean temperature rise to no more than 2 °C above the pre-industrial level. Because the power sector is also a dominant direct and indirect consumer of water, it is vital to understand current and likely future trends in power sector water consumption. In this paper, we use an input-output based hybrid approach to study the direct and indirect impacts on water consumption from power mix adjustment in the world’s seven largest emitting economies under multiple cost-effective mitigation pathways toward the 2 °C target. Although different pathways exist, we discovered generally increases in water consumption of power sector under the long-term 2 °C target compared with no-climate-policy pathways, especially for China and India. Fulfilling the Intended National Determined Contributions (INDCs) could decouple direct water consumption and electricity output for most regions but may result in increases of indirect water consumption in China. This paper suggests that in the light of geographically uneven water scarcity, more comprehensive evaluation of both the direct and indirect water demands of the power sector is demanded when considering climate policies relevant to significant structural and technological adjustments in power sector. [ABSTRACT FROM AUTHOR]

Hydrogen is called to play a vital role in the decarbonization of the energy sector. Its importance is notable for industries, where it finds multiple applications, but also for electricity generation through fuel-cells. Due to the existence of mature conversion technologies, the electricity‑hydrogen nexus is expected to be frequently present in the future for multiple applications. In this sense, it is very important to develop computational tools that consider both energy vectors and their links. Following this idea, this paper develops a local electricity‑hydrogen market model for industrial parks. The new model is suitable for systems with a notable presence of hydrogen consumers and on-site hydrogen generation through water electrolysis. The proposed market framework is capable to jointly reveal local electricity and hydrogen prices without ignoring the strong physical and financial interactions between systems. The mathematical notation arises from Stackelberg-based models for the electricity and hydrogen pricing sub-problems, which are solved iteratively until reaching convergence, thus resulting in a holistic optimization framework solvable by average machines. A case study is presented with results, which serve to validate the new tool as well as analyse several important aspects such as the role of fuel-cells or local renewable generation. Moreover, the results obtained allows us to show how both sub-systems are capable to cooperate seeking the collective welfare, thus augmenting the possibilities and flexibility of the whole system. • A novel local electricity model for industrial parks is developed. • The different agents involved are properly modelled. • Electricity and hydrogen prices can be calculated. • Electricity and hydrogen systems can cooperate seeking collective welfare. • The presence of photovoltaics or fuel-cells may notably impact on results. [ABSTRACT FROM AUTHOR]

Several studies have shown that the revenue of wind power generators on spot markets (“market value”) diminishes with increasing deployment. This “value drop” is mostly observed in power markets that are dominated by thermal power plants, such as in Germany. This paper assesses the wind market value in power systems where hydroelectric stations with large reservoirs prevail, such as in Sweden. Due to their dispatch flexibility, such hydropower compensates for wind power output variability and thereby mitigates the wind power value drop. The market value of electricity from wind declines with penetration in both types of power systems, but it tends to decline at a slower rate if hydropower is present. This paper presents empirical evidence on the relevance of this effect derived from market data and numerical model results. Our results indicate that when moving from 0% to 30% wind penetration, hydropower mitigates the value drop by a third. As a result, 1 MWh of wind energy is worth 18% more in Sweden than in Germany. Sensitivity analyses indicate high robustness despite large parameter uncertainty: in 80% of all sensitivities, wind energy is valuable 12–29% more in Sweden than in Germany. The benefits of hydropower seem to level off at around 20% wind penetration. This suggests that the hydro flexibility is “exhausted” at this level. Low wind speed wind turbines, carbon pricing, and upgrades of hydropower generation capacity can lever the added value of hydro flexibility further. Not only is wind energy more valuable in the presence of hydropower, hydroelectricity also becomes more valuable if paired with wind power. [ABSTRACT FROM AUTHOR]

Calculating carbon dioxide ( CO 2 ) emissions associated with electricity is a key component in the field of Life Cycle Assessment (LCA), but is often cited as challenging due to the complex nature of electricity systems despite its importance to the outcome. While calculating the operational CO 2 emissions associated with electricity generation is an active research field, the embodied CO 2 emissions, typically referred to as embodied carbon, of network assets has far less representation in the literature. This paper focuses on the CO 2 emissions aspect of LCA to calculate the embodied CO 2 of network assets in relation to the operational grid CO 2 over time. Several functional units are defined: CO 2 per operational year, CO 2 per asset cost, CO 2 per functional unit of electricity (kW h) and the relationship between embodied emissions and operational emissions in an electricity system over time. Hybrid functional units are then applied in order to better attribute the embodied carbon to the network functions. The hybrid functional units involve network asset lifetime and the issue of temporal horizons. Several suitable horizons are suggested and the comparison of results highlight the importance of the timeframe on results. The relationship between temporal horizons and environmental discounting is discussed and recommendations are made on the appropriate level of discounting depending on the temporal horizon and the purpose of the LCA. The paper uses data from the Great Britain electricity system where planned investment in network assets is £12bn at distribution level (Dx) and £16.4bn at transmission level (Tx) over the next eight years. By using GB network data for embodied carbon, demand and asset data, as well as data from the decarbonisation of electricity generation, indicative results are provided into the way in which embodied carbon impacts could change over time, showing that by 2035, the embodied carbon of the transmission network could contribute almost 25% of total emissions associated with electricity. On a regional basis, DNO level network assets could reach anywhere between 40% and 130%. This network data is also used to show that new network investment could account for up to 6.5% of DNO level network embodied carbon when front loaded during the RIIO-ED1 period. [ABSTRACT FROM AUTHOR]

Due to the increasing generation capacity of intermittent renewable electricity sources and an electrical grid ill-equipped to handle the mismatch between electricity generation and use, the need for advanced energy storage technologies will continue to grow. Currently, pumped-storage hydroelectricity and compressed air energy storage are used for grid-scale energy storage, and batteries are used at smaller scales. However, prospects for expansion of these technologies suffer from geographic limitations (pumped-storage hydroelectricity and compressed air energy storage), low roundtrip efficiency (compressed air energy storage), and high cost (batteries). Furthermore, pumped-storage hydroelectricity and compressed air energy storage are challenging to scale-down, while batteries are challenging to scale-up. In 2015, a novel compressed gas energy storage prototype system was developed at Oak Ridge National Laboratory. In this paper, a near-isothermal modification to the system is proposed. In common with compressed air energy storage, the novel storage technology described in this paper is based on air compression/expansion. However, several novel features lead to near-isothermal processes, higher efficiency, greater system scalability, and the ability to site a system anywhere. The enabling features are utilization of hydraulic machines for expansion/compression, above-ground pressure vessels as the storage medium, spray cooling/heating, and waste-heat utilization. The base configuration of the novel storage system was introduced in a previous paper. This paper describes the results obtained from a transient, analytical, physics-based thermodynamic system model used for the system design and evaluation of three design configurations (including base configuration). The system model captures real gas effects and all loss mechanisms. The model demonstrates an energy storage roundtrip efficiency of 82% and energy density of 3.59 MJ/m 3 . Experimental evaluation of system performance and detailed cost-analysis will be presented in future publications. [ABSTRACT FROM AUTHOR]

This paper presents a generic Mixed Integer Linear Programming (MILP) model that integrates a Mid-term Energy Planning (MEP) model, which implements generation and transmission system planning at a yearly level, with a Unit Commitment (UC) model, which performs the simulation of the Day-Ahead Electricity Market. The applicability of the proposed model is illustrated in a case study of the Greek interconnected power system. The aim is to evaluate a critical project in the Ten Year Network Development Plan (TYNDP) of the Independent Power Transmission System Operator S.A. (ADMIE), namely the electric interconnection of the Crete Island with the mainland electric system. The proposed modeling framework identifies the implementation (or not) of the interconnection of the Crete Island with the mainland electric system, as well as the optimum interconnection capacity. It also quantifies the effects on the Day-Ahead electricity market and on the energy mix. The paper demonstrates that the model can provide useful insights into the strategic and challenging decisions to be determined by investors and/or policy makers at a national and/or regional level, by providing the optimal energy roadmap and management, as well as clear price signals on critical energy projects under real operating and design constraints. [ABSTRACT FROM AUTHOR]

The increasing share of uncertain wind generation has changed traditional operation scheduling of power systems. The challenges of this additional variability raise the need for an operational flexibility in providing both energy and reserve. One key solution is an effective incorporation of plug-in electric vehicles (PEVs) into the power system operation process. To this end, this paper proposes a two-stage stochastic programming market-clearing model considering the network constraints to achieve the optimal scheduling of conventional units as well as PEV parking lots (PLs) in providing both energy and reserve services. Different from existing works, the paper pays more attention to the uncertain characterization of PLs takes into account the arrival/departure time of PEVs to/from the PL, the initial state of charge (SOC) of PEVs, and their battery capacity through a set of scenarios in addition to wind generation scenarios. The results reveal that although the cost saving as a consequence of incorporating PL to the grid is below 1% of total system cost, however, flexible interactions of PL in the energy and reserve markets can promote the integration of wind power more than 13.5%. [ABSTRACT FROM AUTHOR]

Prognostics applications on PEMFC are developing these last years. Indeed, taking decision to extend the lifetime of a PEMFC stack based on behavior and remaining useful life predictions is seen as a promising solution to tackle the too short life’s issue of PEMFCs. However, the development of prognostics shows some lacks in the literature. Indeed, performing prognostics requires health indicators that reflect the state of health of stack, while being able to interpret them in an industrial context. It is also important to propose criteria to set its end of life. Moreover, to trust any prognostics’ application, one should be able to evaluate the performance of its algorithms with respect to standards. To help launching a discussion on these subjects among scientific and industrial actors, this paper addresses some of the issues encountered when performing prognostics of a PEMFC stack. After showing the link between prognostics and decision, this paper proposes guidelines to set the limits of a prognostics approach. The definitions of healthy and degraded modes are discussed as well as how to choose the time instant to perform predictions. Then, three criteria based on the power produced by the stack are proposed as indicators of the state of health of the stack. The definition of the end of life of the stack is also discussed before proposing some criteria to assess the performance of any prognostics algorithm on a PEMFC. Some perspectives of works are also discussed before concluding. [ABSTRACT FROM AUTHOR]

This paper presents an innovative methodology to perform market analysis of a new solar power generation technology based on parabolic dish and micro gas turbine engines. Technical, economic, social and political parameters of influence are combined together into a single figure of merit: index of market potential . This index is an original approach enabling the identification of the potential markets for this technology, tackling the inverse problem (from technology to market identification) in lieu of the usual direct problem (determining the interest of a technology in a predefined region). The paper takes into account the availability of solar energy, population distribution, intensity of the electricity consumption, economic indicators, business environment and legal framework for a set of more than twenty countries. Risk assessment tools at various levels are also built into the numerical tool, which is not the case in similar works reviewed by the authors. Finally, the methodology includes a probabilistic approach to handling uncertainty in the input data. The result of this confirms that the methodology is robust and is not very affected by changes in the initial assumptions. [ABSTRACT FROM AUTHOR]

This paper aims at assessing the value of load shifting and demand side flexibility for improving electric grid system operations. In particular, this study investigates to what extent residential heat pumps participating in load shifting can contribute to reducing operational costs and CO 2 emissions associated with electric power generation and how home owners with heat pump systems can be best motivated to achieve these flexibility benefits. Residential heat pumps, when intelligently orchestrated in their operation, can lower operational costs and CO 2 emissions by performing load shifting in order to reduce curtailment of electricity from renewable energy sources and improve the efficiency of dispatchable power plants. In order to study the interaction, both the electricity generation system and residences with heat pumps are modeled. In a first step, an integrated modeling approach is presented which represents the idealized case where the electrical grid operation in terms of unit commitment and dispatch is concurrently optimized with that of a large number of residential heat pumps located in homes designed to low-energy design standards. While this joint optimization approach does not lend itself for real-time implementation, it serves as an upper bound for the achievable operational cost savings. The main focus of this paper is to assess to what extent load shifting incentives are able to achieve the aforementioned savings potential. Two types of incentives are studied: direct load control and dynamic time-of-use pricing. Since both the electricity generation supply system and the residential building stock with heat pumps had been modeled for the joint optimization, the performance of both load shifting incentives can be compared by separately assessing the supply and demand side. Superior performance is noted for the direct-load control scenario, achieving 60–90% of the cost savings attained in the jointly optimized best-case scenario. In dynamic time-of-use pricing, poor performance in terms of reduced cost and emissions is noted when the heat pumps response is not taken into account. When the heat pumps response is taken into account, dynamic time-of-use pricing performs better. However, both dynamic time-of-use pricing schemes show inferior performance at high levels of residential heat pump penetration. [ABSTRACT FROM AUTHOR]

Waste heat recovery and utilization represents a missed opportunity to reduce China’s total energy use, decrease carbon dioxide emissions, and improve air quality. Currently, China does not have a standardized or transparent methodology to quantify the waste heat potential in the industrial sector, which accounts for more than two thirds of China’s primary energy consumption. This paper presents the results of thermal energy modeling to quantify the technical maximum waste heat potential in three energy-intensive industrial sectors: cement, iron and steel, and glass. In addition, this paper identifies the practical potential for producing electricity from waste heat in these sectors. The analysis finds that the glass sector has the highest waste heat to power generation potential per unit of production basis among the studied sectors. This paper provides key principles for managing waste heat in the industrial sector and key sector characteristics for implementing waste heat to power generation technologies. [ABSTRACT FROM AUTHOR]

Demand Response (DR) as an option for electric utility peak load management has gained significant attention in the recent past as it helps to avoid stress conditions and possibly defer or avoid construction of new power generation, transmission and distribution infrastructures. DR in commercial buildings can play a major role in reducing peak load and mitigate network overloading conditions. Small and medium-sized commercial buildings have not historically played much role as a DR resource both due to lack of hardware and software tools and awareness. This paper presents a peak load reduction computing tool for commercial building DR applications. The proposed tool provides optimal control of building’s cooling set points with the aim to reduce building’s peak load, while maintaining occupant comfort measured by the Predicted Mean Vote (PMV) index. This is unlike other studies which use global cooling set point adjustment resulting in an uneven distribution of occupant satisfaction across the building. The approach is validated by experimentation conducted on a simulated medium-sized office building, which reflects an existing commercial building in Virginia, USA. Research findings indicate that the proposed methodology can effectively reduce the simulated building’s peak load and energy consumption during a DR event, while maintaining occupant comfort requirements. The paper also addresses the issue of rebound peaks following a DR event, and offers a means to help avoid this situation. [ABSTRACT FROM AUTHOR]

This paper describes the investigation of a hybrid power production system from biomass and solar energy. This paper suggests integration through heat exchanger network as a useful approach to obtain the synergy between biomass and solar. Biomass is first gasified in a bubbling fluidized bed (BFB) gasifier, and then syngas is used in a gas turbine. Excess heat exists in this sub-system and concentrated solar thermal process (CSTP) while there is a demand of steam for generating gasifying agent. Steam Rankine cycle exploits the heat created by these thermal streams to generate power while satisfying the steam demands. Thermodynamic performance was analyzed by process modelling with a semi-kinetic model of BFB gasifier and pinch analyses. The composition and temperature of gasifying agent showed some effect on the overall efficiency of the system. Higher overall efficiency of the system was achieved at higher temperature and higher O 2 fraction in the O 2 -steam mixture as gasifying agent. The increase in thermal input from CSTP had positive effect on overall efficiency of the hybrid system until thermal input from CSTP becomes dominant against thermal stream related to the gasifier and the gas turbine. [ABSTRACT FROM AUTHOR]

As the share of integrated renewable energy sources (RES) increases, traditional operation principles of the power systems need to change in order to maintain reliable and secure service provision, on one hand, and minimal cost and environmentally friendly electricity generation on the other. The challenge of alleviating additional uncertainty and variability brought by new sources to the system operation is seen as defining both flexibility capacities and flexibility requirements through provision of multiple services. In this context the role of emerging technologies, such as electric vehicles (EV) and energy storage (ES), is recognized through their active participation in providing both energy and reserve service. This paper elaborates on the benefits of active EV participation in multiple system services through various charging strategies. The presented mixed integer linear programming (MILP) unit commitment problem (UC) considers the capability of EV to provide primary, secondary and tertiary reserve as well as energy, however the focus is put on the benefits of EV providing spinning reserve services. The results clearly show benefits of multiple EV role to that of providing energy only. In addition the paper analyses multiple power systems, with regards to their energy mix, and recognizes how integration of EVs reflects on power system flexibility through metrics expressed as operational cost, environmental benefits and reduced wind curtailment. [ABSTRACT FROM AUTHOR]

For two variants of a supercritical coal-fired combined heat and power plant a thermodynamic, economic and risk analyses were carried out. The first variant consists of a unit working without realization of CO 2 capture process. The second one is the unit integrated with a chemical absorption CO 2 capture installation. In this variant the heat required for the desorption process is supplied with steam extracted from the steam turbine. The developed model of the CHP plant allowed to obtain main operation characteristics for annual change of load. For the two analyzed variants the characteristics of the amount of produced electricity (gross and net), generated heat and consumed chemical energy of fuel, as a function of the cogeneration unit operation time per year, were determined. In the next stage of calculations these characteristics were required to carry out the economic and risk analysis. Economic performances were evaluated in terms of the break-even price of electricity. The performed analysis proves that both investment projects will achieve the same economic effect, i.e. 85.26 €/MW h, if the price of emissions allowances reaches the value of 47.88 €/MgCO 2 . In this case, the potentially better variant of the system may be indicated based on the result of the risk analysis. In order to perform the risk analysis the main technical and economic risk factors concerning implementation of this technology were identified. The risk analysis was conducted with the use of Monte Carlo method. Based on the determined cumulative probability curves of obtaining specified values of the break-even price of electricity, it was possible to obtain values for defined in the paper indices of the investment risk assessment. The results of risk analysis are presented and discussed in the paper. [ABSTRACT FROM AUTHOR]

The interest in self-consumption of PV electricity from grid-connected residential systems is increasing among PV system owners and in the scientific community. Self-consumption can be defined as the share of the total PV production directly consumed by the PV system owner. With decreased subsidies for PV electricity in several countries, increased self-consumption could raise the profit of PV systems and lower the stress on the electricity distribution grid. This review paper summarizes existing research on PV self-consumption and options to improve it. Two options for increased self-consumption are included, namely energy storage and load management, also called demand side management (DSM). Most of the papers examine PV-battery systems, sometimes combined with DSM. The results show that it is possible to increase the relative self-consumption by 13–24% points with a battery storage capacity of 0.5–1 kW h per installed kW PV power and between 2% and 15% points with DSM, both compared to the original rate of self-consumption. The total number of papers is however rather limited and further research and more comparative studies are needed to give a comprehensive view of the technologies and their potential. Behavioral responses to PV self-consumption and the impact on the distribution grid also need to be further studied. [ABSTRACT FROM AUTHOR]

This paper presents the design, construction and tests of a traveling-wave thermoacoustic electric generator. A two-stage traveling-wave thermoacoustic engine converts thermal energy to acoustic power. Two low-impedance linear alternators (i.e., audio loudspeakers) were installed to extract and convert the engine’s acoustic power to electricity. The coupling mechanism between the thermoacoustic engine and alternators has been systematically studied numerically and experimentally, hence the optimal locations for installing the linear alternators were identified to maximize the electric power output and/or the thermal-to-electric conversion efficiency. A ball valve was used in the loop to partly correct the acoustic field that was altered by manufacturing errors. A prototype was built based on this new concept, which used pressurized helium at 1.8 MPa as the working gas and operated at a frequency of about 171 Hz. In the experiment, a maximum electric power of 204 W when the hot end temperature of the two regenerators reaches 512 °C and 452 °C, respectively. A maximum thermal-to-electric efficiency of 3.43% was achieved when the hot end temperature of the two regenerators reaches 597 °C and 511 °C, respectively. The research results presented in this paper demonstrate that multi-stage traveling-wave thermoacoustic electricity generator has a great potential for developing inexpensive electric generators. [ABSTRACT FROM AUTHOR]

Electrical power generation is changing dramatically across the world because of the need to reduce greenhouse gas emissions and to introduce mixed energy sources. The power network faces great challenges in transmission and distribution to meet demand with unpredictable daily and seasonal variations. Electrical Energy Storage (EES) is recognized as underpinning technologies to have great potential in meeting these challenges, whereby energy is stored in a certain state, according to the technology used, and is converted to electrical energy when needed. However, the wide variety of options and complex characteristic matrices make it difficult to appraise a specific EES technology for a particular application. This paper intends to mitigate this problem by providing a comprehensive and clear picture of the state-of-the-art technologies available, and where they would be suited for integration into a power generation and distribution system. The paper starts with an overview of the operation principles, technical and economic performance features and the current research and development of important EES technologies, sorted into six main categories based on the types of energy stored. Following this, a comprehensive comparison and an application potential analysis of the reviewed technologies are presented. [ABSTRACT FROM AUTHOR]