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In this framework, experimental tests on different battery technologies, BMS and cooling systems are extremely important to extend the battery life and BEV performance (Sehil et al. [[13]]). Electrical machines and magnetic components, high-voltage voltage power converters, and battery storage systems are some basic bricks to build an effective and efficient energy conversion environment. Electrical Machines and Power Converters The electrical power conversion from renewable energy sources plays a crucial role in the development of a sustainable society. Finally, the fil rouge of every contribution in this section is oriented to investigate the power converters, electrical machines, magnetic components, and battery storage systems in actual energy conversion applications for renewable energy sources integration by a modelling approach. [Extracted from the article]

• Photovoltaic (PV) generation curtailment is characterized for a three-phase unbalanced grid. • Uncertainty on PV generation and electric vehicles addressed in the Monte Carlo framework. • New indicators of avoided PV energy curtailment and peak power reduction effectiveness. • New EV smart charging strategy based on fuzzy logic and blockchain. • Results are shown on a three-phase unbalanced distribution system. The increased diffusion of Photovoltaic (PV) generation could be limited by the grid capacity to host the power input from PV systems, especially in mid-day hours on sunny days. This paper proposes a framework of analysis to determine the mitigation of the PV energy curtailment in the grid, based on a novel smart charging strategy for electric vehicles (EVs) that operate in the grid-to-vehicle mode. This framework adopts a combination of methods and techniques, with a clustering procedure to group the EV charging stations with some PV systems based on the electrical distance, a novel smart charging strategy for the EVs based on the definition of fuzzy weights, and the exploitation of the blockchain technology with a Proof-of-Authority consensus protocol to reinforce network security and achieve decentralization. The blockchain provides full traceability of EV charging operations and grid status monitoring during time. The proposed framework contains novel indicators of avoided PV power reduction and energy curtailment. To account for the EV-related uncertainty, these indicators are determined from a Monte Carlo-based assessment of the three-phase power flow results. The results are presented on a three-phase unbalanced 123-node system with given locations of PV systems and EV charging stations. [ABSTRACT FROM AUTHOR]

The solutions recommended by international roadmaps and technical reports on smart metering refer to interval metering with time resolutions higher than 15 min to 1 h as traditionally used. Based on the characteristics of the users’ power patterns in distribution networks, this article shows that in practical cases the resolutions of the traditional metering are not sufficient to assess peak power and network losses effectively. Effective interval metering solutions should have resolutions of one minute or less. Moreover, this article shows the advantages of assessing the average power peak (amplitude and duration) and estimating the network losses through innovative solutions beyond interval metering, based on event-driven energy metering. The use of EDM significantly enhances the quality of pattern representation and reduces the amount of data required with respect to high-resolution interval metering. Based on the Pareto analysis of conflicting objectives, a novel procedure to set up the EDM thresholds is presented. The applications shown use real data and refer to a single user, some users connected to a distribution network feeder, and many users connected to a large distribution system. The EDM benefits are quantified using specific indicators that consider energy losses and peak power. [ABSTRACT FROM AUTHOR]

Abstract This paper addresses the potential multi-energy arbitrage opportunities for distributed multi-energy systems that arise from shifting the supply across input energy vectors and across plant components. This allows flexible decrease/increase of the electricity input from the grid to provide power system ancillary services, while maintaining the end-use energy demand at a constant level and thus without affecting the consumers' comfort. The benefits of the distributed multi-energy system participation in providing ancillary services for the reserve market are assessed by means of specifically defined multi-energy profitability maps. A novel indicator is introduced to quantify the electricity reduction that corresponds to the maximum profit of the distributed multi-energy system during the provision of the ancillary service. Numerical results that show the effectiveness of the proposed approach and the profitability map usage for a trigeneration system are discussed on two selected illustrative cases. From these cases, it is possible to identify the variety of conditions leading to the maximum profitability of the ancillary service provision in function of the economic parameters (availability fee and exercise fee) and of the amount of input electricity reduction. The most significant result is that, depending on the availability and exercise fees, the maximum profit may be obtained in some cases for an input electricity reduction lower than the maximum reduction that may be provided as the technical limit. This happens especially in the summer period, when the higher cooling demand and the presence of alternative solutions to provide cooling energy give more possibilities to perform energy shifting. Highlights • Distributed multi-energy systems provide multi-energy arbitrage opportunities. • The multi-energy arbitrage framework for ancillary services provision is presented. • Multi-energy profitability maps are introduced to assess profits and break-even conditions. • A novel indicator quantifies the input electricity reduction at maximum profit. • The proposed energy shifting strategy does not affect the consumers' comfort. [ABSTRACT FROM AUTHOR]

The development of multigeneration systems is evolving in different directions. One of the main directions is the extended application of the technologies at smaller sizes. Micro-multigeneration solutions aim at becoming competitive at the size of the residential users. The cost of the technologies, in particular the cost of the cogenerator, is a major limitation to the diffusion of micro-multigeneration, especially in countries (e.g., Italy) where residential customers have a limited usage of electricity to supply their facilities. This paper discusses the prospects for the application of micro-multigeneration in Italy. The modelling and analysis of a residential micro-multigeneration system are developed from the energy efficiency and economic assessment viewpoints. The analysis is carried out on a typical system composed of a natural gas internal combustion engine, a small-scale photovoltaic plant, a backup boiler, thermal energy storage and electrical energy storage. A specific analysis tool has been implemented to address the operational planning of this system during a time period of one year. The whole model has been constructed from real data of thermal and electrical demand in a housing complex in Italy. The annual running cost and the primary energy savings occurring to serve the multi-energy demand have been considered in the operational assessment. From an economical viewpoint, the model considers the price of natural gas related to the cogeneration system, the electricity prices and all the tax breaks allowed in Italy. In this way, different scenarios have been constructed and assessed. The results indicate the impact of providing incentives on the purchase cost of the technologies, leading to increase the diffusion of micro-multigeneration solutions for the residential sector in the next years. [ABSTRACT FROM AUTHOR]

Recent developments in smart metering applications have led to the conceptualization and construction of a new type of energy meter, operating on the basis of event-driven principles. The event-driven metering concepts are applied to represent the information on the electrical load patterns, which have an integral value. This paper explains why these concepts are different from the ones used for event-based applications in other domains, discusses the principles used in the new type of electricity meter, presents the data formats structured in such a way to provide detailed knowledge representation, and shows a number of results on real-case applications. A specific index is defined in order to represent the effectiveness of the event-driven metering scheme illustrated to represent the details of the metered pattern, comparing the results with the ones that could be reached in the most favorable case through regular timer-driven metering. The presentation of specific applications based on real-life datasets highlights the advantages of the event-driven energy metering over the traditional timer-driven metering scheme. [ABSTRACT FROM AUTHOR]

This paper deals with the identification of balance, unbalance and distortion components in unbalanced three-phase systems with distorted waveforms containing harmonics and interharmonics. The analysis starts from the harmonic distortion and unbalance components found through the symmetrical component-based (SCB) approach previously defined by the authors. The SCB approach is extended in this paper by introducing an auxiliary reference frequency and identifying its consistency condition with respect to the fundamental system frequency. After defining the auxiliary reference frequency, the proposed approach directly uses the classical symmetrical component transformation matrix at any harmonic or interharmonic. Various results are presented, for conventional test cases and for measurements gathered from real systems with variable unbalanced and distorted loads. These results show that the extended SCB approach is particularly useful to analyze three-phase systems in unbalanced and distorted conditions with harmonics and interharmonics, because of its simplicity and intuitiveness compared to other approaches. [ABSTRACT FROM AUTHOR]

Availability of effective estimation of the power profiles of photovoltaic systems is essential for studying how to increase the share of intermittent renewable sources in the electricity mix of many countries. For this purpose, weather forecasts, together with historical data of the meteorological quantities, provide fundamental information. The weak point of the forecasts depends on variable sky conditions, when the clouds successively cover and uncover the solar disc. This causes remarkable positive and negative variations in the irradiance pattern measured at the photovoltaic (PV) site location. This paper starts from 1 to 3 days-ahead solar irradiance forecasts available during one year, with a few points for each day. These forecasts are interpolated to obtain more irradiance estimations per day. The estimated irradiance data are used to classify the sky conditions into clear, variable or cloudy. The results are compared with the outcomes of the same classification carried out with the irradiance measured in meteorological stations at two real PV sites. The occurrence of irradiance spikes in "broken cloud" conditions is identified and discussed. From the measured irradiance, the Alternating Current (AC) power injected into the grid at two PV sites is estimated by using a PV energy conversion model. The AC power errors resulting from the PV model with respect to on-site AC power measurements are shown and discussed. [ABSTRACT FROM AUTHOR]

The recent trends toward enhancing distribution system automation and the development of microgrids are making the perspective of applying intraday reconfigurations more and more appealing. This paper formulates and applies a comprehensive rule-based approach to determine the configuration with minimum losses during time for a distribution system with time-varying load and local generation patterns. The results of the optimization carried out for successive periods are used to develop an original procedure for determining the timings of the intraday reconfiguration by taking into account the ranking of the best configurations and the persistence in time of these configurations. The objective function used depends on a parameter called cost ratio, that is, the ratio between the cost of the energy losses kilowatthour and the cost of performing a switching operation. A specific indicator (called objective assessment ratio) is introduced in order to quantify the convenience of performing intraday reconfiguration with respect to maintaining during the day the same configuration leading to the lowest daily energy losses. The results obtained on two classical test systems and on a real distribution network are included, comparing the outcomes of the proposed approach with the results obtained from other methods. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

For distribution system studies, a relevant aspect is the characterisation of the aggregate demand in a feeder. The probabilistic model of the aggregate demand is very useful for system operators or aggregators to extract information about the demand side behaviour in the operation of smart grids and microgrids. The time step used to scan the aggregate demand pattern is very important to preserve the information about the consumers' behaviour and the related uncertainty. The conventional models of aggregate electrical demand consider an average value for a specific time step (e.g. 30 min to 1 h). In this study, a faster time step (1 min) is considered to construct a time-coupled probabilistic model of the aggregate residential demand based on Beta distributions. For a given number of aggregate loads, the parameters of the Beta distributions are found by taking into account the aggregate demand pattern variations at two successive time steps. The probabilistic model is then used to generate a number of aggregate demand scenarios. The effectiveness of the proposed scenario generation method is evaluated by using goodness of fit tests such as the Kolmogorov-Smirnov test and the average mean absolute percentage error. [ABSTRACT FROM AUTHOR]

For distribution system studies, a relevant aspect is the characterisation of the aggregate demand in a feeder. The probabilistic model of the aggregate demand is very useful for system operators or aggregators to extract information about the demand side behaviour in the operation of smart grids and microgrids. The time step used to scan the aggregate demand pattern is very important to preserve the information about the consumers' behaviour and the related uncertainty. The conventional models of aggregate electrical demand consider an average value for a specific time step (e.g. 30 min to 1 h). In this study, a faster time step (1 min) is considered to construct a time‐coupled probabilistic model of the aggregate residential demand based on Beta distributions. For a given number of aggregate loads, the parameters of the Beta distributions are found by taking into account the aggregate demand pattern variations at two successive time steps. The probabilistic model is then used to generate a number of aggregate demand scenarios. The effectiveness of the proposed scenario generation method is evaluated by using goodness of fit tests such as the Kolmogorov–Smirnov test and the average mean absolute percentage error. [ABSTRACT FROM AUTHOR]

Highlights: [•] Multi-objective distribution system reconfiguration with conflicting objectives. [•] Ranking of multi-objective solutions by using decision-making methods. [•] Extension of the crossover operator to analyse multi-objective solutions. [•] Adaptation of the mutation operator to address cases with adjacent branches. [•] Geometrical metric to represent Pareto fronts (current and complete) similarity. [ABSTRACT FROM AUTHOR]

Load pattern clustering based on the shape of the electricity consumption is a key tool to provide enhanced knowledge on the nature of the consumption and assist meaningful customer partitioning. This paper presents new developments to group the load patterns using an initial set of centroids specified according to a user-defined centroid model. The original Electrical Pattern Ant Colony Clustering (EPACC) algorithm is illustrated, highlighting its characteristics and parameters, with centroids evolution during the iterative process until stabilization. The EPACC results are compared with those obtained from the classical k-means algorithm to group the representative load patterns taken from a set of non-residential customers in typical weekdays. [ABSTRACT FROM PUBLISHER]

Abstract: The evolution of distribution automation technologies and the advances in distribution system optimisation studies are enabling the implementation of network configurations that are variable in time, with a limited number of configuration changes per day. The first part of this paper addresses the definition of pseudo-optimal intra-day distribution system configurations based on multi-scenario analysis handled with decision theory concepts. The resulting configurations are then used to formulate a demand response scheme for a given time period, aimed at procuring demand reductions to further decrease the distribution system losses. This scheme is driven by the calculation of the marginal loss coefficients and by the customers’ willingness to participate in the demand response action. A dedicated offer scheme to be introduced in a benefit-based mechanism for optimal demand procurement is formulated and discussed. [Copyright &y& Elsevier]

Data size reduction techniques may be helpful in the process of categorising the electrical load consumption patterns on the basis of their shape. Starting from a macro‐class of consumers defined according to certain general criteria on the type of consumers and the period of the year or week, the representative load pattern (RLP) of each consumer can be built by considering the data points in the time domain or a reduced number of features. This study exploits the effects of using the symbolic aggregate approximation (SAX) method to form the reduced set of features. The portion of the time–amplitude plane defining the RLP is partitioned into sub‐portions on the basis of the characteristics of the whole data set. A specific partitioning of the time axis is proposed on the basis of the cumulative distribution function of the RLP variations in time. Each RLP is then coded according to the SAX principles. The resulting codes are then used into a hierarchical clustering procedure. The validity of the clustering results obtained by using the SAX data representation with the proposed non‐uniform partitioning of the time axis is presented and discussed, including comparisons with the results obtained from other data size reduction techniques. [ABSTRACT FROM AUTHOR]

Abstract: Nowadays, distributed generation (DG) is playing a significant role in the electrical energy systems. The diffusion of DG in the electrical networks could be beneficial to improve network operation, but excessive amounts of DG in operation could cause violations of the system constraints. This paper presents a new method to obtain the optimal size of DG sources in electrical distribution systems, taking into account the time-dependent evolution of generation and load. This method adopts a procedure composed of two nested calculation stages. The external stage is carried out by selecting a set of candidate nodes through a clustering-based approach based on normalised loss sensitivity factors and normalised node voltages. The internal stage is an exhaustive search driven by the calculation of an objective function with energy losses and voltage profile components, aimed at finding upgraded DG sizes using exhaustive search on a set of available sizes at the candidate nodes. The resulting method avoids the combinatorial explosion of the solutions to be analysed and determines pseudo-optimal DG sizing without violation of any of the system constraints under any operating condition. The proposed method is tested on a 20kV rural distribution network, showing its effectiveness in obtaining the pseudo-optimal solution with a relatively low computational burden. [Copyright &y& Elsevier]

Abstract: In the current structure of the electricity business, distribution and supply services have been unbundled in many jurisdictions. As a consequence of unbundling, electricity supply to customers is now provided on a competitive basis. In this context, the electricity suppliers need to get accurate information on the actual behaviour of their customers for setting up dedicated commercial offers. Customer grouping on the basis of consumption pattern similarity is likely to provide effective results. This paper provides an overview of the clustering techniques used to establish suitable customer grouping, included in a general scheme for analysing electrical load pattern data. The characteristics of the various stages of the customer grouping procedure are illustrated and discussed, providing links to relevant literature references. The specific aspect of assessing the performance of the clustering algorithms for load pattern grouping is then addressed, showing how the parameters used to formulate different clustering methods impact on the clustering validity indicators. It emerges that the clustering methods able to isolate the outliers exhibit the best performance. The implications of this result on the use of the clustering methods for electrical load pattern grouping from the operator’s point of view are discussed. [Copyright &y& Elsevier]

Abstract: In current policies, targets for GHG (greenhouse gas) and more specifically CO2 emissions are set on the basis of annual emissions. However, warming effects associated with global average temperature rise depend on accumulation of GHG in the atmosphere. Due to the quantity and longevity of CO2 in the atmosphere there is increasing awareness that taking into account cumulative CO2 emissions in defining targets for restraining the growth of CO2 emissions would be particularly effective. The notion of effectiveness is linked to measuring the degree of achievement of the objectives. Considering CO2 emissions targets set over a few decades, the path of emissions reduction contains relevant information that cannot be captured by a classical measure like the distance to the target. The main contribution of this paper is the definition of an original measure of carbon dioxide reduction effectiveness, which allows comparison of specified CO2 reduction paths expressed in deterministic or probabilistic ways. Appropriate metrics are used to illustrate the proposed measure which in particular captures the importance of early action. The measure is applied to simple what-if scenarios for the EU27 electricity and heat sector to 2050, evaluating the impact of each scenario with respect to a reference case. [Copyright &y& Elsevier]

Abstract: In a symmetrical and balanced three-phase system with distorted waveforms, a well-known rule states that each harmonic order corresponds to a specified sequence (positive, negative or zero). In this ideal case, the current in the neutral conductor (or more generally in the return path) contains only triplen harmonics. However, this rule is no longer valid in practical distribution systems subject to unbalance and waveform distortion, in which phase and neutral currents at any sequence generally contain components of any harmonic order. Possible improper extension of the ideal case concepts to general situations may create a sort of myth, to be removed by providing tutorial and practical examples. This paper provides a direct quantification of the extent to which non-triplen harmonics are present in the zero-sequence current components and triplen harmonics are present in the positive and negative sequence current components. An original set of indicators, built on the basis of the theoretical symmetrical component-based framework developed by the authors, is introduced for assessing the specific impact of the triplen harmonics at the different sequences. Some classical myths based on the ideal case are illustrated and discussed on specific examples including theoretical cases and experimental analyses, quantifying the actual role played by the triplen harmonics in these applications. [Copyright &y& Elsevier]

Abstract: This paper discusses specific models and analyses to select the best cogeneration planning solution in the presence of uncertainties on a long-term time scale, completing the approach formulated in the companion paper (Part I). The most convenient solutions are identified among a pre-defined set of planning alternatives according to decision theory-based criteria, upon definition of weighted scenarios and by using the exceeding probabilities of suitable economic indicators as decision variables. Application of the criteria to a real energy system with various technological alternatives operated under different control strategies is illustrated and discussed. The results obtained show that using the Net Present Cost indicator it is always possible to apply the decision theory concepts to select the best planning alternative. Other economic indicators like Discounted Payback Period and Internal Rate of Return exhibit possible application limits for cogeneration planning within the decision theory framework. [ABSTRACT FROM AUTHOR]

Abstract: Cogeneration system planning spans a multi-year time interval and is affected by various sources of uncertainty, mainly depending on the evolution of energy loads and prices. The high level of uncertainty requires assessing the convenience of adopting predefined technological alternatives in different scenarios of variation of the uncertain variables. This paper introduces an original framework based on identifying the characteristics of small-scale and large-scale uncertainties, whereby a comprehensive approach based on multiple (long-, medium- and short-term) time frames is formulated. Medium-term time periods exhibiting small variations of both electrical and thermal load patterns are grouped together and represented through electrical/thermal load and electricity price correlated random variables (RVs). A Monte Carlo simulation of the cogeneration plant operation is carried out in the short-term by extracting the RVs for each group from multivariate Normal probability distributions. Multi-year scenarios in the long-term time frame are addressed in the companion paper (Part II). The proposed approach is applied to a real energy system. [ABSTRACT FROM AUTHOR]

Abstract: Small-scale distributed cogeneration technologies represent a key resource to increase generation efficiency and reduce greenhouse gas emissions with respect to conventional separate production means. However, the diffusion of distributed cogeneration within urban areas, where air quality standards are quite stringent, brings about environmental concerns on a local level. In addition, partial-load emission worsening is often overlooked, which could lead to biased evaluations of the energy system environmental performance. In this paper, a comprehensive emission assessment framework suitable for addressing distributed cogeneration systems is formulated. Local and global emission impact models are presented to identify upper and lower boundary values of the environmental pressure from pollutants that would be emitted from reference technologies, to be compared to the actual emissions from distributed cogeneration. This provides synthetic information on the relative environmental impact from small-scale CHP sources, useful for general indicative and non-site-specific studies. The emission models are formulated according to an electrical output-based emission factor approach, through which off-design operation and relevant performance are easily accounted for. In particular, in order to address the issues that could arise under off-design operation, an equivalent load model is incorporated within the proposed framework, by exploiting the duration curve of the cogenerator loading and the emissions associated to each loading level. In this way, it is possible to quantify the contribution to the emissions from cogeneration systems that might operate at partial loads for a significant portion of their operation time, as for instance in load-tracking applications. Suitability of the proposed methodology is discussed with respect to hazardous air pollutants such as NO x and CO, as well as to greenhouse gases such as CO2. Two case study applications based on the emission data of real microturbines are illustrated in order to highlight the effectiveness of the proposed assessment techniques. The numerical results exemplify the emission impact of distributed cogeneration systems operating under general and realistic loading conditions with respect to average and state-of-the-art conventional technologies. [Copyright &y& Elsevier]

This paper presents an original and effective application of support vector clustering (SVC) to electrical load pattern classification. The proposed SVC-based approach combines the calculation of the support vectors, carried out by using a classical procedure adopting a Gaussian kernel, with a specifically developed deterministic algorithm to form the clusters. This algorithm exploits the meaningful location of the bounded support vectors (BSVs) to define the outliers, identifying the clusters in function of the distance of the non-BSVs to the BSVs. Its implementation is less computationally intensive than other existing approaches and the cluster formation is driven by a single user-defined threshold. Extended comparison to other clustering methods is included to show the effectiveness of the proposed approach in grouping multidimensional load pattern data into non-overlapping clusters. This effectiveness is confirmed by the calculation of various cluster validity indicators. In particular, the most successful tasks are the identification of the outliers and the more effective formation of small numbers of clusters with respect to other methods. [ABSTRACT FROM AUTHOR]

Abstract: This paper provides a multi-faceted view on the characterization of the waveform distortion in grid-connected photovoltaic (PV) plants from experimental results. The focus is set on the characterization of the waveform distortion occurring under different operating conditions in field measurements and laboratory tests. The assessment is carried out by considering the system-based point of view, on the basis of the measurements gathered at the interface between the PV plant and the grid or the supply point in the laboratory. New methodological hints on the formulation of the experimental tests are provided. The results of the waveform distortion analysis for harmonic currents and voltages are compared to the requirements of present power quality standards, indicating that in practical cases the current distortion can be significantly higher than in normal test conditions. Furthermore, the key aspect concerning harmonic and interharmonic modelling of multiple grid-connected PV inverters is addressed. Experimental results on plant configurations with multiple PV inverters show that low-order harmonics sum up almost arithmetically, whereas the higher-order harmonics and the interharmonics sum up in an almost Euclidean way. [Copyright &y& Elsevier]

Abstract: The recent development of efficient thermal prime movers for distributed generation is changing the focus of the production of electricity from large centralized power plants to local generation units scattered over the territory. The scientific community is addressing the analysis and planning of distributed energy resources with widespread approaches, taking into account technical, environmental, economic and social issues. The coupling of cogeneration systems to absorption/electric chillers or heat pumps, as well as the interactions with renewable sources, allow for setting up multi-generation systems for combined local production of different energy vectors such as electricity, heat (at different enthalpy levels), cooling power, hydrogen, various chemical substances, and so forth. Adoption of composite multi-generation systems may lead to significant benefits in terms of higher energy efficiency, reduced CO2 emissions, and enhanced economy. In this light, a key direction for improving the characteristics of the local energy production concerns the integration of the concepts of distributed energy resources and combined production of different energy vectors into a comprehensive distributed multi-generation (DMG) framework that entails various approaches to energy planning currently available in the literature. This paper outlines the main aspects of the DMG framework, illustrating its characteristics and summarizing the relevant DMG structures. The presentation is backed by an extended review of the most recent journal publications and reports. [Copyright &y& Elsevier]

Combined production of electricity, heat and cooling power in trigeneration represents a key option for the development of high-efficiency and cost-effective integrated energy systems. The complexity of the possible plant schemes calls for the adoption of general models handling multiple interconnected components and energy flows of various typologies. This paper presents a comprehensive input–output matrix approach aimed at modelling small-scale trigeneration equipment taking into account the interactions among plant components and external energy networks. Starting from the definitions of specific efficiency matrices for each plant component and from a matrix representation of the relevant interconnections, an overall efficiency matrix representing the whole plant is constructed. This construction is carried out by means of an original procedure, suitable for automatic and symbolic implementation, which, exploiting graph theory concepts, explores the tree formed by the backward paths from outputs to inputs. The proposed formulation maintains the separation among the individual energy vectors, each of which can be associated to its time-dependent price, providing the basic framework for formulating optimization problems concerning management of trigeneration systems within an energy market context. A numerical example referred to the optimal operation of a composite scheme with absorption and electric chillers is illustrated and discussed. The results obtained show the modelling effectiveness of the proposed matrix formulation. [Copyright &y& Elsevier]

Abstract: This paper presents an original application of the Ant Colony Optimization concepts to the optimal reconfiguration of distribution systems, with the objective of minimizing the distribution system losses in the presence of a set of structural and operational constraints. The proposed algorithm starts from the current configuration of the system and proceeds by progressively introducing variations in the configuration according to local and global heuristic rules developed within the Hyper-Cube Ant Colony Optimization framework. Results of numerical tests carried out on a classical system and on a large real urban distribution system are presented to show the effectiveness of the proposed approach. [Copyright &y& Elsevier]

The increasing diffusion of small-scale energy systems within the distributed generation (DG) paradigm is raising the need for studying the environmental impact due to the different DG solutions in order to assess their sustainability. Addressing the environmental impact calls for building specific models for studying both local and global emissions. In this framework, the adoption of natural gas-fueled DG cogeneration technologies may provide, as a consequence of cogeneration enhanced overall energy efficiency and of natural gas relatively low carbon content, a significant reduction of global impact in terms of CO2 emissions with respect to the separate production of electricity and heat. However, a comprehensive evaluation of the DG alternatives should take into account as well the impact due to the presence of plants spread over the territory that could increase the local pollution, in particular due to CO and NO x , and thus could worsen the local air quality. This paper provides an overview on the characterization of the emissions from small-scale natural gas-fueled cogeneration systems, with specific reference to the DG technologies nowadays most available in the market, namely, microturbines and internal combustion engines. The corresponding local and global environmental impacts are evaluated by using the emission balance approach. A numerical case study with two representative machines highlights their different emission characteristics, also considering the partial-load emission performance. [Copyright &y& Elsevier]

Abstract: Poly-generation systems for combined production of manifold energy vectors such as electricity, heat at different enthalpy levels (for instance, in the form of hot water and steam), and cooling power from a unique source of primary energy (typically natural gas) are increasingly spreading, above all on a small-scale basis (below 1MWe), owing to their enhanced energy, environmental and economic characteristics. Availability of suitable tools for assessing the performance of such systems is therefore fundamental. In this paper, a unified general model is proposed for assessing the energy and CO2 emission performance of any type of poly-generation system with natural gas as the energy input. In particular, the classical energy saving model for cogeneration systems is extended to include in the analysis further energy vectors by defining the novel PPES (Poly-generation Primary Energy Saving) indicator. In addition, equivalent efficiencies for CO2 emission assessment are defined and used in the formulation of the new PCO2ER (Poly-generation CO2 Emission Reduction) indicator, specifically introduced for environmental analysis. The formal analogy between the PPES and the PCO2ER indicators is highlighted. Numerical applications are provided to show the effectiveness of the proposed models and to quantify the typical benefits that poly-generation systems can bring. In particular, the new indicators are of relevant interest for both energy planners and policy makers, above all in the outlook of formulating financial incentive strategies, as it already occurs for cogeneration systems, or of participating to specific energy-related markets such as the ones for trading white certificates or emission allowances. [Copyright &y& Elsevier]

In this paper, the concepts related to loss partitioning among the phase currents in three-phase distribution systems are revisited in the light of new findings identified by the authors. In particular, the presence of a paradox in the classical loss partitioning approach, based on the use of the phase-by-phase difference between the input and output complex power, is highlighted. The conditions for performing effective loss partitioning without the occurrence of the paradox are thus established. The corresponding results are then used to extend the branch current decomposition loss allocation method for enabling its application to three-phase unbalanced distribution systems with distributed generation. Several numerical examples on a three-phase line with grounded neutral and on the modified IEEE 13-node test system are provided to assist the illustration and discussion of the novel conceptual framework. [ABSTRACT FROM AUTHOR]

Abstract: In the restructured electricity industry, meaningful loss allocation methods are required in order to send correct signals to the market taking into account the location and characteristics of loads and generations, including the local sources forming the distributed generation (DG). This paper addresses the issues related to loss allocation in radial distribution systems with DG, with a three-fold focus. First, the key differences in the formulation of the loss allocation problem for radial distribution systems with respect to transmission systems are discussed, specifying the modeling and computational issues concerning the treatment of the slack node in radial distribution systems. Then, the characteristics of derivative-based and circuit-based loss allocation techniques are presented and compared, illustrating the arrangements used for adapting the various techniques to be applied to radial distribution systems with DG. Finally, the effects of introducing voltage-controllable local generation on the calculation of the loss allocation coefficients are discussed, proposing the adoption of a “reduced” representation of the system capable of taking into proper account the characteristics of the nodes containing voltage-controllable DG units. Numerical results are provided to show the time evolution of the loss allocation coefficients for distribution systems with variable load and local generation patterns. [Copyright &y& Elsevier]

Abstract: The diffusion of cogeneration and trigeneration plants as local generation sources could bring significant energy saving and emission reduction of various types of pollutants with respect to the separate production of electricity, heat and cooling power. The advantages in terms of primary energy saving are well established. However, the potential of combined heat and power (CHP) and combined cooling heat and power (CCHP) systems for reducing the emission of hazardous greenhouse gases (GHG) needs to be further investigated. This paper presents and discusses a novel approach, based upon an original indicator called trigeneration CO 2 emission reduction (TCO 2 ER), to assess the emission reduction of CO2 and other GHGs from CHP and CCHP systems with respect to the separate production. The indicator is defined in function of the performance characteristics of the CHP and CCHP systems, represented with black-box models, and of the GHG emission characteristics from conventional sources. The effectiveness of the proposed approach is shown in the companion paper (Part II: Analysis techniques and application cases) with application to various cogeneration and trigeneration solutions. [Copyright &y& Elsevier]

Abstract: This paper provides a set of specific examples to show the effectiveness of the trigeneration CO 2 emission reduction (TCO 2 ER) indicator proposed in the companion paper (Part I: Models and indicators) to assess the greenhouse gas (GHG) emission reduction from cogeneration and trigeneration systems. Specific break-even analyses are developed by introducing further indicators, with the aim of assessing the conditions for which different types of combined systems and conventional separate production systems are equivalent in terms of GHG emissions. The various emission indicators are evaluated and discussed for a number of relevant application cases concerning cogeneration and trigeneration solutions with different types of equipment. Scenario analyses are carried out to assess the possible emission reduction benefits from extended diffusion of cogeneration and trigeneration in regions characterized by different energy generation frameworks. The results strongly depend on the available technologies for combined production, on the composition of the energy generation mix, and on the trend towards upgrading the various generation systems. The numerical outcomes indicate that cogeneration and trigeneration solutions could bring significant benefits in countries with prevailing electricity production from fossil fuels, quantified by the use of the proposed indicators. [Copyright &y& Elsevier]

This paper introduces an original and rigorous formulation for computing the unbalance and distortion components of phase and neutral currents in the framework of the symmetrical component transformation. The proposed formulation extends recent literature results, in which different matrices were used for unbalance characterization in the presence of distorted waveforms and provides, at the same time, an innovative interpretation of the neutral current waveform components. New indicators are also defined to combine the effects of unbalance and waveform distortion, extending the set of indicators currently adopted in the power-quality standards. A set of illustrative examples is presented to show the applicability of the proposed approach. These include four circuits, two real-case applications, and an example taken from the IEEE trial-use standard 1459–2000. [ABSTRACT FROM AUTHOR]

The allocation of the system losses to suppliers and consumers is a challenging issue for the restructured electricity business. Meaningful loss allocation techniques have to be adopted to set up appropriate economic penalties or rewards. The allocation factors should depend on size, location, and time evolution of the resources connected to the system. In the presence of distributed generation, the variety of the power flows in distribution systems calls for adopting mechanisms able to discriminate among the contributions that increase or reduce the total losses. Some loss allocation techniques already developed in the literature have shown consistent behavior. However, their application requires computing a set of additional quantities with respect to those provided by the distribution system power flow solved with the backward/forward sweep approach. This paper presents a new circuit-based loss allocation technique, based on the decomposition of the branch currents, specifically developed for radial distribution systems with distributed generation. The proposed technique is simple and effective and is only based on the information provided by the network data and by the power flow solution. Examples of application are shown to confirm its effectiveness. [ABSTRACT FROM AUTHOR]

The recent evolution of the electricity business regulation has given new possibilities to the electricity providers for formulating dedicated tariff offers. A key aspect for building specific tariff structures is the identification of the consumption patterns of the customers, in order to form specific customer classes containing customers exhibiting similar patterns. This paper illustrates and compares the results obtained by using various unsupervised clustering algorithms (modified follow-the-leader, hierarchical clustering, K-means, fuzzy K-means) and the self-organizing maps to group together customers with similar electrical behavior. Furthermore, this paper discusses and compares various techniques—Sammon map, principal component analysis (PCA), and curvilinear component analysis (CCA)—able to reduce the size of the clustering input data set, in order to allow for storing a relatively small amount of data in the database of the distribution service provider for customer classification purposes. The effectiveness of the classifications obtained with the algorithms tested is compared in terms of a set of clustering validity indicators. Results obtained on a set of nonresidential customers are presented. [ABSTRACT FROM AUTHOR]

Trigeneration refers to the combined production of electricity, heat, and cooling. In a competitive energy market frame- work, the adoption of Combined Heat, Cooling, and Power (CHCP) plants may become profitable with respect to traditional systems, where electricity, heat, and cooling are produced or purchased separately. This paper illustrates and evaluates the possible benefits of adopting different trigeneration alternatives in the design of a new energy system, with the specific focus on comparing different cooling production solutions. For the cooling side of CHCP systems, most of the literature refers to absorption groups fed by cogenerated thermal energy. Here, the trigeneration concept is ex- tended to also include conventional electric chillers, heat pumps, or direct-fired absorption chillers. Comparative analysis of the trigeneration solutions is carried out for a hospital site, by performing time-domain simulations to characterize the out-of-design operation and different regulation strategies of the equipment. Poor effectiveness of using classical energy efficiency indices is discussed. A more effective economic analysis, where buying/selling electricity in a competitive market is specifically considered, is then per- formed. Finally, a multiscenario analysis is carried out for assessing the impact of electricity and gas price variations on the choice of the most convenient trigeneration solution. [ABSTRACT FROM AUTHOR]

Abstract: In competitive electricity markets, electricity customer classification is becoming increasingly important, due to new degrees of freedom the electricity providers have been given in formulating dedicated tariff options for different customer classes. Several customer classification techniques have been proposed in the literature, in which the load patterns are typically represented by time–domain data. However, a good load pattern representation requires using several data for each customer, causing possible difficulties in storing a large amount of data in the electricity company''s databases. In order to reduce the number of data to be stored for each customer, an original solution is proposed in this paper, based on post-processing the results of time–domain measurements to obtain a reduced set of data defined in the frequency domain. The new set of data is successively used in a customer classification procedure, e.g. a suitable clustering technique, whose adequacy can be assessed by means of properly defined indicators. This paper provides the mathematical background for the frequency–domain data definition and investigates on the effectiveness of the customer classification for different choices of the number of data to be stored. Results obtained on a set of customers belonging to a real distribution system are presented and discussed. These results show that the proposed representation is effective in reducing the number of data stored while maintaining a satisfactory level of classification adequacy. [Copyright &y& Elsevier]

In reliability analysis of distribution systems, random events like the occurrence of a fault or the time to restore the service after a fault are represented by using random variables (RVs), so that the reliability indices built on the basis of these RVs also become RVs. Existing techniques for the evaluation of the probability distributions of reliability indices are typically based on Monte Carlo and analytical simulations. This paper presents a new method for computing the probability distribution of reliability indices. The random sums introduced by the randomness of the number of fault occurrences in the time interval of analysis are handled by using a characteristic functions-based approach. The direct convolution of the probability density functions is avoided by resorting to the properties of the compound Poisson process. In addition, the direct and inverse discrete Fourier transforms are used to allow for handling any type of probability distribution. The proposed method is an effective alternative to the existing methods, providing a fast and simple computation of probability distributions and moments for local and global reliability indices. Results obtained for large real urban distribution systems are presented. [ABSTRACT FROM AUTHOR]

The rational buyer procedure provides the competitive the procurement of capacity-based ancillary services (AS) hi unbundled markets by the independent grid operator (IGO). The capacity-based AS are prioritized in order of ascending response times. Prioritization allows substitutability of the AS by automatically making the unused capacity of a higher priority AS usable for any lower priority AS without the need of submitting additional offers. We develop an efficient scheme for the rational buyer procedure for the acquisition of the prioritizable capacity-based AS. The scheme allows the simultaneous determination of the successful offers in the multiauction procedure through the effective deployment of discrete programming notions and the exploitation of the structural characteristics of the formulation. A key feature is the incorporation of physical constraints such as capacity ramp-rate, and interzonal constraints. The use of bounding techniques combined with procedures for the quick detection of infeasible combinations of the offer prices and the identification of avoidable calculations leads to reducing the computational burden. The effectiveness and computational efficiency of the scheme are Illustrated with representative numerical results including case studies based on the IEEE 118-bus network. [ABSTRACT FROM AUTHOR]

Presents tools used to classify electricity customers based on their electrical behavior. Discussion on a priori and field indices; Use of an automatic clustering procedure to organize customers; Analysis of the possibility of a tariff diversification for various customer classes.

Provides a corrected reprint of an article that was previously published in 'IEEE Transactions on Power Systems.'

Presents a study that described a physical flow mechanism for allocating the reactive power support requirements provided by generators in multitransaction networks. Discussion on challenges in the characterization and evaluation of reactive power support requirements allocations; Details on the use of the multitransaction framework for the allocation of loss; Results and implications.

The penetration of the distributed energy resources in the distribution networks is facilitated by the structure of the microgrids (MGs). The MG operator (MGO) can schedule the MG resources to meet the local load and participate in the wholesale markets. In this article, a new model is developed for the MGO participation in the day-ahead (DA) (energy and reserve) and the real-time (RT) energy markets under uncertainties. For this purpose, the effect of the uncertainties of demand and generation from renewable energy sources on the MGO decisions is represented in a two-stage stochastic model. The MGO bids in the DA and RT markets are modeled as the first and the second stage decisions, respectively. Moreover, the information gap decision theory method is used to model the behavior of the MGO to address the uncertainties of the RT energy market price and the probability of calling the reserve. The results show that as the RT price uncertainty radius increases, the energy sold to the RT market decreases/increases in the risk-averse/risk-taker strategy. Furthermore, to manage the uncertainty related to the probability of calling the reserve, the reserve capacity provided by the MGO in the risk-averse and the risk-taker strategies decreases and increases, respectively. [ABSTRACT FROM AUTHOR]

About ten hydroelectric power plants realized from 1970 to 1990 in Romania are confronted with stator overheating. The developed mathematical model analyzes the voltage stability based on modal analysis of the Jacobian matrix, identifying the hazardous modes of variation between voltage and flow rate, correlated with the characteristics of the analyzed generators and their response to these variations. Vulnerable elements in the system for inductive and capacitive modes of operation are identified. In these conditions, hydro generators cannot attend the secondary voltage control, not even for a frequency power dependency control. The elaborated mathematical model was tested at the hydroelectric power plants Gilceag, Mariselu, and Susag with similar functioning conditions. The necessary conditions for stator ventilation and variation of flow hydrodynamic parameters during the operation were established. The theoretical model was tested with an experimental method applied separately for the thermal and ventilation conditions. Some results obtained during the measurements are illustrated and correlated with the theoretical results. The model was tested to prevent the onset instability of voltage drops and accelerated overheating. Finally, some solutions to minimize the stators overheating based on local conditions are recommended. [ABSTRACT FROM AUTHOR]

In the power and energy systems area, a progressive increase of literature contributions that contain applications of metaheuristic algorithms is occurring. In many cases, these applications are merely aimed at proposing the testing of an existing metaheuristic algorithm on a specific problem, claiming that the proposed method is better than other methods that are based on weak comparisons. This 'rush to heuristics' does not happen in the evolutionary computation domain, where the rules for setting up rigorous comparisons are stricter but are typical of the domains of application of the metaheuristics. This paper considers the applications to power and energy systems and aims at providing a comprehensive view of the main issues that concern the use of metaheuristics for global optimization problems. A set of underlying principles that characterize the metaheuristic algorithms is presented. The customization of metaheuristic algorithms to fit the constraints of specific problems is discussed. Some weaknesses and pitfalls that are found in literature contributions are identified, and specific guidelines are provided regarding how to prepare sound contributions on the application of metaheuristic algorithms to specific problems. [ABSTRACT FROM AUTHOR]

Thermal energy systems (TES) contribute to the on-going process that leads to higher integration among different energy systems, with the aim of reaching a cleaner, more flexible and sustainable use of the energy resources. This paper reviews the current literature that refers to the development and exploitation of TES-based solutions in systems connected to the electrical grid. These solutions facilitate the energy system integration to get additional flexibility for energy management, enable better use of variable renewable energy sources (RES), and contribute to the modernisation of the energy system infrastructures, the enhancement of the grid operation practices that include energy shifting, and the provision of cost-effective grid services. This paper offers a complementary view with respect to other reviews that deal with energy storage technologies, materials for TES applications, TES for buildings, and contributions of electrical energy storage for grid applications. The main aspects addressed are the characteristics, parameters and models of the TES systems, the deployment of TES in systems with variable RES, microgrids, and multi-energy networks, and the emerging trends for TES applications. [ABSTRACT FROM AUTHOR]

28 June 2018 was the 100th anniversary of the first presentation on symmetrical components made by Charles LeGeyt Fortescue at the 34th Annual Convention of the American Institute of the Electrical Engineers in Atlantic City (NJ, USA). The introduction of the symmetrical component concept was immediately seen as a milestone for electrical system studies, and many applications have been developed during the ensuing years. Today, refined or advanced contributions to conceptual and practical aspects of electrical applications are still being proposed based on the powerful structure of symmetrical components. This paper recalls the most significant steps made in the electrical engineering field after the introduction of the symmetrical component theory, and indicates recent developments concerning the studies on electrical machines, harmonics and interharmonics in different applications, and the operation of power and distribution systems with distributed energy resources. [ABSTRACT FROM AUTHOR]

Summary: The growing energy demand in the world and the concern for environmentally damaging energy sources have led to an increased interest in seeking alternative renewable energy sources, such as wind energy. Furthermore, choosing effective locations for wind power plants has become a key issue in project planning. However, prior to implementation, such projects should be confirmed as economically viable. This article is a systematic review of the literature carried out with the aim to identify the main factors that impact the economic feasibility of wind energy investments. The search was performed in the ISI Web of Science (WoS) electronic database, from which 120 papers were extracted after a selection process, and were analyzed individually. As a result of the review analysis, 23 factors that have an impact on feasibility analysis were identified and organized in five categories: location (surface roughness, turbine location), economic (investment costs, operation and maintenance costs, avoided energy cost, depreciation, land rent), political (interest rates and taxes, energy sales price, inflation, financing conditions), climatic (wind speed, air density, temperature, air pressure), and technical (turbine height, installed wind power, lifetime, efficiency, rotor diameter, operation time, number of turbine blades, construction time). These factors can directly impact the cost of capital and/or energy production, affecting the economic viability of wind farms. In the last decade, there has been an exponential growth in publications about economic feasibility of wind investments. The wind investments growth has been accompanied by financial studies about this subject. This study provides insights on the main variables used in wind energy feasibility studies. The results may assist researchers and investors to identify the key parameters that are being examined in the literature, and to evaluate which ones should be considered in their study to ensure a sustainable development of power generation through the wind source. [ABSTRACT FROM AUTHOR]