Search

Among different solutions to increase flexibility of electricity system, grid interactive water heaters (GIWHs) can make a large contribution, against a relatively low cost. They can advantageously be used within a single building, a local energy community or within an entire distribution grid, thanks to the very fast response time, low cost, highly distributed resource and widely demonstrated technology. In the near future, the flexibility potential of GIWHs will certainly increase, thanks to the advantageous flexibility programs that have been implementing in some area of the world, with the aim of coordinating several million of GIWHs with the electricity network. In this study, we assess the potential value that the flexibility of GIWHs can bring to the electrical power system, compared to the other sources of flexibility, focusing on the US market, specifically California, Oregon and Washington. The GIWH technology and the main GIWH control strategies are described, highlighting the flexibility behaviour of GIWHs. An overview of the GIWH pilot programs currently developed in the US market is provided, and current available technologies are shown, both for new and for retrofit GIWH installations. Most of the papers discussed in the literature focus on different aspects of demand response (DR), but very few of them focus specifically on GIWHs, and none of them offers a review of GIWHs in the US context. The present work thus constitutes a research gap, and could help stakeholders to assess the US GIWH market evolution, identifying the potential value of GIWH flexibility.

The Blorin project started at the end of 2019 to support the implementation of a blockchain platform to support the energy services provision from end users by means of Demand Response and Vehicle to Grid programs. The experimental part of the project is being carried out on two Mediterranean islands and inside the University campus in Palermo. Customized smart contracts have been designed to support the active participation of end users to regulation services for the two weak electrical grids of the islands in the view of a deep penetration of renewable energy in the two energy systems. In particular, the smart contract for remuneration accounts for the very special energy situation of islands where TSO, DSO, energy seller and aggregator collapse in a unique market actor. Moreover, in islands the electricity provision is typically still relying on diesel generators thus strongly connecting the Demand Response programs benefit to the reduction of fuel consumption, as an effect of increased efficiency of diesel generators. Due to the critical international situation and to the climate crisis, fossil fuels get more and more costly, thus a speed up of the energy transition in small islands is highly needed. This paper addresses the problem of designing a customized smart contract for remuneration of Demand Response service provision in small islands.

In this chapter, the problem of energy management in smart grids is outlined. Optimized energy management is considered here as the operation of energy and power flow control in the aim of attaining minimum cost or minimum power losses while meeting technical constraints. Of course, according to the type of energy system in which such operation is carried out, the meaningful variables and objectives in the problem may largely change. As the extension of the system increases, the influence of the physical behaviour of the electrical power lines takes a more important role. Power electronics takes instead an increasing influence, as the dimension of the power system decreases although Kirchhoff's laws must always be verified. Energy management is also an interesting issue in multi-carrier energy hubs that implement a recent tendency in energy systems interfacing smart grids. They include different energy resources that need to be managed differently, but in an integrated fashion. This chapter offers an overview of energy management in a small system using a two-level centralized approach.

In this paper, the authors propose a new protection strategy for electrical Medium Voltage distribution networks, based on a distributed intelligence system composed of a central unit and of many local processing units. The distributed intelligence system can precisely identify and locate faults in suitably limited times. Each local processing unit is composed of a data acquisition system and a data analysis system. The first allows the accurate reconstruction of the fundamental using only 1.5 cycles of under fault transient electrical quantities. The second performs suitably precise on-line fault diagnosis based on the data provided by the data acquisition module. The data acquisition algorithm and the data analysis algorithm are managed by the data processing system of the remote processing units implemented on a micro-processor. With the proposed architecture, if local acquisition, elaboration and clearing times are limited, the faulted line experiences only two micro-interruptions, also during multi-phase permanent faults, with a great improvement of the quality of the service. Some experimental results on a simulated test system, proving the efficacy and simplicity of the proposed approach, are reported.

The paper illustrates the interventions for improving security of a WiFi communication system applied in the automatic management of a Medium Voltage network. The management system fails if the data measured at the secondary substations can’t flow regularly. In this paper the security of the transmission as function of the action range of the radio channel, on the data sending time of the IEEE 802.11 protocol, and of the out of use of a WiFi node. Then, a modified IEEE 802.11 protocol is described, for making secure the transmission in presence of a high number of WiFI nodes. Finally, a probabilistic analysis in presented for analyzing the problem from an economical point of view.

A high level of power quality in distribution networks is obtained by means of a diagnostic software, that establishes on-line the status of the network, by elaborating the measured data. An efficient telecommunication system is necessary, from whose reliability depends the security of the timely interventions on the network in case of fault. In the paper, after a brief examination of the diagnostic method, the telecommunication system is examined. The WiFi system has been considered most suitable, for its economy, for the diagnostic service, besides it is not suitably reliable for how it is managed by the IEEE 802.11 protocol for this application. In this work a new protocol derived by the existing IEEE 802.11 is described, highlighting the improvements that it introduces and verifying its capability for the diagnostic service. An application shows its potentiality

In this chapter, we try to connect the urban design features with energy consumption and consequent pollution parameters. After a review of a selected set of approaches to Urban Energy Systems study with a special focus on electrical power systems, urban energy systems are proposed as networks of multi-source hybrid energy hubs, where different energy flows are collected at the same bus and can be stored, delivered or transformed as needed. Resources at the hub and infrastructures interact with each other; therefore, both definition and boundaries of such energy systems at urban level are difficult to be clearly outlined. Similarly, the possibility to generate new operational models based on existing critical urban infrastructures is also challenging. This contribution proposes a preliminary study of urban energy hubs. Operations of thermal, electrical and mobility infrastructures are considered as qualifying features of the hub, but still the interconnected operation is not taken into account. The application part shows, indeed, the analysis and optimized design of the energy system serving two different urban districts. The related optimized parametric design of power generation infrastructures is considered as a function of urban features. The results about emissions and costs provide some interesting conclusions about the linkage between energy planning and urban features at district level, thus allowing, as possible application of this work, an energy-based territorial planning for urban contexts.

The paper presents a method for the study of large interconnected earthing systems in High Voltage networks. The mathematical model proposed for calculating the distribution of the Single-line-to-Earth fault current is useful for a methodical and accurate analysis of complex systems having meshed configuration and more sources, and has practical application for the Transmission System Operator. Two case studies are provided. The first one considers a fault occurring inside and outside a station in a real 220 kV transmission network. In the second example, the proposed methodology is compared with the classical “Double-sided elimination” method.

In this chapter, the problem of energy management in smart-grids is outlined. Optimized energy management is here considered as the operation of energy and power flow control in the aim of attaining minimum cost or minimum power losses while meeting technical constraints. Of course, according to the type of energy system in which such operation is carried out, the meaningful variables and objectives in the problem may largely change. As the extension of the system increases, the influence of the physical behaviour of the electrical power lines takes a more important role. Power electronics takes instead an increasing influence, as the dimension of the power system decreases although Kirchhoff laws must always be verified. Energy management is also an interesting issue in multi-carrier energy hubs that implement a recent tendency in energy systems interfacing smart-grids. They include different energy resources that need to be managed differently, but in an integrated fashion. The chapter offers an overview of energy management in a smallsystem using a two levels centralized approach.

In this paper, a new and efficient model for variables representation, named F-coding, in optimal power dispatch problems for smart electrical distribution grids is proposed. In particular, an application devoted to optimal energy dispatch of Distributed Energy Resources including ideal storage devices is here considered. Electrical energy storage systems, such as any other component that must meet an integral capacity constraint in optimal dispatch problems, have to show the same energy level at the beginning and at the end of the considered timeframe for operation. The use of zero-integral functions, such as sinusoidal functions, for the synthesis of the charge and discharge course of batteries is thus consequential. The issue is common to many other engineering problems, such as any dispatch problem where resources must be allocated within a given amount in a considered timeframe. Many authors have proposed different methods to deal with such integral constraints in the literature on smart grids management, but all of them do not seem very efficient. The paper is organized as follows. First, the state of the art on the optimal management problem is outlined with special attention to treatment of integral constraints, then the proposed new model for variables representation is described. Finally, the multiobjective optimization method and its application to the optimal dispatch problem considering different variables representations are considered.

Service continuity is one of the major aspects in the definition of the quality of the electrical energy, for this reason the research in the field of faults diagnostic for distribution systems is spreading ever more. Moreover the increasing interest around modern distribution systems automation for management purposes gives faults diagnostics more tools to detect outages precisely and in short times. In this paper, the applicability of an efficient fault location and characterization methodology within a centralized monitoring system is discussed. The methodology, appropriate for any kind of fault, is based on the use of the analytical model of the network lines and uses the fundamental components rms values taken from the transient measures of line currents and voltages at the MV/LV substations. The fault location and identification algorithm, proposed by the authors and suitably restated, has been implemented on a microprocessor-based device that can be installed at each MV/LV substation. The speed and precision of the algorithm have been tested against the errors deriving from the fundamental extraction within the prescribed fault clearing times and against the inherent precision of the electronic device used for computation. The tests have been carried out using Matlab Simulink for simulating the faulted system.

In this work, a power dispatch problem for a system composed of an aggregate of loads and an electrical energy storage system is considered. The approach to solve the optimal dispatch is innovative and shows good performances in limited calculation times. According to the more recent indications coming from the European distributors, the architecture for energy dispatch at distribution level will be hierarchical. The 'Aggregator' is the interface between groups of loads and the energy distributor and sends the individual consumers the desired load profiles, following which the user may gets a discount on the energy bill. On the other hand, the energy tariff may follow a given daily profile either Time Of Use or even a Real Time Pricing structure. Given a desired energy profile of an aggregate of loads owned by the same entity, the day ahead price of energy in the subsequent 24 hours and a forecast of the consumed power from the same aggregate of loads, it is possible to dispatch the power injected or absorbed by the energy storage system and the programmable loads, representing them as continuous variables with specific analytic properties. The application carried out over an energy district shows the efficiency and ease of use of the proposed approach and gives a new insight into the field of scheduling of resources in all fields. © 2014 IEEE.

The subject addressed in this paper is the definition of some strategies for the design and the optimaized management of EES (Electrical Energy Storage) systems, for an existing islanded distribution network supplying the Island of Pantelleria (Italy) in the Mediterranean Sea. In the paper the authors have drawn interesting conclusions through the application of an efficient MO (multi-objective) optimization algorithm, the NSGA-II, minimizing the energy losses in the grid, the total electricity generation cost and the greenhouse gas emissions. The results obtained for different installation scenarios of the EES are presented and discussed, putting into evidence the technical, environmental and economical benefi{ligature}ts of using EES as well as the technical issues connected to their installation into an existing distribution network. The paper describes in details the second part of a feasibility study about the transition from a "fuel-based" traditional centralized electrical system to an active and smart "renewables-based" electrical distribution system. © 2013 Elsevier Ltd.

In this paper an optimization approach to devise efficient management strategies for Electric Vehicles parking lots is proposed. A Monte Carlo approach is used to evaluate the load consumption profile for groups of Electric Vehicles showing different features. The Monte Carlo approach allows to combine the different social and economical features affecting the commercial penetration of Electric Vehicles with the technical aspects. The basic feature to be assessed is the initial State Of Charge, which in turn depends on the distance travelled by the vehicle since the last recharge and thus by the usage of the vehicle (private, professional). The model is then used to optimize some objective function such as the losses minimization or the cost of purchased energy minimization. Finally, a Simulated Annealing algorithm is used to identify the time intervals, along the day, in which the Electric Vehicles should be put in charge to minimize technical or economical objectives. The objective function is evaluated using a probabilistic model based on Monte Carlo simulations. © 2013 Springer-Verlag Berlin Heidelberg.

The paper proposes an analytical study about the design and operation of distributed Electrical Storage Systems(ESS) in an active distribution network supplying a Mediterranean island, according to different criteria. The approach is based on the application of a multi-objective optimization algorithm (NSGA-II) that outputs a set of optimized schedules of the ESS in different configurations when operated according to different criteria (minimum energy losses in the grid, total generation cost, greenhouse gas emissions, limiting the fluctuations of the generation from fossil fuel plants). Moreover the variability of the voltage profile has been investigated also by a comparison with a reference scenario characterized by the absence of storage systems.

Load management includes all the techniques, logics, actions and programs through which the electric utilities and the customers are able to manage loads absorption in a more prudent and efficient way; it determines economic benefits for the users, but also allows a network management and operation simpler and cheaper, determining technical and economic benefits. The present paper constitutes a detailed study of interventions and techniques to control demand in the residential and tertiary sectors and the effects that these actions have on the entire electrical system and its management. It discusses the implications of such control actions in terms of reduction of network losses and related cost savings, of the deferral of actions on the expansion and upgrading of the electrical systems and of environmental issues.

In this paper, the authors analyze the impact of the participation of customers to the sustainable implementation of energy rational strategies in microgrids. The management of shiftable loads is compared to the control of real and reactive storage systems in smart grids. An optimization algorithm is used as analysis tool to assess the impact of such control variables in different conditions. The results clearly indicate that if shiftable loads are of suitable size, they have a more promising as tools to both reduce losses and to flatten the peak load through the HV/MV bus. Many tests have been carried out on a real experimental MV system in the area of Rome Italy.

This paper studies the possibility to use efficient multimodal optimizers for multi-objective optimization. In this paper, the application area considered for such new approach is the optimal dispatch of energy sources in smart microgrids. The problem indeed shows a non uniform Pareto front and requires efficient optimal search methods. The idea is to exploit the potential of agents in population-based heuristics to improve diversity in the Pareto front, where solutions show the same rank and are thus equally weighted. Since Pareto dominance is at the basis of the theory of multi-objective optimization, most algorithms show the non dominance ranking as quality indicator, with some problem in finding sufficiently diverse solutions. Other algorithms, such as the Indicator Based Evolutionary Algorithm, use most commonly the Hypervolume indicator which also intrinsically shows diversity preserving problems. In this paper, the Glow-worm swarm optimizer is used as multimodal optimization method over a set of solutions ordered based on non dominance. After the introduction of this algorithm, its multiobjective implementation is briefly outlined. Then some tests are carried out on test functions taken from the literature giving quite encouraging results. Finally, the problem of optimal energy dispatch in smart microgrids is described and different applications are shown comparing the results with those obtained emplying the Non Dominated Sorting Genetic Algorithm II. (6 pages)

This paper investigates the possibility to use a new modeling of Energy Storage Systems based on zero integral functions. Such functions represent the course of the energy level stored in batteries during the solution of optimal management problems in smart-grids. Storage devices, such as all the other components that are required to meet an integral capacity constraint along the dispatch time, must show the same State of Charge at the start and at the end of the timeframe considered for operation. In this paper, a set of sinusoidal functions have been used for the synthesis of the charge and discharge course of energy Storage Systems. Such representation allows to eliminate the difficult constraint about the State of Charge at the start and at the end of the considered timeframe and in general allows to reduce the number of parameters involved in the optimization. A few tests of the proposed representation for an optimal dispatch problem solved with evolutionary computation in a small distribution system is considered in the application section.

The amount of distributed generators in power distribution systems is evermore increasing, and the potential benefits and drawbacks are becoming clearer. The optimal management of Distributed Energy Resources (DER) in microgrids is essential to guarantee their best exploitation. Optimal operation allows to maximize their benefits, such as reduction of network energy losses, reduction of carbon emissions and to minimize the negative effects of a strong DER penetration, such as the increase of infrastructural investment and operational costs. Hence, DER management is a multi-objective problem in which many objectives of interest, often conflicting, need to be optimized simultaneously. In this paper, the problem of the 24-hours unit commitment of distributed generators supplying a LV micro-grid connected to the main grid is addressed. The model developed considers the management of storage systems concentrated at some of the grid buses. The considered objectives are: to minimize generators annual cost, carbon emissions of the overall system and line losses. The unknowns are: the hourly power production of DER and the hourly storage unit level. The results show that the multi-objective approach based on non domination provides a wide range of alternatives and allows a strong optimization of the considered objectives.

This work develops a new double shell approach to optimal design for multi-objective optimally managed systems. The cost of each design solution can be defined by the evaluation of operational issues and capital costs. In most systems, the correct definition of operational issues can be deduced by means of the solution of a multi-objective optimization problem. The evaluation of each design solution must thus be deduced using the outcome of a multi-objective optimization run, namely a Pareto hyper-surface in the n-dimensional space of operational objectives. In the literature, the design problem is usually solved by considering a single objective formulation of the operational issue. In this paper, the proposed double shell approach is implemented using evolutionary computation and it is explained considering the problem of optimal microgrids design. For this problem the multiple operational impacts identification corresponds to the solution of the optimal unit commitment of generators. After an introductory part, the particular problem formulation is presented and an interesting application of the considered approach to a medium size micro-grid is shown.