Weak Massive Gravity

We find a new class of theories of massive gravity with five propagating degrees of freedom where only rotations are preserved. Our results are based on a non-perturbative and background-independent Hamiltonian analysis. In these theories the weak field approximation is well behaved and the static gravitational potential is typically screened \`a la Yukawa at large distances, while at short distances no vDVZ discontinuity is found and there is no need to rely on nonlinear effects to pass the solar system tests. The effective field theory analysis shows that the ultraviolet cutoff is (m M_PL)^1/2 ~ 1/\mu m, the highest possible. Thus, these theories can be studied in weak-field regime at all the phenomenologically interesting scales, and are candidates for a calculable large-distance modified gravity.Comment: 5 page

Cosmology in General Massive Gravity Theories

We study the cosmology of general massive gravity theories with five propagating degrees of freedom. This large class of theories includes both the case with a residual Lorentz invariance as the cases with simpler rotational invariance. We find that the existence of a nontrivial homogeneous FRW background, in addition to selecting the lorentz-breaking case, implies in general that perturbations around strict Minkowski or dS space are strongly coupled. The result is that dark energy can be naturally accounted for in massive gravity but its equation of state w_eff has to deviate from -1. We find indeed a relation between the strong coupling scale of perturbations and the deviation of w_eff from -1. Taking into account current limits on w_eff and submillimiter tests of the Newton's law as a limit on the possible strong coupling regime, we find that it is still possible to have a weakly coupled theory in a quasi dS background. Future experimental improvements may be used to predict w_eff in a weakly coupled massive gravity theoryComment: 15 page

Finite Energy of Black Holes in Massive Gravity

In GR the static gravitational potential of a self-gravitating body goes as 1/r at large distances and any slower decrease leads to infinity energy. We show that in a class of four-dimensional massive gravity theories there exists spherically symmetric solutions with finite total energy, featuring an asymptotic behavior slower than 1/r and generically of the form $r^\gamma$. This suggests that configurations with nonstandard asymptotics may well turn out to be physical. The effect is due to an extra field coupled only gravitationally, which allows for modifications of the static potential generated by matter, while counterbalancing the apparently infinite energy budget.Comment: 4 page

Smart inverter operation in distribution networks with high penetration of photovoltaic systems

With the growing number and capacity of photovoltaic (PV) installations connected to distribution networks, power quality issues related to voltage regulation are becoming relevant problems for power distribution companies and for PV owners. In many countries, like Italy, this has required the revision of the standards concerning the connection to the public distribution network of distributed renewable generation. The new standards require a flexible operation of generation plants that have to be capable to change the active and reactive power dynamically in function of the network parameters (i.e. frequency and network local voltage) in local control or following external commands. Therefore, this paper investigates the use of smart inverter in a critical PV installation, where relevant voltage fluctuations exist. A case study, with real network parameters monitoring data and measurements, is discussed in the paper with the aim of showing how 'smart' features of new inverters can be implemented to increase PV plant integration in low voltage distribution networks

Renewable Energy Communities in Positive Energy Districts: A Governance and Realisation Framework in Compliance with the Italian Regulation

Renewable energy communities, first outlined in the European Directives and recently transposed into the Italian regulatory framework, are introduced as innovative entities capable of fostering cooperation between active and passive users involved in the production, sharing, and use of locally produced energy according to innovative management schemes. Renewable energy communities empower the end-customers. Citizens and legal entities are committed to a rational and economical use of energy to achieve the community’s climate neutrality goals and pursue the ecological and energy transition objectives defined in the national recovery and resilience plan. In the future, a significant number of energy communities different actors participating from the residential, industrial, commercial, and tertiary sectors are expected to develop within city districts or in suburban settings. This paper proposes and develops a methodology capable of bridging the complexity that can characterise the prototyping, implementation, and management of an energy community within a positive energy district. The approach presented here can also be extended to other application contexts in urban or rural settings. Requirements and best practices for administrative, technical, and technological management have been identified to achieve this goal. Italy is one of the first states to embed in its regulatory framework the European Directives regarding renewable energy communities. These will have a significant impact on network management models and will provide new ways for creating social inclusion that may help achieve climate sustainability goals. A governance model has been formalised for the empowerment of energy community members, outlining a framework useful for planning the proper implementation of a renewable energy community according to current Italian regulations

Blockchain-Based Hardware-in-the-Loop Simulation of a Decentralized Controller for Local Energy Communities

The development of local energy communities observed in the last years requires the reorganization of energy consumption and production. In these newly considered energy systems, the commercial and technical decision processes should be decentralized in order to reduce their maintenance costs. This will be allowed by the progressive spreading of IoT systems capable of interacting with distributed energy resources, giving local sources the ability to be optimally coordinated in terms of network and energy management. In this context, this paper presents a decentralized controlling architecture that performs a wide spectrum of power system optimization procedures oriented to the local market management. The controller framework is based on a decentralized genetic algorithm. The manuscript describes the structure of the tool and its validation, considering an automated distributed resource scheduling for local energy markets. The simulation platform permits implementing the blockchain-based trading process and the automated distributed resource scheduling. The effectiveness of the tool proposed is discussed with a hardware-in-the-loop case study

Distribution energy storage investment prioritization with a real coded multi-objective genetic algorithm

Energy Storage Systems (ESSs) are progressively becoming an essential requisite for the upcoming Smart Distribution Systems thanks to the flexibility they introduce in the network operation. A rapid improvement in ESS technology efficiency has been seen, but not yet sufficient to drastically reduce the high investments associated. Thus, optimal planning and management of these devices are crucial to identify specific configurations that can justify ESSs installation. This consideration has motivated a strong interest of the researchers in this field that, however, have separately solved the optimal ESS location and the optimal ESS schedule. In the paper, a novel multi-objective approach is presented, based on the Non-dominated Sorted Genetic Algorithm - II integrated with a real codification that allows joining in a single optimization all the main features of an optimal ESS implementation project: siting, sizing and scheduling. The methodology has been tested on a real-size rural distribution network

Relieving Tensions on Battery Energy Sources Utilization among TSO, DSO, and Service Providers with Multi-Objective Optimization

The European strategic long-term vision underlined the importance of a smarter and flexible system for achieving net-zero greenhouse gas emissions by 2050. Distributed energy resources (DERs) could provide the required flexibility products. Distribution system operators (DSOs) cooperating with TSO (transmission system operators) are committed to procuring these flexibility products through market-based procedures. Among all DERs, battery energy storage systems (BESS) are a promising technology since they can be potentially exploited for a broad range of purposes. However, since their cost is still high, their size and location should be optimized with a view of maximizing the revenues for their owners. Intending to provide an instrument for the assessment of flexibility products to be shared between DSO and TSO to ensure a safe and secure operation of the system, the paper proposes a planning methodology based on the non-dominated sorting genetic algorithm-II (NSGA-II). Contrasting objectives, as the maximization of the BESS owners’ revenue and the minimization of the DSO risk inherent in the use of the innovative solutions, can be considered by identifying trade-off solutions. The proposed model is validated by applying the methodology to a real Italian medium voltage (MV) distribution network

Uncertainty Reduction on Flexibility Services Provision from DER by Resorting to DSO Storage Devices

Current trends in electrification of the final energy consumption and towards a massive electricity production from renewables are leading a revolution in the electric distribution system. Indeed, the traditional “fit & forget” planning approach used by Distributors would entail a huge amount of network investment. Therefore, for making these trends economically sustainable, the concept of Smart Distribution Network has been proposed, based on active management of the system and the exploitation of flexibility services provided by Distributed Energy Resources. However, the uncertainties associated to this innovation are holding its acceptance by utilities. For increasing their confidence, new risk-based planning tools are necessary, able to estimate the residual risk connected with each choice and identify solutions that can gradually lead to a full Smart Distribution Network implementation. Battery energy storage systems, owned and operated by Distributors, represent one of these solutions, since they can support the use of local flexibility services by covering part of the associated uncertainties. The paper presents a robust approach for the optimal exploitation of these flexibility services with a simultaneous optimal allocation of storage devices. For each solution, the residual risk is estimated, making this tool ready for its integration within a risk-based planning procedure