The promotion of electric mobility is a key objective of energy transition, and it is aimed at significantly reducing greenhouse gas emissions, with road transport being understood as a major contributor. Despite its potential, the adoption of electric vehicles (EVs) in logistics faces critical challenges, including limited battery range, charging time, and the availability of charging infrastructure. Moreover, deploying charging stations must be carefully coordinated with the public grid to ensure seamless integration. This paper proposes a novel methodology for the optimal design and management of EV fleets in logistics. Our approach introduces innovations such as leveraging self-produced electricity and incorporating time-varying energy prices that can be tailored to individual nodes. This marks an important step toward a comprehensive interdisciplinary framework that integrates technical solutions with public policy considerations. Through case studies, we explore how various parameters and resource distributions influence optimal decisions. The findings demonstrate significant potential for cost reduction and enhanced efficiency when applying this methodology to EV-based logistics, thereby offering actionable insights for advancing sustainable transportation.

With an increasing share of wind power generation, it is crucial to analyze its availability and effect on the reliability of power systems, to maintain a high level of security of supply. Moreover, since the annual generation can vary greatly, long term analysis is required. Thus, this study examined two independent methods for determining the capacity credit of wind power, considering a long period of 18 years. The first method was a time-period-based capacity credit which only considered wind power generation, and the second one a risk-based method, which analyzed the complete power system and its level of reliability. Moreover, with the risk-based method, the analysis considered different installed capacities for wind power and possible hydrogen storage coupled to the wind power. The results from the time-period-based capacity credit determined, that 8.8% and 3.1% of wind power capacity can be expected the be available with 90% and 98% confidence levels, respectively. In addition, with the risk-based method, the ratio between additional load that a system can supply by including wind power and installed wind capacity, decreased from 14.5% to 4.3% when the wind capacity was increased from 5.68 GW to 30 GW. Moreover, coupling an energy storage to the wind power generation improved its utilization and simultaneously the capacity credit by 2.6-4.6 percentage points. Furthermore, to obtain these results, wind power generation was modeled from 2004 to 2021.

This paper examines the challenges and opportunities in the European energy sector, with a particular focus on Italy, in light of the ongoing energy crisis and policies aimed at transitioning to renewable sources. Utilizing an optimization-based approach, the study analyzes innovative methodologies to manage the complexities of the current energy system. Specifically, it investigates the crucial role of communication between distribution system operators and renewable energy communities in maximizing mutual benefits and addressing the challenges posed by the energy crisis. The findings of this study could provide valuable insights for the development of effective energy policies, guiding the transition towards a more sustainable and efficient energy system in Europe.

In recent years, several factors, including the conversion of overhead feeders into cable lines and the spread of power electronics, have contributed to a significant change in the nature of distribution networks' loading. In the past, network equivalent capacitance was largely compensated by ohmic-inductive loads. Conversely, today most of the network operated by SET Distribuzione experiences an ohmic-capacitive behavior even when loaded, leading to undesired inductive power injections into the High Voltage National Transmission Grid. In this regard the present paper illustrates the compensation approach devised and implemented by SET Distribuzione. It consists in a combination of distributed shunt reactors to locally compensate the capacitive power absorption of cable branches and loads. Shunt reactors are installed either at the Medium Voltage side or at the Low Voltage side of some Secondary Substations. Simulations and field experience have proved this solution to be effective in providing valuable local reactive compensation, together with an improvement in voltage profile regulation and a remarkable reduction in the loading of feeder branches, with benefits in terms of network distribution losses.

In a context of ongoing energy transition in which distribution networks' end-users are not mere consumers anymore, a more accurate approach to study the power flows in such systems becomes vital, especially considering the intrinsic asymmetry and high percentage of single-phase users connected in the low voltage network. This paper, by addressing the main differences with the usually employed simplified approaches, presents a multi-conductor methodology for modelling electric power systems which can be adopted for the analysis of distribution networks. The proposed approach allows for a complete generalization of the network model, providing a detailed set of results which can be used for monitoring and controlling the distribution system.

Recent advances in the development of reconfigurable batteries pave the way for novel DC microgrid architectures that eliminate the need for DC–DC converters. The present study is focused on the control of a microgrid comprising a battery system with three reconfigurable strings to flexibly operate two electric vehicle (EV) fast chargers, a photovoltaic (PV) system, and a grid-tie inverter. The primary control tasks are to dynamically connect the individual battery strings to the other system components through a busbar matrix, and to manage the energy exchange with the AC grid. The paper formulates the control tasks as a mixed-integer linear optimization problem, virtually splitting the system into three parallel representations, each constructing the perspective of one battery string on the busbar matrix. The functionality of the proposed control is assessed through simulation scenarios using actual PV production and EV charging data of a prototype installed on the Danish island of Bornholm. To quantify the performance, the optimizer is compared with a heuristic control. Considering grid energy costs and revenues through EV charging, the optimal control increased the profit by 5.4% in the summer and 13.0% in the winter scenario, with respect to the benchmark control.

This analysis investigates the business case of a virtually aggregated unit with PV and Power-to-Gas, outlining the added value of enhanced operation modes for the deepened market integration of distributed energy resources in an aggregated form. Based on empirical generation and market data, the presented analysis outlines the added benefit of the so-called value stacking that considers the exploitation of short-term arbitrage opportunities, the provision of secondary and tertiary frequency reserve, and active imbalance management to balance forecast errors. A multi-stage and multi-period optimization approach is presented to generate an aggregated bidding strategy on multiple energy and ancillary service markets. On a case study basis with hourly resolution, annual energy flows and financial outcomes are derived for the modelled plant. Overall, nine different operating modes with different levels of market integration of the aggregated unit are analysed. While static baseline operation results barely profitable, proper integration into energy markets raises the annual cash flow from operating activities to around 60 k€ per aggregated MW. This six-fold increase is accompanied by a much more price-specific dispatch with the equivalent full-load hours of controllable output effectively dropping to about one-third. Integrating the aggregated unit further into balancing markets and performing active imbalance management leverages the freed-up capacity margin and further increases the operational results up to 150 k€ per MW. The provided empirical insights from the case study are beneficial for both practitioners in the energy sector that want to evaluate the potential value of virtual aggregation with enhanced operation and policymakers that consider further regulatory amendments to open markets and enable further integration of new energy sources.

Battery energy storage systems (BESSs) are known as a potential solution to integrate renewables and electric vehicle (EV) charging in the power system. This article compares the direct grid installation of ultra-fast chargers (UFCs) with a hybrid system inclusive of a reconfigurable BESS, a photovoltaic (PV) unit, two UFCs and a grid connection. The hybrid system is simulated with an optimization model, which reveals that the overall efficiency of the system plays a major role in determining the power grid exchange. Results show that the hybrid system can increase the local PV consumption while reducing the grid impact of EV charging. Based on yearly results, the hybrid system shows potential for further improving the utilization of the BESS and unlocking new revenue streams.

This analysis investigates the business case of a virtually aggregated unit with PV and power-to-gas, outlining the added value of enhanced operation modes for the integration of distributed energy resources.Such an aggregated unit can not only leverage the internal benefits of acting as a single unit, for example, by reducing imbalance errors and respective payments but also by offering a larger variety of products and services to the system than each unit could offer individually.Based on empirical generation and market data, the presented analysis outlines the added benefit of the socalled value stacking implementing the balance of forecast errors, the exploitation of short-term arbitrage opportunities, and the provision of secondary and tertiary frequency reserve.A multi-stage and multiperiod optimization approach is presented to generate an aggregated bidding strategy on multiple energy and ancillary service markets.On the one hand, the results highlight the value of individual operation modes for the plant and, on the other hand, the aggregated benefit of value stacking with multiple combined operating modes.The provided empirical insights are beneficial for both potential investing parties that want to evaluate the potential value of combined plants and policymakers that consider further regulatory amendments to open markets and enable further integration of new energy sources.

The paper considers different market settings for the participation to the balancing services market of small scale variable renewable energy sources connected to the distribution grid. By mixing an economical and a technical approach, it evaluates the efficiency of participation to the market under two distinct approaches to resources' aggregation: a commercial scheme and a technical one. In the former, the supply of the small scale variable distributed renewable energy sources is grouped on a purely commercial basis; in the latter, the distribution system operator is responsible of the imbalances that may possibly arise in the distribution grid and aggregates the sources from a technical perspective. By considering a reference distribution network and designing scenarios for the forecast uncertainty about supply and demand of power profiles, the impact of different market frameworks is assessed. The upward and downward balancing services provided by variable distributed energy resources and controllable units connected to the high voltage grid are both considered. Moreover, the power supply curtailments, that endogenously arise due to the violation of technical constraints of the distribution grid and the random nature of energy supply by renewables, are addressed, for each specific market model. As a general outcome of this research, it is shown that providing balancing energy based on a commercial approach is preferable as long as renewables' curtailment penalty is low and local generators have correlated forecast errors (as in the case of photovoltaic units) with a large reserve capacity. High penalties for curtailment and lower correlation among generation schedule deviations, along with a lower reserve by distributed units, make the technical approach more convenient.

The continuous increase of Renewable Energy Sources (RESs) connected to distribution networks requires a careful review of the current regulatory framework to enable the provision of Ancillary Services (ASs) by these small-scale units. One of the envisaged options for coordinating Transmission System Operators (TSOs) and Distribution System Operators (DSOs) is the agreement and regulation of a scheduled power profile at the Primary Substation (PS). This means assigning the balancing responsibility to DSOs and, consequently, reducing the unpredictability of the power exchanges with the upstream transmission grid. The paper proposes a novel procedure for the management of Distributed Energy Storages (DESs) in order to provide ASs to both the DSO (local regulation of distribution network and congestion management) and the TSO (control of the power profile at the PS). The methodology, based on a sliding time window approach, evaluates the actual availability of each storage unit in providing ASs, assigns a scheduled profile and corrects it during the real-time operation. In addition, for each DES, the scheduled State of Charge (SoC) is restored in accordance with network constraints. Simulations on a realistic case study network are carried out considering randomly perturbed power profiles for both loads and generators. Benefits associated with storage coordination (power exchange management at the PS and support to DSO in voltage regulation and congestion resolution) are evaluated and discussed.

In light of the advancing energy transition and an increasing amount of intermittent renewable energy to be integrated, flexibility from distributed energy resources will be key. In this paper, the Italian UVAM (Unità Virtuali Abilitate Miste, i.e., virtually aggregated mixed units) project, one of the biggest pilots in Europe to serve this purpose, is critically reviewed and mapped after two years of operation. The pilot is analyzed on a global level as well as the individual participant level. Based on the extensive analysis of actual market data, different strategies of participating companies to obtain capacity in accordance with the pilot project’s design are identified. Furthermore, the specific bidding strategies of individual participating units on the balancing market are outlined. Alongside this, the overall pilot project’s market integration, in terms of offered and accepted bids, is depicted. The thorough data analysis, therefore, serves as an input and fundamental building block for future electricity market modeling. Comprehending specific data from the coronavirus disease 2019 (COVID-19) pandemic, provides insights for future high renewable-energy scenarios. Based on the analysis findings, valuable deliverables are devised for both policy-makers and decision-makers who aim to leverage the flexibility potential of distributed resources.

The diffusion of distributed energy resources in distribution networks requires new approaches to exploit the users' capabilities of providing ancillary services. Of particular interest will be the coordination of microgrids operating as an aggregate of demand and supply units. This work reports a model predictive control (MPC) application in microgrids for the efficient energy management of energy storage systems and photovoltaic units. The MPC minimizes the economic cost of aggregate prosumers into a prediction horizon by forecasting generation and absorption profiles. The MPC is compared in realistic conditions with a heuristic strategy that acts in a instant manner, without taking into account signals prediction. The work aims at investigating the effect that different types of energy tariffs have in enhancing the end-users' flexibility, based on three examples of currently applied tariffs, comparing the two storage control modes. The MPC always achieves a better solution than the heuristic approach in all considered scenarios from the cost minimization point of view, with an improvement that is amplified by increasing the energy price variations between peak and off-peak periods. Furthermore, the MPC approach provides a cost saving when compared to the case considering a microgrid endowed with only photovoltaic units, in which no storage is installed. Findings in this work confirm that storage units better perform when some knowledge of future demand and supply trends is provided, ensuring an economic cost saving and an important service for the overall community.

With the increase of the distributed generation, the development of distribution networks able to operate detached from the bulk grid has become possible. However, these islanded distribution networks lead to several issues to be dealt with, including the stability, the efficient generation profile scheduling and the procurement of balancing services. This paper proposes an optimal network management scheme capable of obtaining the power profiles of all users connected to the network for a given time frame. This scheme, based on a double negotiation phase, aims to minimize the social cost for the coverage of the overall demand, keeping the network within its technical operating limits. The impact of Multi-Energy Storage Systems (MESS) in the cost of providing these services is assessed by considering the technical limits of the specific users. Finally, the proposed control scheme has been tested on four different scenarios, with increasing MESS penetration level, demonstrating to be able to reduce the social cost associated with the re-dispatching by exploiting the services offered by the Battery and Thermal Energy Storage Systems.

The increasing focus on the active participation of low-voltage (LV) active distribution networks (DNs) in electricity markets requires the real-time optimal control of these DNs. To achieve this goal, a cheap semi-definite programming (SDP)-based optimal power flow (OPF) model for active neutral-equipped DNs, hosting both wye- and delta-connected loads, is proposed in this paper, aiming at overcoming the high computational requirement of the primal SDP-based OPF model. The coupled power injections between conductors are explicitly represented for each conductor by utilizing the network admittance matrix-based approach. Furthermore, three novel propositions (P1, P2 and P3) are proposed for the modelling of the constant current component of ZIP end-users in the context of the proposed OPF model. Moreover, the impact of the voltage-angle deviation on the exactness of the P1- and P2-based models is discussed. Simulations are carried out on several LV active DNs for various parameters of ZIP end-users, and the quality of the proposed OPF model is verified through the % optimality gap, power mismatch, voltage violation and root-mean-square error criteria. It is successfully shown that the proposed OPF model provides an optimal and feasible solution for all load types (wye, delta, mixed wye-delta) under a large range of ZIP load parameters. Furthermore, among the three propositions, the P3-based OPF model appears to be the most accurate in terms of determining an optimal and feasible solution. Finally, the reduced computational time of the cheap conic model allows its real-time implementation for medium- and large-sized DNs for which the primal multi-phase SDP-based model is practically difficulty to realize.

A novel optimal PhotoVoltaic (PV) inverter dispatch scheme is proposed in this paper which combines the active power curtailment and reactive power control schemes in order to simultaneously determine the optimal active and reactive power set points of residential PVs. The non-convexity of resultant AC optimal power flow model, caused by the inherent power balance constraints and selective inclusion of PV systems through binary variables, is handled by leveraging the cheap semi-definiteprogramming and sparsity-promoting-regularization approaches. The application of proposed methodology on a low-voltage test distribution network shows that recurrent technical issues of these networks such as voltage rise and voltage unbalance can be successfully mitigated as well as significant reduction in active power losses can also be achieved.

Losses allocation, being a purely economical problem, demands a fair allocation procedure that can distribute the losses in an impartial manner by avoiding cross-subsidies among end users. In view of this, a novel multi-phase losses allocation methodology is proposed, which fairly segregates the losses associated with cross-terms of phase-currents and also provides an explicit information about losses allocated to the neutral. The effect of phase loading on another phase is comprehensively taken into consideration while distributing losses among end users. Furthermore, allocation of neutral losses to each phase of a node is avoided as these losses exist in a system due to its inherent characteristics. Quadratic and geometric losses partitioning approaches have been utilized to determine the share of losses between phase currents of same and different nodes. The methodology is implemented on a modified IEEE 13-node test system in the presence of distributed generators and results show that the proposed scheme leads to a more fair penalization and reward of passive and active end users as compared to the resistive component based losses allocation method. In addition to this, concept of neutral losses allocation factor along with their possible application in the management of distribution network has also been discussed briefly.

Semi-Definite Programming (SDP) and Second Order Cone Programming (SOCP) relaxations are state-of-the-art lift-and-project based techniques for solving the non-convex AC optimal power flow problem in multi-phase active distribution networks. A novel centralized Quadratic Convex (QC) relaxation for such networks, which is a significant departure from the lift-and-project based approaches, is developed in this paper. The proposed scheme encloses the non-convex region, associated with the non-linear terms of power flow equations represented in the polar form, by appropriate convex envelopes. The envelopes for the trigonometric terms are based upon the first order Taylor series approximation and cosecant/secant functions, whereas bilinear terms are enclosed by McCormick envelopes. Furthermore, appropriate bounds on the lifted variables are also introduced and the trilinear function is enclosed by the recursive application of the McCormick envelope. The application of the proposed scheme on several test cases reveals that it outperforms SOCP in all the cases and is close to the SDP relaxation. Furthermore, it has also shown to have high computational efficiency as compared to the SDP approach due to the existence of mature solving technology for quadratically constrained problems.