Utility-scale Battery Energy Storage Systems Research Articles

Massively Parallel Modeling of Battery Energy Storage Systems for AC/DC Grid High-Performance Transient Simulation

Extensive integration of power electronics apparatuses complicates the modern power grid and consequently necessitates time-domain transients study for its planning and operation. In this work, a heterogeneous computing architecture utilizing the CPU and graphics processing unit (GPU) is proposed for the efficient study of interactions between a power grid network and massive utility-scale battery energy storage systems (BESSs). The device-level electromagnetic transient (EMT) simulation aiming at enhanced fidelity of the BESS is conducted simultaneously with electro-mechanical transient stability (TS) simulation which suffices system-level dynamic security assessment. Since the reservation of a large amount of energy storage units is computationally intensive for the CPU, the concurrent multi-streaming, multi-threading capability of GPU is exploited to achieve asynchronous sequential-parallel processing, so that the proposed EMT-TS co-simulation can flexibly harness all available computing resources. The multi-rate scheme is adopted for further computational burden alleviation in addition to achieving timely information exchange. It shows that the heterogeneous computation of an IEEE 118-bus system integrated with a substantial number of distributed batteries becomes feasible following the achievement of a remarkable speedup of over 200, and the device- as well as system-level accuracy are validated by MATLAB/Simulink^® and DSATools^TM/TSAT simulation, respectively.

Pack-level performance of electric vehicle batteries in second-life electricity grid energy services

Repurposed electric vehicle (EV) batteries can provide an affordable and sustainable alternative to conventional utility-scale battery energy storage systems. While EV battery packs are often disassembled into modules or cells and repackaged for second life, the required time and labour costs can be mitigated by directly repurposing full EV battery packs when their health allows. However, the diversity among EV battery pack designs introduces uncertainty regarding their relative performance in second-life applications. This study presents experimental data demonstrating the second-life performance of EV batteries from five different EV manufacturers, featuring four unique positive electrodes, three cell formats, and three thermal management designs. All five EV batteries are tested at the pack level in their original housings, providing thermal conditions distinct from module or cell testing. The batteries are tested under 4 h, 2 h, and 1 h deep-discharge constant-power duty cycles to emulate electricity grid energy services such as energy arbitrage or peak shaving. Novel methods are employed to measure, assess, and compare battery performance in this test regime. The results show significant performance differences among the five EV battery packs, particularly between older (2012–2015) and newer (2018–2019) designs due to evolutions in energy density and thermal management. The test results are analyzed and ranked, showing that among the five tested batteries, the 2019 Tesla Model 3 battery (tested with active-liquid cooling) will provide the best overall performance in most second-life energy storage applications, while the 2015 BMW i3 battery (tested with passive-air cooling) will provide the best profit margins in applications where energy losses must be minimized. The novel experimental dataset is used to derive a number of generalized conclusions and recommendations which can be used by researchers and industrial developers to inform the modelling and design of second-life energy storage systems.

Coordinated expansion planning of transmission and distribution systems integrated with smart grid technologies

Integration of smart grid technologies in distribution systems, particularly behind-the-meter initiatives, has a direct impact on transmission network planning. This paper develops a coordinated expansion planning of transmission and active distribution systems via a stochastic multistage mathematical programming model. In the transmission level, in addition to lines, sitting and sizing of utility-scale battery energy storage systems and wind power plants under renewable portfolio standard policy are planned. Switchable feeders and distributed generations are decision variables in the distribution level while the impact of demand response programs as a sort of behind-the-meter technologies is accommodated as well. Expansion of electric vehicle taxi charging stations is included as a feasible option in both transmission and distribution levels. In order to deal with short-term uncertainty of load demand, renewable energy sources output power, and the charging pattern of electric vehicle taxis in each station, a chronological time-period clustering algorithm along with Monte Carlo simulation is utilized. The proposed model is tackled by means of Benders Dual Decomposition (BDD) method. The IEEE RTS test system (as the transmission system) along with four IEEE 33-node test feeders (as distribution test systems) are examined to validate effectiveness of the proposed model.

Determinants of Residential Consumers’ Acceptance of a Utility-Scale Battery Energy Storage System in Malaysia: Technology Acceptance Model Theory from a Different Perspective

In a developing country such as Malaysia, studies of determinants which influence residential consumers of the Battery Energy Storage System (BESS) are limited. This paucity of studies was the catalyst for this study and its aim to investigate the factors affecting acceptance by Malaysian residential consumers of BESS as it relates to the Technology Acceptance Model Theory. A sample of 331 residential consumers indicated that consumer attitudes, social norms and self-efficacy, or the perception of behavioral control, had a positive and significant relationship with the intention to use BESS. Additionally, trust was a factor that had a significant effect on the consumers’ perceptions of cost, benefits and anticipated effects. All these variables significantly affect consumer attitudes. These findings provide important insights into BESS and facilitate the development of policies and practices relating to BESS in developing countries such as Malaysia.

Optimal Sizing of Grid-Scaled Battery with Consideration of Battery Installation and System Power-Generation Costs

Variable renewable energy (VRE) generation changes the shape of residual demand curves, contributing to the high operating costs of conventional generators. Moreover, the variable characteristics of VRE cause a mismatch between electricity demand and power generation, resulting in a greater expected energy not supplied (EENS) value. EENS involves an expected outage cost, which is one of the important components of power-generation costs. A utility-scale battery energy storage system (BESS) is popularly used to provide ancillary services to mitigate the VRE impact. The general BESS ancillary-service applications are as a spinning reserve, for regulation, and for ramping. A method to determine optimal sizing and the optimal daily-operation schedule of a grid-scale BESS (to compensate for the negative impacts of VRE in terms of operating costs, power-generation-reliability constraints, avoided expected-outage costs, and the installation cost of the BESS) is proposed in this paper. Moreover, the optimal BESS application at a specific time during the day can be selected. The method is based on a multiple-BESS-applications unit-commitment problem (MB-UC), which is solved by mixed-integer programming (MIP). The results show a different period for a BESS to operate at its best value in each application, and more benefits are found when operating the BESS in multiple applications.

Utility-Scale Storage Integration in the Maltese Medium-Voltage Distribution Network

Deployment of renewable energy sources in Malta is limited by grid integration constraints. Photovoltaic (PV) systems pose a significant risk to grid stability due to their inherent intermittency and result in overvoltages at the medium-voltage and low-voltage networks. Investments in utility-scale battery energy storage systems (BESS) will facilitate further deployment of renewables and will help to achieve energy security. This study proposed a novel sizing strategy for utility-scale battery energy storage systems (BESS) based only on technical considerations to find the minimum required storage capacity based on historical electricity demand and PV generation. The modeling and simulation were constrained to a section of the Gozitan 11 kV electrical distribution network and the results showed that the utility-scale storage can reduce the impact of PV systems on the grid infrastructure by avoiding reverse power flows and improve the local energy security by reducing the peak electricity demand. The central BESS and the decentralized coordinated BESS with “equal sizing” stored 3.4 MWh while the decentralized coordinated BESSs with “optimal sizing” stored 5.307 MWh. In all three cases, the evening peak demand was reduced by 30.5% from 2.62 MW down to a defined limit of 1.82 MW. From the results presented in this paper, the “optimal sizing” strategy showed that the BESSs have most benefit when installed next to the local PV generation. Hence, by deploying coordinated utility-scale BESSs sized according to the PV generation potential, it is expected that the penetrations of PV generation can be increased even with the present distribution network infrastructure.

Energy management of stationary hybrid battery energy storage systems using the example of a real-world 5 MW hybrid battery storage project in Germany

Utility-scale Battery Energy Storage Systems (BESS) are becoming increasingly important for the transition to large shares of renewable energy sources in the electricity grid. Hybrid battery storage systems are an interesting option to increase the profitability of BESS by combining low-cost battery technologies with more expensive, but also more efficient and robust ones. In theory, such a hybrid system can be cheaper than a single-technology system by leveraging synergy effects while still satisfying the requirements of a given application. An energy management system, which allocates the setpoint power of the BESS to the individual battery technologies, is crucial for taking advantage of the hybrid system layout. This paper details an analysis of different energy management algorithms for hybrid BESS using the example of a real-world project called M5BAT and compares the latter to alternative BESS layouts. Besides two heuristic algorithms, a non-predictive optimization and a predictive optimization are developed. Models comprising the electrical, thermal and aging behavior of the considered BESS components are introduced. Simulations of the operation of the BESS providing frequency containment reserve are conducted for determining the operating costs. The performance of the algorithms is evaluated based on the simulation results. Comparing the results shows significant differences in the operating costs between the algorithms, especially when optimized to reduce operating costs. The economic advantage of hybrid BESS is validated by additional simulations of a virtual hybrid BESS and a virtual single-technology BESS. Although the layout has not been optimized in terms of individual sizing of the different battery technologies, the hybrid BESS show a considerable advantage over the single-technology BESS.Highlights-Comparative study of energy management algorithms for power allocation in hybrid battery energy storage systems.-Development of heuristic power allocation algorithms and optimization approaches for cost-optimal operation.-Modeling of all relevant components and effects that contribute to the operating costs.-Simulations based on frequency-containment reserve operation of a real-world system.-Evaluation of the advantage of hybrid over mono-technology battery energy storage.

Consensus-based decision making approach for techno-economic operation of largescale battery energy storage in industrial microgrids

Utility-scale battery energy storage systems (BESSs) are emerging as an essential part of future power grids. A framework for the techno-economic application of a BESS in a dc coupled hybrid microgrid serving a mining industry is presented. Specifically, a multi-level consensus-based decision-making (MCD) approach is proposed for the energy management of the microgrid and the active/reactive power control of the microgrid's converters. The MCD can promote the operation of microgrids in the national electricity market as an economic unit. Also, the heterogeneous power curve of mining machines, the intermittency of renewables and the uncertainties of power systems can be addressed with reduced complexity. Whilst, the utility grid can apply and lead the regulatory parameters for the power system, as well as the microgrid, in accordance with the generator performance standards (GPS). A detailed electromagnetic transients (EMT) model is developed in PSCAD for a realistic test system and the effectiveness of the proposed MCD is pervasively assessed through different case studies. According to the assessed scenarios, the operational cost of the microgrid is decreased and the highly varying power curve of the renewables and mining industry is flattened. Further, the operational conditions of the microgrid can be autonomously controlled to mitigate unpredicted voltage disturbances, which can support the stability of power systems.

What drives capacity degradation in utility-scale battery energy storage systems? The impact of operating strategy and temperature in different grid applications

Battery energy storage systems (BESS) find increasing application in power grids to stabilise the grid frequency and time-shift renewable energy production. In this study, we analyse a 7.2 MW / 7.12 MWh utility-scale BESS operating in the German frequency regulation market and model the degradation processes in a semi-empirical way. Due to observing large temperature differences between the individual battery packs within a battery container, we include thermal effects in this model. In the analysed BESS the battery packs near the floor experience much lower temperatures in an annual average than the battery packs near the top (maximum average of 32 °C, minimum average of 23 °C). Operating in the Frequency Containment Reserve market, the annual capacity degradation differs up to 0.97% between the highest and lowest observed average temperatures. Hence, the BESS's lifetime could be extended by up to 11 years. Based on a detailed analysis of the BESS, we conclude that spatial temperature gradients within the battery containers are larger than expected and have a profound effect on lithium-ion battery ageing on system level. We extend this degradation model to study the technical potential of batteries in different energy market applications such as the day-ahead market with long periods of high charge and discharge rates (up to 1 h with a power to capacity ratio of 1 C) and the intraday market with volatile price spreads and therefore frequent and short periods (of up to 0.25 h) of high charge rates of up to 1 C. Our results suggest that the cooling system of energy storage systems needs to be carefully designed according to the intended application in order to control the temperature of the individual battery packs effectively. Slowing down ageing will be also beneficial for reusing 2nd life batteries stemming from a prior automotive application to extend the overall lifetime of such batteries.

Coordinating Distributed Energy Resources and Utility-Scale Battery Energy Storage System for Power Flexibility Provision Under Uncertainty

Relying on the power flexibility of distributed energy resources (DERs) located in an active distribution network (ADN), this ADN will be able to provide power flexibility to the upper-layer grid at their point of common coupling (PCC). The power flexibility is defined as additional bi-directional active/reactive powers a resource can provide to the grid by adjusting its operating point. In this context, this paper presents a two-stage ADN management method to deliver, at the PCC, the power flexibility that the upper-layer grid operator would request minutes-ahead real-time operation. The first stage updates the power set-points of DERs considering their offer curves as well as the uncertainties stem from the short-term forecast errors of demand and renewable generation profiles. The inter-temporal constraints and losses of the grid are accounted for by exploiting a linearized dynamic optimal power flow model, whereby the first stage is implemented as a linear scenario-based optimization problem. Then, in real-time operation, relying on a linear optimization problem, the second stage adjusts the power flexibility injection of a utility-scale battery energy storage system (ESS) to mitigate the imbalance at the PCC inherent in the above-mentioned uncertainties. The performance of the proposed method is tested in the case of a real ADN located in the city of Aigle in southwest of Switzerland.

Simultaneous Provision of Dynamic Active and Reactive Power Response From Utility-Scale Battery Energy Storage Systems in Weak Grids

Utility-scale battery energy storage system (BESS) technologies have huge potential to support system frequency in low-inertia conditions via fast frequency response (FFR) as well as system voltage via dynamic reactive power response. However, technical challenges may emerge in weak grids where low system strength could cause voltage instability, eventually potentially hindering provision of FFR too. This paper provides a systematic and comprehensive analysis of the challenges, and proposes relevant solutions, for BESS in providing FFR and general dynamic active and reactive responses under low system strength conditions. In particular, first we propose a constraint to describe the negative impact of low system strength on BESS phase-locked loop (PLL) stability and possible mitigation solutions. We then investigate the negative impact of large contingencies on BESS DC-link stability and active power control by introducing d-q current-power sensitivity factors and propose a solution based on reactive power prioritization that prevents converter-level instabilities while providing simultaneous active and reactive dynamic responses. Possible negative active/reactive power interactions due to BESS converter capacity constraints and the impact of the BESS operating point are also addressed. All these issues are investigated, and the proposed solutions tested, through explicit mathematical modelling as well as dynamic simulations of the South Australia's Eyre Peninsula weak grid.

Dynamic Modeling and Simulation of Non-Interconnected Systems under High-RES Penetration: The Madeira Island Case

The defossilization of power generation is a prerequisite goal in order to reduce greenhouse gas emissions and transit for a sustainable economy. Achieving this goal requires increasing the penetration of renewable energy sources (RESs) such as solar and wind power. The gradual shrinking of conventional generation units in an energy map introduces new challenges to the stability of power systems as there is a considerable reduction of stored rotational energy in the synchronous generators (SGs) and the capability to control their power output, which has been taken for granted until today. Inertia and primary reserve reduction have a substantial effect on the ability of the power system to maintain its security and self-resilience during contingency events. Such issues become more evident in the case of non-interconnected islands (NII) as they have unique features associated with their small size and low inertia. The present study examines in depth the NII system of Madeira, which is composed of thermal, hydro, solid-waste, wind and solar generation units, and additional RES integration is planned for the near future. Electromagnetic transient (EMT) simulations are performed for both the current and future states of the system, including the installation of planned variable RES capacities. To alleviate the stability issues that occurred in the high-RES scenario, the introduction of a utility-scale battery energy storage system (BESS), capable of mitigating the active power imbalance due to the power system’s disturbances resultant of RES penetration, is examined. In addition, a comparison between a flywheel energy storage system (FESS) and BESS is shortly investigated. The grid has been modeled and simulated utilizing the open-source, object-oriented modeling language Modelica. The dynamic simulation results proved that battery storage is a promising technology that can be a solution for transitioning to a sustainable power system, maintaining its self-resilience under severe disturbances such as rapid load changes, the tripping of generation units and short-circuits.

A data-driven approach to estimate battery cell temperature using a nonlinear autoregressive exogenous neural network model

Abstract Battery cell temperature is a key parameter in battery life degradation, safety, and dynamic performance. Intense charging-discharging operations and high-ambient temperatures escalate battery cell temperature, which in turn accelerates its degradation. Therefore, accurate battery cell temperature estimation can play a significant role in ensuring the optimal operation of a battery energy storage system (BESS). In order to estimate battery cell temperature as accurate as possible, use of non-linear models is imperative due to the non-linear nature of the battery operation. This paper proposes a data-driven model based on a Non-linear Autoregressive Exogenous (NARX) neural network to estimate battery cell temperatures in a utility-scale BESS, considering strongly-correlated independent variables, e.g., charging-discharging current and ambient temperature. Due to different temperature and weather characteristics in each season, seasonal NARX models have also been derived and compared with the universal one. The proposed models’ performance has been verified using the field data collected from a grid-connected BESS within a PV plant. The simulation results show high accuracy of the proposed model compared to the measured data for both seasonal and universal models without considering the complexity of the large-scale battery and container thermal dynamics. In particular, in more than 95% of the time, the estimated values yield root mean squared errors (RMSE) below 1 ∘C in different conditions, which confirms the validity and accuracy of the proposed model. Moreover, seasonal models show better performance with 18% to 50% less RMSE on average (for 1 h to 24 h forward estimation) compared to the universal model.

Optimal scheduling of mobile utility-scale battery energy storage systems in electric power distribution networks

Abstract Today, knowledge of battery energy storage systems (BESSs) has experienced a rapid growth resulting to the numerous grid applications. The utility-scale batteries assembled in containers can be transported in the grid. Despite numerous benefits, this feature has been overlooked. In previous studies, battery movement is modeled based on a specific transfer method, such as a truck or train. Accordingly, by changing the method of transporting the battery, the problem should be re-modeled and also it is not possible to schedule the battery movements by combining two transfer methods. In this context, this paper proposes a new battery movement scheduling in the distribution networks. To this end, optimal charging or discharging power in addition to the bus location will be determined for any time period of operation. In the proposed model, only distance between buses is important and how the battery is transferred is not important. accordingly, battery transfer may be performed using one transmission method, such as a truck or a combination of two methods (truck and train). Reactive power contribution by the battery, power losses and bus voltages of the network are also counted by maintaining linear structure of the model. This guarantees practical application of the formulation for the real-life distribution grids. Results of implementing the model on a test system indicate distinct superiority of the mobile BESS with respect to the stationary installations.

Parameter Identification for Cells, Modules, Racks, and Battery for Utility-Scale Energy Storage Systems

The equivalent circuit model for utility-scale battery energy storage systems (BESS) is beneficial for multiple applications including performance evaluation, safety assessments, and the development of accurate models for simulation studies. This paper evaluates and compares the performance of utility-scale equivalent circuit models developed at multiple sub-component levels, i.e. at the rack, module, and cell levels. This type of modeling is used to demonstrate that the equivalent circuit model for a reference cell, module, or rack of a BESS can be scaled to represent the entire battery system provided that the battery management system (BMS) is active and functional. Contrary to the rapid pulse discharge cycles employed in conventional cell parameter estimation approaches, the study proposes a new charge/discharge cycle for identifying the equivalent circuit parameters for utility-scale battery systems using equipment readily available at installation sites without the need for laboratory setups. Furthermore, a sensitivity analysis for classifying and quantifying the effect of each equivalent circuit parameter on the performance of the proposed battery system model was executed. The measurements and simulations are conducted for a 1MW/2MWh BESS testing facility located at the Louisville Gas and Electric and Kentucky Utilities (LG&E and KU) E.W. Brown generating plant. The results indicate that for the example utility-scale battery setup with an active BMS, the equivalent circuit model of either the cell, module, or rack can be scaled to represent the battery system with less than 1% average voltage error.

Energy efficiency evaluation of grid connection scenarios for stationary battery energy storage systems

The connection to the electrical grid is a key component of stationary battery energy storage systems. Utility-scale systems comprise of several power electronics units. Various grid connection topologies may be used, depending on the conversion stages within each unit, the load distribution between the power electronics and additionally the grid level to which the system is connected. The energy efficiency, which is a key performance indicator for storage systems, is compared between various scenarios. Detailed models are developed for the key components: The inverter/rectifier, the DC-DC converter, and the transformer. The respective model parameterization is based on state-of-art industry components and compared against experimental data. Two grid application scenarios, namely Primary Control Reserve and Secondary Control Reserve, are simulated for a comparison in reference application scenarios often discussed for utility-scale battery energy storage systems. Results show that grid connection setups without an intermediate DC link conversion stage are more efficient than those with. The optimum number of inverters in dependence on the actual load is determined. The connection to the low-voltage grid is more efficient due to the absence of the transformer which introduces significant additional losses. The topology models developed herein can be integrated into system models that include the overall systems or used for the design of novel battery systems grid connection topologies with detailed evaluation down to the component level.

Enhancing the dispatchability of distribution networks through utility-scale batteries and flexible demand

In this paper, the problem of dispatching the operation of a distribution feeder comprising a set of heterogeneous resources is investigated. The main objective is to track a power trajectory, called the dispatch plan, which is computed the day before the beginning of operation. In this paper, we propose a method to optimally compute the dispatch plan so as to optimize the operation of the feeder while making sure to allocate enough local reserves to absorb deviations of the realizations. Indeed, during real-time operation, due to the stochasticity of part of the resources in the feeder portfolio, tracking errors need to be absorbed in order to track the committed dispatch plan. This is achieved by modulating the power consumption of a utility-scale battery energy storage system and of the heating, ventilation and air conditioning system of a commercial controllable building. To this end, a hierarchical controller is designed to coordinate these two controllable entities while requiring a minimal communication infrastructure. Due to the inherent different response times of these systems, the power injection of the electrical battery is controlled at a sub-minute time-scale so as to absorb high-frequency tracking errors and, therefore, deliver the dispatch service. At a slower time-scale, the controllable building is controlled to maintain the state of charge for the electrical battery at a scheduled level by means of a model predictive controller. The model predictive controller is designed in order to account for both comfort and operational constraints of the controllable building, as well as power limits for the electrical storage.The effectiveness of the proposed control framework is demonstrated by means of both an extensive simulation analysis, as well as a set of 12 full day experimental results on the 20 kV distribution feeder in the campus of the Swiss institute of technology in Lausanne, that is comprised of: 1) A set of uncontrollable resources represented by five office buildings (350 kWp) and a roof-top photovoltaic installation (90 kWp), 2) a set of controllable resources, namely, a grid-connected electrical storage (720 kVA–500 kWh), and a fully-occupied multi-zone office building (45 kWp).

A Resilient Power System Operation Strategy Considering Transmission Line Attacks

Due to significant losses caused by attacks on power grids, mitigation of transmission line attacks has drawn increasing attention in recent years. It is crucial to develop solutions to mitigate these potential damages. Therefore, this paper presents a novel operational strategy aimed at minimizing unserved energy under the worst-case attack on transmission lines of a power system with generators and utility-scale battery energy storage systems (BESS). The paper formulates a tri-level optimization problem to model interactions between the operator and the attacker. The upper-level problem represents normal operational actions to hedge against potential attacks and minimize operating costs. Then, the middle-level problem determines the attack strategy, including both attack time and lines to be attacked, to maximize impacts to the grid. The lower-level problem models actions of operators during restoration process by minimizing unserved energy. Column-and-Constraint Generation (C&CG) method is applied to solve the problem. Numerical case studies are conducted to demonstrate advantages of the proposed model in unserved energy reduction under the worst-case transmission line attack.

A Review of Power Electronics for Grid Connection of Utility-Scale Battery Energy Storage Systems

The increasing penetration of renewable energy sources (RES) poses a major challenge to the operation of the electricity grid owing to the intermittent nature of their power output. The ability of utility-scale battery energy storage systems (BESS) to provide grid support and smooth the output of RES in combination with their decrease in cost has fueled research interest in this technology over the last couple of years. Power electronics (PE) is the key enabling technology for connecting utility-scale BESS to the medium-voltage grid. PE ensure energy is delivered while complying with grid codes and dispatch orders. Simultaneously, the PE must regulate the operating point of the batteries, thus for instance preventing overcharge of batteries. This paper presents a comprehensive review of PE topologies for utility BESS that have been proposed either within industry or the academic literature. Moreover, a comparison of the presently most commercially viable topologies is conducted in terms of estimated power conversion efficiency and relative cost.

Integration and Operation of Utility-Scale Battery Energy Storage Systems: the EPFL’s Experience

Abstract: The experimental integration and control of an utility-scale 720 kVA/500 kWh battery energy storage system (BESS) in the medium voltage network of the Swiss Federal Institute of Technology of Lausanne (EPFL) to achieve dispatched-by-design operation of a heterogeneous group of prosumers is discussed. The motivation for such an objective is twofold: (i) dispatching the operation of prosumers reduces the uncertainty associated with their operation, thus the amount of regulating power required to operate power systems, a key issue when considering large-scale integration of renewable energy; (ii) , the dispatch plan is built in order to satisfy a given design objective for the local network, such as congestion management, load levelling or economic optimization of the prosumers operation according to the electricity price. The proposed framework relies on a minimally invasive monitoring infrastructure, trying to maximize the effort on the use of data analytics to identify prediction models of the consumer behavior and BESS voltage dynamics for an efficient control policy.