Photovoltaic Battery Storage Systems Research Articles

Open-Access Model of a PV–BESS System: Quantifying Power and Energy Exchange for Peak-Shaving and Self Consumption Applications

Energy storage is vital for a future where energy generation transitions from a fossil fuels-based one to an energy system that relies heavily on clean energy sources such as photovoltaic (PV) solar energy. To foster this transition, engineers and practitioners must have open-access models of PV systems coupled with battery storage systems (BESS). These models are fundamental to quantifying their economic and technical merits during the design phase. This paper contributes in this direction by carefully describing a model that accurately represents the power directions and energy dealings between the PV modules, the battery pack, and the loads. Moreover, the general model can be implemented using two different PV generation methods, the Gaussian model and the meteorological data-based model (MDB). We found that the MDB model is more appropriate for short-term analysis compared to the Gaussian model, while for long-term studies, the Gaussian model is closer to measured data. Moreover, the proposed model can reproduce two different energy management strategies: peak-shaving and maximizing self-consumption, allowing them to be used during PV–BESS sizing stages. Furthermore, the results obtained by the simulation are closed when compared to a real grid-tied PV–BESS, demonstrating the model’s validity.

A smart control for self-reliant single-phase, grid-tied photovoltaic-battery storage system

This paper presents a grid-tied, solar energy conversion-battery energy storage (BES) system with an autonomous control method for critical load applications. In order to improve grid current dynamics and ensure that balance power is exchanged as an active power with utility, direct current management of the voltage source converter utilizes least mean fourth method. The intermittent nature of solar photovoltaics also affects dynamics and power quality of grid current. A potential solution to such a situation evolves by using a bi-directional, DC/DC converter which interfaces an optimized-sized BES system with a DC link. Dual-loop DC/DC converter control keeps BES system charging and discharging current within pre-set limits and also simultaneously regulates DC link voltage. State-of-charge control gets incorporated through a dual-loop control to prevent BES from overcharging/deep-discharging. Dual-loop voltage control with harmonic compensation is used to manage load voltage amplitude and frequency in islanded mode. Auto-grid synchronization is realized by using a first-order, frequency-locked loop (FLL) technique. Using FLL also reduces dc offset, harmonics, and inter-harmonics even in distorted grid circumstances. The presented investigation also proposes a step-by-step controller parameter design procedure based on the frequency domain stability restrictions. Experimental results using OPAL RT-5600 validate the expected system response.

Efficiency characterization of 26 residential photovoltaic battery storage systems

Numerous loss mechanisms contribute to the overall performance of stationary battery storage systems. From an economic and ecological point of view, these systems should be highly efficient. This paper presents the performance characteristics of 26 commercially available residential photovoltaic (PV) battery systems derived from laboratory tests. They were measured according to the efficiency guideline for PV storage systems. Nine AC-coupled and 17 DC-coupled lithium-ion battery systems are compared. Their measured usable energy content varies between 5.8 kWh and 16.7 kWh and is in some cases more than 19 % below the specifications in the data sheets. Besides the usable capacity, the nominal power and the efficiency of the power conversion system are analyzed. DC-coupled PV storage systems are often advertised with inherently higher efficiency compared to AC-coupled systems. However, the comparison shows that they depend on high battery voltages of several hundred volts in order to exploit their efficiency advantages. The most efficient systems achieve average conversion path efficiencies of more than 97 %. In contrast, the values of the least efficient systems evaluated are only 90 %. Furthermore, the paper analyzes the control behavior by comparing the dead and settling times as well as the stationary control deviations of the investigated systems. Differences in the dead time of almost 3 s and in the settling time of more than 13 s can be observed. In addition, the AC, DC and peripheral power consumption in the fully charged and discharged state are evaluated. While individual systems have an outstanding power consumption of less than 4 W in the standby mode, others consume more than 70 W. The paper shows that various systems still have potential for optimization, especially in terms of conversion efficiency and standby losses. When selecting or optimizing a PV battery system, it is important to consider all loss categories to achieve high overall efficiency.

An Enhancement of Power Quality With Efficient Active Power Transfer Capability in a PV–BSS-Fed UAPF for Microgrid Realization

This article investigates the enhancement of power quality with an efficient active power transfer capability in a universal active power filter (UAPF) integrated with a photovoltaic (PV) and battery storage system (BSS). The UAPF operates as a bidirectional interface between the PV–BSS and point of interconnection for microgrid realization. A new control strategy is proposed to extract fast and accurate voltage and current reference signals to operate the system in a desired manner. Here, the extraction of load voltages and calculation of load and reference powers are used to generate the reference signals, thereby comparing with actual signals with hysteresis controller to produce switching pulses of converters. As a result, the shunt and series converters form a robust system by acting as a current-controlled voltage source and voltage-controlled current source, respectively. It eliminates the need for adaptive filters and low-pass filters to extract the fundamental component of the load current. Furthermore, it increases the conversion efficiency of converters and improves the static and dynamic performance of the system. The proposed system is developed with a 1-kVA prototype laboratory setup using a field-programmable gate array controller and extensively tested with various test conditions such as grid voltage fluctuations, nonlinear and imbalanced load, and change in irradiance.

Minimizing Energy Cost in PV Battery Storage Systems Using Reinforcement Learning

This article addresses the development and tuning of an energy management for a photovoltaic (PV) battery storage system for the cost-optimized use of PV energy using of reinforcement learning (RL). An energy management concept based on the Proximal Policy Optimization algorithm in combination with recurrent Long Short-Term Memory neural networks is developed for data-based policy learning. As a reference system for the simulation-based investigations, a PV battery storage system is modelled, parametrized and implemented with an interface for the RL algorithm. To demonstrate the generalization capability of the learned energy management, 98 training and 12 evaluation episodes, each with a length of one year, are generated from an empirical dataset of global radiation and load power time series. To improve the convergence speed and stability of the RL algorithm as well as the learned policy with regards to techno-economic metrics, an extensive hyperparameter study is conducted by training 216 control policies with different hyperparameter configurations. Simulation-based benchmark tests of the learned energy management against conventional rule-based and model-predictive energy managements show that the RL-based concept can achieve slightly better results in terms of energy costs and the amount of energy fed into the grid than the commonly used model-predictive method.

Coyote optimization algorithm for optimal allocation of interline –Photovoltaic battery storage system in islanded electrical distribution network considering EV load penetration

In current times, there is a need to do power system planning to endure situations of any kind. An islanding operation is one such unavoidable situation that may be required in many cases for both technical and economic reasons. First and foremost, this paper focuses on the determination of the best allotment of Interline-Photovoltaic (I-PV) system as per Electric Vehicle (EV) load penetration in the network. With different operational constraints, a multi-objective optimization using real power loss and voltage deviation index is formulated and solved using the Coyote Optimization Algorithm (COA).The paper highlights the computational efficiency of COA with Particle Swarm Optimization (PSO) and Grey Wolf Optimizer (GWO), in addition to various literary works, and the results suggest the superiority of COA by its global optima. The required battery energy storage system (BESS) capacity for supplying an islanded network's entire load demand for a day is determined in the second stage. The simulations were carried out on the IEEE 33-bus electrical distribution network (EDN) contemplating different levels of EV load penetration. The proposed methodology results have proved that the required energy is provided by optimal I-PV-BESS backup for a daylong islanding operation and its adaptability for practical situations.

A novel methodology for optimal sizing photovoltaic-battery systems in smart homes considering grid outages and demand response

–This paper deals with the optimal sizing of a hybrid photovoltaic-battery storage system for home energy management considering reliability against grid outages and demand response. To that end, a novel optimization framework is developed which aims at minimizing the electricity bill while the reliability of the system is ensured for certain common outages. In order to ensure the accuracy of the results, a large amount of characteristic outages along with demand, solar irradiance and temperature profiles are generated from real data. Clustering techniques are used for reducing this data to those most characteristics profiles and manage with the unpredictable behaviour of the outage events. Demand response is incorporated via different incentives like tariffs based on time of use and real time pricing, along with the optimal scheduling of different typical deferrable appliances. A case study on a smart-prosumer environment serves to illustrate the capabilities of the developed approach as providing sufficient guidelines for its universal applicability. Different cases studies are simulated considering different battery technologies and electricity tariffs for comparison. Various aspects related with the reliability against grid outages are also analysed like its impact on the project cost or the influence of demand response strategies.

Getting Prices for Prosumers Right? Incentivizing Investment and Operation of Small-scale PV-Battery Storage Systems Through Prices, Charges and Levies

We assess how the design of retail prices, grid fees and levies for household prosumers affects the attractiveness and resulting operation of small-scale photovoltaic battery storage systems (PVBSS), using a detailed modeling approach applied to a case study of six households in Germany. The selected pricing schemes and reform proposals are evaluated regarding the investment attractiveness for the prosumer and the impact on system-oriented operation, considering both market and grid integration. We show that the current business models for PV and PVBSS are only exist because they are based on avoiding the need to purchase electricity from the grid and thus avoiding paying taxes and levies on consumed electricity. Introducing time-variable pricing schemes or price components increase the value of PVBSS for the customer and the market, but lead to a less grid-friendly operation. It is shown that the term “system-oriented operation” should be defined carefully, since under the analyzed incentives, the two objectives included in system-oriented operation (market and grid integration) do not necessarily go hand in hand, sometimes even contradicting one another. Both the tariff design and the design of single tariff components have a considerable impact on the attractiveness and the resulting system integration of PVBSS and should be evaluated thoroughly to avoid unintended outcomes.

Deep-Reinforcement-Learning-Based Capacity Scheduling for PV-Battery Storage System

Investor-owned photovoltaic-battery storage systems (PV-BSS) can gain revenue by providing stacked services, including PV charging and frequency regulation, and by performing energy arbitrage. Capacity scheduling (CS) is a crucial component of PV-BSS energy management, aiming to ensure the secure and economic operation of the PV-BSS. This article proposes a Proximal Policy Optimization (PPO)-based deep reinforcement learning (DRL) agent to perform the CS of PV-BSS. Unlike previous work that uses value-based methods with the discrete action space, PPO can readily handle continuous action space and determine the specific amount of charging/discharging. To enforce the safety constraints of BSS’s energy and power capacity, a safety control algorithm using a serial strategy is proposed to cooperate with the PPO agent. The PPO agent can exploit the capacity of BSS safely while maximizing the accumulated net revenue. After training, the PPO agent can adapt to the highly uncertain and volatile market signals and PV generation profiles. The efficacy of the proposed CS scheme is substantiated by using real market data. The comparative results demonstrate that the PPO agent outperforms the Deep Deterministic Policy Gradient agent, Advantage Actor-Critic agent, and Double Deep Q Network agent in terms of profitability and sample efficiency.

Providing frequency control reserve with photovoltaic battery energy storage systems and power-to-heat coupling

The number of households with photovoltaic battery storage systems is steadily growing, and so is the number of heat pump installations. An integrated home combines domestic battery systems and a heat pump for power-to-heat coupling. During winter, storage systems in an integrated home are not used to their full capacity due to low solar radiation. This potential can be used to enhance the economics by applying a dual-use scheme. In this publication, an integrated home that participates in the frequency control reserve market is investigated.A major advantage of integrated homes with power-to-heat coupling in comparison to standalone battery storages is the additional flexibility to absorb negative control reserve power in the heating sector. Seasonal variation of feed-in from photovoltaics is considered by an advanced strategy for variable provision of control reserve.Results show that a dual-use operation with participation in the control reserve market can increase the profitability of storage systems. Market participation leads to accelerated battery aging, mainly driven by increased calendar aging. This is overcompensated by the possible incomes. Under consideration of low costs for market participation, a constant provision of at least 3 kW of reserve power could be economical. A variable provision further enhances economic efficiency.

Evaluation of the effects of frequency restoration reserves market participation with photovoltaic battery energy storage systems and power-to-heat coupling

In central Europe, the number of photovoltaic battery storage systems is steadily growing. Combined with a heat pump for power-to-heat coupling, these storage systems can contribute to sector coupling and increase the use of renewable energies in private households. The growing share of renewable energies leads to further fluctuations in the grid and a growing demand for reserve power. Integrated homes that combine a photovoltaic battery storage system with power-to-heat coupling can contribute to providing control reserve. The frequency restoration reserve in central Europe is divided into a negative and a positive reserve market, enabling market opportunities for integrated homes. Integrated homes participating in the negative frequency restoration reserve market could benefit from energy at low costs. Therefore, integrated homes profit from the additional flexibility provided by the heating sector. Low-cost energy from dual-use operation could lead to enhanced economics of integrated homes, especially during the winter.This paper presents the calculation of the marginal costs and savings for the market participation and the resulting economic influence on integrated homes. Costs for additional battery aging, as well as savings for reduced domestic energy consumption from the grid and an enhanced feed-in, are taken into account. The results show that participation in the German frequency restoration reserve market could reduce the annual costs for heat and electricity of integrated homes by up to 14.5%. A dual-use operation could be beneficial for integrated homes and enhance their market penetration.

How the Design of Retail Prices, Network Charges, and Levies Affects Profitability and Operation of Small-Scale PV-Battery Storage Systems

We assess how the design of retail prices, network charges and levies for household prosumers affect the attractiveness and resulting operation of small-scale photovoltaic battery storage systems (PVBSS), using a detailed modeling approach applied to a case study of six households in Germany. The selected pricing schemes and reform proposals are evaluated regarding the investment attractiveness for the prosumer and the impact on system-oriented operation, considering both market and grid integration. We show that currently the business case for PV as well as PVBSS only exists since it allows avoiding grid offtake and thus avoiding paying taxes and levies on consumed electricity. Introducing time-variable pricing schemes or price components increases the value of PVBSS for the customer and the market, but leads to less grid-friendly operation. It is shown that the term “system-oriented operation” should be defined carefully since market value and grid-friendly operation do not necessarily go hand in hand so that one incentive cannot inherently contribute to both objectives at the same time. The tariff design, as well as the design of single tariff components have a considerable impact on the attractiveness and the resulting system integration of PVBSS and should be evaluated thoroughly to avoid unintended outcomes.

Strategic decision making of distribution network operators and investors in residential photovoltaic battery storage systems

As the adoption of combined photovoltaic (PV) systems and battery storage systems (BSSs) for residential buildings increases, challenges for distribution network operators (DNOs) arise. Part of the attractiveness of investing in such systems stems from avoiding paying grid charges (GCs). Yet, the systems rely on the grid for PV feed-in and possibly contribute to PV grid integration challenges. Here, a bilevel optimization approach is developed to evaluate interdependencies between the DNO’s decision of raising GCs and the reaction of PV BSS investors. The model allows DNOs to trade-off the effectiveness of different measures to foster PV grid integration and the danger of starting a self-reinforcing process, potentially leading to grid defection. Included are two case studies that show that the new equilibrium between DNO and PV BSSs comes at a price of raised GCs and larger PV system sizes. Yet, in either case study, grid defection is not a realistic scenario as the marginal value of additional self-supply decreases with higher GCs. Compared to PV curtailment by the DNO, or grid reinforcements, fixed feed-in limits and power-based GCs reduce oversizing of PV BSSs and provide an operational incentive for peak-oriented BSS operation.

Interdependencies between self-sufficiency preferences, techno-economic drivers for investment decisions and grid integration of residential PV storage systems

The business case for residential photovoltaic (PV) systems in combination with battery storage systems (BSSs) is thriving in Germany. Next to an increasing spread between electricity prices and feed-in tariffs (FITs), the adoption of PV BSSs is fostered by a preference for higher self-sufficiency and a federal investment incentive for PV BSSs. Such an incentive subsidizes BSSs on the promise of facilitating PV grid integration. However, so far a comprehensive analysis of implications of self-sufficiency desire and investment incentive for PV BSS sizing and operation and their grid integration is missing. To enable the key stakeholders – PV BSS investors, distribution network operators and policy makers – to derive a better understanding of the underlying interdependencies between these drivers and the corresponding sizing and operation of PV BSSs, an optimization model is developed. The model includes all relevant cash flows for the business case of PV BSSs, e.g. surcharges on PV self-consumption, and an approach for adopting preferences for self-sufficiency. A case study-based analysis shows that the desire for self-sufficiency and the BSS investment incentive lead to larger PV systems. From a PV grid integration perspective, a grid-supporting BSS operation is contradicted by larger system sizes fostered by the investment incentive and self-sufficiency desires. Imposing stricter feed-in limits and adjusting the residential PV support mechanism entail chances to enable larger PV systems sizes while also limiting their grid impact.

The off-grid PV-battery powered home revisited; the effects of high efficiency air-conditioning and load shifting

The potential for residential households to go ‘off-grid’ with a photovoltaic-battery storage system in a location where a conventional connection to the electricity network is available has received recent attention. Several studies have reported that at present, in Australia the economics are not justified. These studies have used unmodified electricity consumption profiles from grid-connected households as input to their off-grid system analyses. However, households looking to go off-grid may be motivated to make basic modifications to their consumption pattern so as to minimise the size of the PV-battery system. Here the effects of (i) shifting the booster time of electric storage hot water system to coincide with peak irradiance, (ii) improving the efficiency of air-conditioning appliances, and (iii) shifting pool pump operation and improving pump efficiency are compared and assessed. The analysis uses sub-circuit measurements of electricity consumption from 28 households for up to 2 years. Results show that the hot water and air-conditioning adjustments in particular can improve the economics considerably, even accounting for the fact that the appliance efficiency improvements also lower the grid connected electricity costs. For households seeking to go off-grid, any changes to electricity load profiles that provide a more uniform match of consumption to generation in particular, improve off-grid system economics in comparison to grid electricity, since the true cost of delivering electricity from the grid at peak times is typically spread across all consumers.

Techno-economic analysis of photovoltaic battery system configuration and location☆

The techno-economic analysis investigates first the impact of tilt angle and orientation on the production profile of a rooftop solar generator and the related performance of a photovoltaic battery storage system for single family houses at a specific location in Germany. Then, a technical comparison to a different location in Almeria in Spain is performed.The calculations are model-based and take into consideration the consumer load profile, technical and economic photovoltaic battery storage system parameters as well as the framework of regulations for the case of Germany. The parameters “share of self-consumption”, “degree of autarky”, and “economic efficiency in terms of levelized cost of electricity” make up the focus of the modelling results. It is concluded that self-consumption and degree of autarky are strongly and inversely related. In terms of system design, a trade-off has to be made between aiming for high self-consumption and a high degree of autarky.Key findings from the modelling results reveal that in Lindenberg in Germany, a south orientation gives the highest degree of autarky and the lowest levelized cost of electricity, but with the lowest share of self-consumption as well. For rooftops oriented towards east/west, an interesting possibility could be to split the total installed capacity (equally) between the two orientations. This makes it possible to benefit from the high self-consumption of the east orientation and the high degree of autarky of the west orientation. In general, it has to be considered that the optimum orientation strongly depends on the consumer load profile. The technical analysis shows that changing the location to Almeria increases degree of autarky and decreases share of self-consumption for south orientation with different magnitude that depends on the load profile. Finally, the results show opposite impacts that depend on orientation and location when switching from a tilt angle of 30° to 45°. For a south orientation in Almeria and Lindenberg, the degree of autarky is increased when approaching the optimum tilt angle, while for west and east orientations in Lindenberg self-consumption increases.

Tilt Angle and Orientation Impact on the Techno-economic Performance of Photovoltaic Battery Systems

The techno-economic analysis investigates the impact of tilt angle and orientation on the production profile of a rooftop solar generator and the related performance of a photovoltaic battery storage system for single family houses at a specific location in Germany. The calculations are model-based and take into consideration the consumer load profile, technical and economic photovoltaic battery storage system parameters as well as the framework of regulations. The parameters “share of self-consumption”, “degree of autarky”, and “economic efficiency in terms of levelized cost of electricity” make up the focus of the modelling results. It is concluded that self-consumption and degree of autarky are strongly and inversely related. In terms of system design, a trade-off has to be made between aiming for high self-consumption and a high degree of autarky. Key findings from the modelling results reveal that a south orientation gives the highest degree of autarky and the lowest levelized cost of electricity, but with the lowest share of self-consumption as well. For rooftops oriented towards east/west, an interesting possibility could be to split the total installed capacity (equally) between the two orientations. This makes it possible to benefit from the high self-consumption of the east orientation and the high degree of autarky of the west orientation. In general it has to be considered that the optimum orientation strongly depends on the consumer load profile. Finally, the results show two opposite impacts that depend on orientation when switching from a tilt angle of 30° to 45°. For a south orientation, the degree of autarky is increased, while for west and east orientations, self-consumption increases.

Techno-economical Analysis of Photovoltaic-battery Storage Systems for Peak-shaving Applications and Self-consumption Optimization in Existing Production Plants

With rising electricity costs, increasing environmental awareness and aggravating legal requirements, production plants demand innovations in the field of energy efficiency and utilization of renewable energies. Here we perform a techno-economical assessment of photovoltaic-battery storage systems for industrial peak-shaving and self-consumption applications. In order to consider individual load profiles, different battery types, aging mechanisms, varying costs for electricity and storage capacity, a simulation tool was developed. Net present value method was applied to evaluate the costs over the systems’ service life. The case study shows positive net present values for system configurations with large photovoltaic systems compared to storage capacity.

Energy dispatch schedule optimization for demand charge reduction using a photovoltaic-battery storage system with solar forecasting

A battery storage dispatch strategy that optimizes demand charge reduction in real-time was developed and the discharge of battery storage devices in a grid-connected, combined photovoltaic-battery storage system (PV+system) was simulated for a summer month, July 2012, and a winter month, November 2012, in an operational environment. The problem is formulated as a linear programming (LP; or linear optimization) routine and daily minimization of peak non-coincident demand is sought to evaluate the robustness, reliability, and consistency of the battery dispatch algorithm. The LP routine leverages solar power and load forecasts to establish a load demand target (i.e., a minimum threshold to which demand can be reduced using a photovoltaic (PV) array and battery array) that is adjusted throughout the day in response to forecast error. The LP routine perfectly minimizes demand charge but forecasts errors necessitate adjustments to the perfect dispatch schedule. The PV+system consistently reduced non-coincident demand on a metered load that has an elevated diurnal (i.e., daytime) peak. The average reduction in peak demand on weekdays (days that contain the elevated load peak) was 25.6% in July and 20.5% in November. By itself, the PV array (excluding the battery array) reduced the peak demand on average 19.6% in July and 11.4% in November. PV alone cannot perfectly mitigate load spikes due to inherent variability; the inclusion of a storage device reduced the peak demand a further 6.0% in July and 9.3% in November. Circumstances affecting algorithm robustness and peak reduction reliability are discussed.

Supervision and control of grid connected PV-Storage systems with the five level diode clamped inverter

This paper aimed to evaluate the use of photovoltaic-battery storage systems to supply electric power in the distribution grid through a multilevel inverter. The proposed system is composed by four PV generators with MPPT (P&O) control, four battery storage systems connected to each capacitor of the DC link and a five level diode clamped inverter connected to the grid by a traditional three phase transformer. The proposed control has a hierarchical structure with both a grid side control level to regulate the power and the current injected to the grid and four input side regulation units. The system operator controls the power production of the four PV generators by sending out reference power signals to each input side regulation unit, the input side regulation units regulate the voltage of each capacitor of the DC link, regulate the voltage and the state of charge of each battery storage system.