How to optimize electricity costs using BESS? Frontiers of load leveling and model predictive control
In today's society, optimizing electricity costs and stable supply are urgent issues for companies. Fluctuations in electricity demand due to the spread of renewable energy in particular call for new countermeasures. This article focuses on the use of BESS (battery energy storage systems), which are attracting attention as a powerful solution to this problem, and model predictive control (MPC) that maximizes its efficiency, particularly load leveling model predictive control (LLMPC). I will explain in detail how BESS and LLMPC contribute to reducing electricity costs and improving energy efficiency, from their mechanisms to specific implementation cases, and even future prospects.
The key to reducing power costs: BESS and the importance of load leveling
In recent years, the rise in electricity costs has become a major issue for companies. Among them, the importance of introducing battery energy storage systems (BESS) and load leveling is attracting attention as solutions to reduce electricity costs and realize sustainable business operations. In this paper, I will explain how these technologies contribute to reducing electricity costs and the key mechanisms.
Why is power load leveling important now?
Power load leveling is an important initiative to suppress fluctuations in electricity demand and achieve stable power supply. In particular, in the modern age where the introduction of renewable energy is progressing, its importance is increasing. At the peak of electricity demand, power generation costs soar, and the burden on the power system also increases. Load leveling solves these problems and helps reduce power costs and improve energy efficiency.
Issues with the spread of renewable energy and fluctuating electricity demand
Renewable energies such as solar power generation and wind power generation are easily affected by the weather, and the amount of power generated tends to fluctuate. As a result, the load on the power system tends to fluctuate, and stable power supply is an issue. Also, since demand for electricity fluctuates greatly depending on the time of day and season, it is difficult to maintain a balance between supply and demand. In order to solve these issues, technology for leveling power loads is essential.
What is BESS (Battery Energy Storage System)?
BESS (Battery Energy Storage System) is a system that stores electrical energy in a battery and can be discharged when necessary. This makes it possible to supply electricity during peak electricity demand and to store surplus renewable energy, contributing to leveling the power load. BESS is an essential technology for modern energy systems, not only for stabilizing power systems, but also for reducing electricity costs and making effective use of renewable energy.
How BESS contributes to power load leveling
BESS mitigates fluctuations in power demand by charging power during times when power demand is low (off-peak) and discharging during times when power demand is high (peak). This allows power companies to reduce the amount of electricity generated during peak times, leading to a reduction in electricity charges. Also, even when the amount of renewable energy generated fluctuates, the impact on the power system can be minimized by BESS storing and adjusting power.
Control Methods for BESS Optimization: Introduction of Model Predictive Control (MPC)
As the introduction of renewable energy expands, stabilizing power systems has become an urgent issue. In order to address this issue, the use of battery energy storage systems (BESS) is attracting attention. BESS not only absorbs fluctuations in power generation volume and demand and contributes to system stabilization, but also provides profit opportunities through market transactions. In order to maximize the performance of BESS, advanced control technology is essential, and in recent years, model predictive control (MPC) has attracted attention due to its effectiveness.
What is load leveling model predictive control (LLMPC)?
LLMPC (Load Leveling Model Predictive Control) is a control method for optimizing BESS charging/discharging by applying model predictive control (MPC). LLMPC simultaneously reduces power costs and realizes load leveling by predicting future power demand and systematically charging/discharging BESS based on that. Compared to conventional control methods, more efficient and flexible operation is possible.
Why LLMPC is effective in reducing energy costs
LLMPC predicts future electricity demand based on past power demand data, weather data, etc. By optimizing BESS's charge/discharge schedule based on this forecast, it is possible to reduce peak power consumption and reduce demand charges. Additionally, LLMPC can minimize power costs by adjusting BESS charging/discharging according to fluctuations in electricity charges. LLMPC's major strength is that it can perform optimal operations by considering multiple factors.
LLMPC implementation steps and precautions
When implementing LLMPC, it is first necessary to understand the characteristics of electricity demand and construct an appropriate model. Next, control parameters are adjusted according to BESS performance and operating conditions. At the time of implementation, it is important to consider initial costs, operating costs, system stability, etc., and carefully consider them. Furthermore, even after implementation, continuous data analysis and improvement must be carried out to maximize the effectiveness of LLMPC.
Effects of LLMPC as seen from demonstration experiments
In this section, we will consider the effects of LLMPC based on the results obtained in the demonstration experiment.
Empirical Study: Power Fee Reduction Effects of LLMPC
In the LLMPC demonstration experiment, BESS was actually operated to verify the effects of control by LLMPC. These experimental results show that LLMPC contributes to a significant reduction in electricity charges compared to conventional control methods. In particular, the effects of LLMPC are evident in facilities where electricity demand fluctuates greatly and facilities that have introduced renewable energy.
Specific reduction examples and data analysis
In a demonstration experiment at a factory, there is data that the annual electricity bill was reduced by 15% by introducing LLMPC. This is due to LLMPC effectively suppressing peaks in electricity demand and reducing demand charges. Also, at another commercial facility, LLMPC has succeeded in efficiently utilizing surplus electricity from solar power generation and drastically reducing the amount of electricity purchased. These cases specifically show that LLMPC is effective in reducing electricity costs.
Changes in operating costs due to the introduction of LLMPC
The introduction of LLMPC will incur initial costs, but in the long run, operating costs can be drastically reduced by reducing electricity bills. LLMPC can also be expected to have the effect of extending battery life by optimizing BESS charging/discharging. This reduces battery replacement costs and contributes to long-term cost savings.
BESS implementation and operation considerations
In recent years, as the introduction of renewable energy has expanded, stabilizing power systems has become an urgent issue. The introduction of electricity storage systems (BESS) is attracting attention as a key to solving this problem. BESS greatly contributes to system stabilization by absorbing output fluctuations in variable power sources such as solar power generation and wind power generation, and adjusting the power supply and demand balance. In addition, BESS has a wide range of advantages, such as reducing electricity charges through peak cut/peak shift, and being used as an emergency power source in the event of a disaster. However, there are various considerations for implementing and operating BESS, such as cost, safety, regulations, and technical constraints. This article details key considerations for BESS implementation and operation.
Pre-review before implementing BESS: Balancing cost and effectiveness
When considering the introduction of BESS, it is necessary to comprehensively evaluate initial costs, installation space, operating costs, expected effects, etc. Also, it is important to carefully select the BESS type, capacity, control system, etc., and build a system that best suits your company's needs. We recommend getting expert advice and performing detailed simulations prior to implementation.
Data analysis and continuous improvement in BESS operations
Continuous data analysis and improvement is essential even after the introduction of BESS. By analyzing BESS operation data, it is possible to find system issues and improvements, and aim for more efficient operation. Also, when introducing control methods such as LLMPC, it is important to perform regular parameter adjustments to optimize system performance.
Energy cost optimization realized by BESS and LLMPC
BESS technology has advanced rapidly in recent years, and battery energy density, life span, charging/discharging efficiency, etc. have improved. As a result, the cost of implementing BESS will gradually decrease, and it is expected that implementation will progress in more companies and facilities. Also, with the development of advanced control technology such as LLMPC, it is thought that the possibility of reducing electricity costs will expand further.
Advice for companies considering implementing BESS
The introduction of BESS has the potential to greatly contribute to reducing electricity costs and improving energy efficiency, but careful consideration is necessary before implementation. First, we recommend understanding the characteristics of your company's electricity demand and constructing an optimal system while receiving expert advice. Furthermore, even after implementation, it is important to carry out continuous data analysis and improvements to maximize the effects of BESS.
