Technical Insights | PV + Energy Storage + AI: How Can a Building Save Millions in Electricity Costs Annually?

“Monthly electricity bills are 800,000, and the boss gets a headache every time the air conditioning is turned on.”

This is a real complaint from the person in charge of a certain technology park.

Soaring corporate electricity costs and increasing power rationing risks,

How to break the deadlock?

The answer may be hidden on the roof

—— Photovoltaic power generation + energy storage system + AI ，

are transforming buildings from "big electricity consumers" into "energy factories,"

and can even achieve annual electricity cost savings of millions!

(Image source: Internet)

 

The "golden combination" of PV + energy storage + AI:

How can buildings "print money" themselves?

 

➤ Photovoltaic roof: turning sunlight into free electricity

Photovoltaic components convert solar energy into direct current, and the inverter converts it into alternating current for building use, realizing "self-generation and self-use, and surplus electricity to the grid."

Zero fuel cost: sunlight is free, and the power generation cost is only 1/3-1/2 of the grid electricity.

Long-term benefits: Taking a 10,000-square-meter roof as an example, with an installed capacity of 1MW, the annual power generation is about 1 million kWh, saving 800,000-1,200,000 yuan in electricity costs annually (calculated at an industrial and commercial electricity price of 0.8-1.2 yuan/kWh).

(Image source: Internet)

 

➤ Energy storage system: the "time transporter" of electricity

The energy storage system can store electricity and release it when needed, divided into four stages: charging-storage-discharge-control, supporting multiple technical routes such as lithium batteries and flow batteries.

Peak shaving and valley filling: storing electricity during the day and discharging at night, avoiding peak electricity prices (the peak-valley price difference in some cities exceeds 3:1).

Emergency backup power: ensuring the operation of key equipment during extreme weather or grid failures, reducing losses due to downtime.

Added benefits: By participating in peak-shaving services in the electricity market, the energy storage system can obtain additional subsidies or electricity sales revenue.

(Image source: Internet)

 

➤ AI energy consumption prediction: seeing through the building's "electricity personality" for the next N years

Integrating building energy consumption, meteorological data, and personnel activity patterns, a high-precision model is built through machine learning (LSTM, Transformer).

Ultra-high precision: relying on empirical formulas or static models, the error is generally above 20%; AI models, through massive data training, capture complex non-linear relationships, and improve prediction accuracy by 5-10 times.

Dynamic optimization: The model continuously optimizes based on real-time data, adapts to changes in building use, predicts energy consumption anomalies in advance (such as equipment failures, extreme weather effects), and reduces losses.

(Image source: Internet)

 

The "golden combination" seems perfect, but how to turn it from a "blueprint" into "real money"?

 

PKPM's solution:

Four technological revolutions directly address industry pain points

 

 

1. Design phase

PKPM-Solar building photovoltaic simulation and analysis software : Jointly developed with Sichuan Provincial Architectural Design and Research Institute Co., Ltd., it supports the selection of solar photovoltaic systems and building integrated design, guides the optimal tilt angle arrangement of photovoltaic panels, conducts carbon reduction effect evaluation and economic analysis, outputs reports that meet the requirements of review, Quantifying the "value of every square meter of roof" 。

• Actual case: A comprehensive service area building

By building a distributed photovoltaic and regional model, PKPM-Solar automatically matches the irradiation conditions of the project location and optimizes the arrangement of the optimal tilt angle of the photovoltaic panels to achieve the simulation calculation of photovoltaic power generation. The average annual power generation of this project is 364750.60 (kWh) ≈ 36 Ten thousand kWh ，the carbon reduction is equivalent to planting 2000 trees annually 🌳 。

 

2. Construction phase

Carbon emission monitoring platform: A carbon emission monitoring platform for the construction phase of substations has been developed to monitor carbon emissions during the construction process in real time, accurately counting and displaying high-carbon emission sources of various types and scenarios within the construction boundary, Achieving "transparency" in carbon emission monitoring 。

• Actual case: Low-carbon control platform during the construction phase

Click to view details: The 500kV substation carbon emission monitoring platform has been successfully launched, opening a new chapter in low-carbon construction in the power industry!

 

 

3. Operation and maintenance phase

Photovoltaic storage direct flexible intelligent operation and maintenance system: Using load forecasting to form a differentiated comparison, assisting in the design analysis, intelligent monitoring, and efficient operation of new power systems, assisting energy regulatory decision-making, promoting building energy saving and emission reduction, and achieving "one-screen control of the overall situation" for visualized management of carbon assets.

• Actual case: Photovoltaic storage direct flexible intelligent operation and maintenance platform

Click to view details: Technology leads the future | Gouli Technology helps China Eastern Airlines' "Seashell Building" shine with green wisdom

 

 

4. AI building energy consumption prediction model

By analyzing and processing massive amounts of data on building information, meteorology, energy consumption, and other types of data, an energy consumption prediction model is constructed using AI methods to achieve energy consumption prediction and evaluation of different types of buildings at various stages, which is A data-driven "energy brain" 。

Prediction: Combining real-time weather forecasts and photovoltaic equipment parameters to accurately predict building energy consumption;

Update: Dynamically update the photovoltaic prediction model as actual data accumulates during building operation;

Application: Applicable to multiple scenarios such as factories, power plants, commercial, office, education, medical, and residential buildings;

(Image source: Internet)

 

Against the backdrop of the "dual carbon" strategy, Gouli Technology has successfully achieved "Photovoltaic + Energy Storage + AI" The full process application of technology from design to implementation demonstrates the industry's leading innovative strength. At the same time, the national and local governments have intensively introduced a number of support policies for the photovoltaic industry, injecting strong impetus into the high-quality development of the industry.

 

Policy Dividends:

Enterprise Photovoltaic Layout "Lying Win" Strategy

 

➤ National Level

• The "2024-2025 Energy Conservation and Carbon Reduction Action Plan" issued by the State Council proposes: By the end of 2025, all newly built buildings in urban areas will implement green building standards, and the photovoltaic coverage rate of newly built public institution buildings and newly built factory buildings will strive to reach 50%;

• The "Management Measures for the Development and Construction of Distributed Photovoltaic Power Generation" issued by the National Energy Administration proposes: Encouraging investment entities of distributed photovoltaic power generation projects to adopt the construction model of building-integrated photovoltaics.

 

➤ Local Level

• Beijing: Six areas including Beijing Economic-Technological Development Area, Haidian District, and Xicheng District have issued subsidy policies. Among them, the Beijing Economic-Technological Development Area provides a one-time reward of 0.8 yuan/watt for distributed photovoltaic power generation projects according to installed capacity;
• Shanghai: Seven areas including Xuhui District, Yangpu District, and Huangpu District have issued subsidy policies. Among them, Pudong New Area provides subsidies according to installed capacity for projects within the scope of application, with a subsidy of 0.35 yuan/watt, with a maximum of 5 million yuan for a single project;
• Guangdong Province: Issued the "Guangdong Provincial Action Plan for Promoting the High-Quality Development of Distributed Photovoltaics", providing multiple preferential treatments and support for distributed photovoltaics in terms of taxation, energy consumption, and application scenarios.

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