A futuristic neighborhood with glowing energy pathways connecting buildings, symbolizing energy sharing and sustainability.

Smart Homes, Smarter Communities: How Grouping Buildings Can Save Energy and Money

Rhea Morgan in Climate & Environment August 2025 • 4 min read.

"Discover the innovative strategies for optimizing energy use in residential areas, turning neighborhoods into eco-friendly powerhouses and reducing your bills."

Imagine a neighborhood where every home produces as much energy as it uses, a concept known as nearly zero energy buildings (nZEBs). While individual nZEBs are a great start, the real magic happens when these homes work together. By forming communities that share renewable energy, these buildings can achieve even greater energy efficiency and cost savings.

But how do you decide which buildings should team up? Grouping similar buildings might seem logical, but the most significant benefits come from pairing buildings with diverse energy needs. For example, an office building that uses most of its energy during the day could share surplus solar power with residential homes that use more energy in the evenings.

This is where a smart grouping strategy comes in. A new approach uses advanced algorithms to identify buildings with complementary energy profiles, creating communities that maximize energy sharing and minimize waste. Let’s dive into how this works and how it can transform our neighborhoods into sustainable energy hubs.

The Science of Smart Grouping

A futuristic neighborhood with glowing energy pathways connecting buildings, symbolizing energy sharing and sustainability.

The key to effective energy sharing lies in understanding the energy characteristics of each building. This involves analyzing their power mismatch curves (PMCs), which show the difference between energy production and consumption over time. Buildings with similar PMCs don't have much to offer each other, but those with diverse PMCs can create a balanced energy ecosystem.

To simplify this complex analysis, a clustering-based grouping method is used. This method involves three main steps:

Clustering PMCs: Buildings are grouped based on their energy usage patterns using algorithms like K-means clustering.
Finding Optimal Groupings: The algorithm explores various combinations of building groups to find the arrangement that maximizes energy sharing.
Validating Performance: The chosen grouping is compared against scenarios where buildings aren't grouped or are randomly grouped to prove its effectiveness.

This approach not only identifies the best groupings but also quantifies the benefits in terms of economic cost and grid interaction. By minimizing electricity costs and reducing peak energy demands from the grid, these smart communities can become more sustainable and resilient.

The Future is Collaborative

As we move towards a more sustainable future, collaborative energy solutions like smart building communities will become increasingly important. By using data-driven insights to group buildings effectively, we can unlock significant energy savings, reduce our reliance on the grid, and create greener, more resilient neighborhoods. Whether you're a homeowner, a building manager, or a city planner, now is the time to explore how smart grouping can transform your community.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.1016/j.apenergy.2018.10.116, Alternate LINK

Title: A Clustering Based Grouping Method Of Nearly Zero Energy Buildings For Performance Improvements

Subject: Management, Monitoring, Policy and Law

Journal: Applied Energy

Publisher: Elsevier BV

Authors: Pei Huang, Yongjun Sun

Published: 2019-02-01

Everything You Need To Know

What are Nearly Zero Energy Buildings (nZEBs), and how does community energy sharing enhance their impact?

Nearly Zero Energy Buildings, or nZEBs, are designed to produce as much energy as they consume. They represent an initial step towards sustainable energy usage. The formation of communities where these nZEBs share renewable energy amplifies efficiency and cost-effectiveness, extending the benefits beyond individual buildings. This collaborative approach is key to maximizing energy savings.

What is a Power Mismatch Curve (PMC), and why is analyzing it important for smart energy sharing?

The Power Mismatch Curve, or PMC, illustrates the variance between a building's energy production and its consumption over a period. Analyzing PMCs is crucial because buildings with similar curves don't offer significant energy-sharing opportunities. Conversely, pairing buildings with diverse PMCs, such as an office building using peak energy during the day and residential homes using more in the evenings, creates a balanced energy ecosystem and maximizes the potential for energy exchange.

How does smart grouping work to create effective energy-sharing communities?

Smart grouping uses algorithms to determine which buildings would benefit most from energy sharing. The process involves clustering PMCs to group buildings based on energy usage patterns, finding optimal groupings by exploring different combinations to maximize energy sharing, and validating performance by comparing the chosen grouping against ungrouped or randomly grouped scenarios. The objective is to minimize electricity costs and reduce peak energy demands from the grid, promoting sustainability and resilience.

What are the potential economic and environmental benefits of forming smart building communities?

Smart building communities promise significant benefits, including reduced electricity costs through optimized energy sharing, decreased reliance on the energy grid, and the creation of more sustainable and resilient neighborhoods. By effectively grouping buildings based on their energy profiles, communities can minimize waste and maximize the use of renewable energy resources. The implementation of collaborative energy solutions can lead to both environmental and economic benefits.

Where does K-means clustering fit into the 'smart grouping' process, and what part does it play?

K-means clustering is used in the first step of the smart grouping process, which is 'Clustering PMCs'. The clustering-based grouping method is a crucial part of the overall process to help understand the patterns and characteristics of energy usage. By using algorithms, the smart grouping can proceed to identifying optimal groupings to validate performance.