标签：#Power

An old Oscar Mayer factory in Wisconsin will become America's latest fusion power research and development hub.

General Fusion started trading on the Nasdaq following a reverse merger that saw high redemptions.

GitHub热门项目 | A simple, lightweight PowerShell script that allows you to remove pre-installed apps, disable telemetry, as well as perform various other changes to declutter and customize your Windows experience. Win11Debloat works for both Windows 10 and Windows 11. | Stars: 50,538 | 74 stars today | 语言: PowerShell

Whether you’re going off-grid or safeguarding against blackouts, these beefy, WIRED-tested batteries can keep the lights on.

The companies’ Fourth of July plans include celebrating new reactor designs coming online. But there’s still a long way to go before they deliver energy at a meaningful scale.

This continues from Part ① . In Part ②, we'll configure the common settings and the internal-processing Power Automate flows. Common Settings Setting Up Connections Open Power Automate ( https://make.powerautomate.com ) Go to "Data" → "Connections" → "New connection" and create a Microsoft Dataverse connection Do the same to create an Office 365 Outlook connection Basic Flow Creation Steps Click "Create" → select "Automated cloud flow" (event-triggered) or "Scheduled cloud flow" (recurring) Name flows in the format [Zone]-[Number] [Description] (e.g., "A-1 Opportunity Stage Stall Alert") Always run a test after creating a flow to verify it works 2. Internal-Processing PA Flows — 4 Flows (Write-back portions of A-4, C-5, C-6, D-3) Once the common settings are done, it's time to build. A-4: Write Back Stage Changed Date Without this flow, the stall-day calculations in A-1 and B-1 will not work. Implement this first. In Microsoft Dynamics 365 (D365), a "stage" refers to a major milestone in a process — such as a sales deal or customer engagement — that guides the responsible person through what needs to happen next. It's how a series of activities is visualized and managed. From here, all work is done in Power Automate. Step Task Details 1 Create the flow "Automated cloud flow" → select trigger "When a row is added, modified or deleted (Dataverse)" 2 Configure trigger Table: Opportunities / Change type: Modified 3 Add condition Add a "Condition" action: "When Status Reason (statuscode) has changed" 4 Write-back action "Update a row (Dataverse)" → set cr917_stage_changed_date to utcNow() C-5: Auto-Set Renewal Date + Auto-Create Renewal Opportunity (on Won) On Won close, two things happen: ① auto-set the renewal date to close date + 365 days, and ② auto-create a new Opportunity for the renewal cycle and add it to the pipeline. Step Task Details 1 Create the flow "Automated cloud flow" → trigger "When a row is added, modified or deleted (Dataverse)" 2 Configure trigger Ta

“We can take power from a plasma,” Kieran Furlong, co-founder and CEO of Realta Fusion, told TechCrunch. The milestone shows “what’s possible,” he added.

A database without relationships is just a spreadsheet with delusions of grandeur. If you've ever stared at a Power BI report showing wrong numbers...totals that don't add up, filters that filter nothing, there's a good chance your data model was broken. Not a bug. Just two tables that should've been talking to each other… and weren't. This is your practical guide to data modeling, schemas, relationships, and joins in Power BI, what they are, how they connect, and how to stop getting burned by them. What Is Data Modeling and How Does It Work? Data modeling is the process of defining how your tables connect to each other inside Power BI's engine (called VertiPaq). Think of it like drawing a map between your tables, telling Power BI this column in Table A is the same thing as this column in Table B. When you load multiple tables into Power BI, it doesn't automatically know they're related. A Sales table and a Products table, sitting separately, can't filter each other. Data modeling builds the bridges. Power BI's model view lets you: Define relationships between tables Set cardinality and cross-filter direction Build star or snowflake schemas Create calculated columns and measures using DAX Under the hood, Power BI compresses and stores each column separately ( columnar storage ). Relationships are resolved in-memory at query time, which is why a well-structured model is blazing fast, and a messy one will bring your report to its knees. Key Concepts | Concept | What It Means | |--------------------------|-----------------------------------------------------| | Fact Table | Stores measurable events (sales, transactions, logs)| | Dimension Table | Stores descriptive context (products, customers) | | Primary Key (PK) | Unique identifier column in a dimension table | | Foreign Key (FK) | Column in a fact table referencing a PK in a dim | | Relationship | The defined link between a PK and FK across tables | | Cardinality | Describes how many rows on each side match | | Cro

Have you ever wondered how apps like university portals know which courses a student is enrolled in, or how they pull up an instructor's full schedule in seconds? The answer lies in database relationships - one of the most important concepts in backend development. In this article, we'll explore: What database relationships are and why they matter The three types of relationships: One-to-One, One-to-Many, and Many-to-Many How relationship schemas work (primary keys, foreign keys) How SQL Joins let you pull connected data from multiple tables To keep things grounded, we'll use one running example throughout: a University Management System . By the end, you won't just understand the theory, you'll see exactly how these concepts connect in a real-world scenario. What Are Database Relationships? A database relationship defines how data in one table connects to data in another. Instead of storing the same information repeatedly, relational databases organize data into separate tables and link them using keys . Think about our university system. We have a table for students and another for courses . A student can enroll in multiple courses, and each course can have many students. Rather than storing a student's full details on every course record, we store the student's info once and create a relationship between the two tables. This keeps data clean, reduces duplication, and makes updates easy. If a student's email changes? Update it in one place - done. Here's a simple visual of what that looks like: +------------------+ +------------------+ | Students | | Courses | +------------------+ +------------------+ | student_id (PK) | | course_id (PK) | | name | | title | | email | | credits | +------------------+ +------------------+ \ / \ / \ / Enrollments (links students ↔ courses) Now let's look at the three types of relationships you'll encounter. Types of Database Relationships 1. One-to-One (1:1) Each record in Table A matches exactly one record in Table B and vice versa

If you don't know you need a jump starter, it’s a sign you really, really need a jump-starter. NOCO and Wolfbox are the best ones.

Base Power is skipping the PJM's troubled interconnection queue by placing its batteries at people's homes, offering backup services in exchange.

Pick up this deal on Jackery's whole home backup battery and be ready for the next power outage.

I wanted a chat agent that could pull security alerts from Sophos Central on demand. Type "get Sophos alerts" into a Copilot Studio chat, get back a readable answer. No dashboard, no manual API calls. It works now, end to end. Agent calls a Power Automate flow, the flow talks to the Sophos API, and the response comes back formatted in chat. This post is how I got there, including the bugs that ate most of my time. The shape of the thing Three pieces: A Copilot Studio agent that the user talks to A Power Automate flow that does the actual API work The Sophos Central API on the other end The agent does not call Sophos directly. It calls the flow, the flow handles auth and the request, and the result gets passed back to the agent to format. Keeping the API logic in the flow means the agent stays simple. The flow The flow is named Sophos - Get Alerts , living in a solution called Sophos Integration . Here is the structure: [Trigger: When Copilot Studio calls a flow] | [Init ClientId] - String (Sophos Client ID) [Init ClientSecret] - String (Sophos Client Secret) [Init TenantId] - String (your Sophos tenant ID) [Init ApiHost] - https://api-<region>.central.sophos.com | [HTTP Get Token] POST https://id.sophos.com/api/v2/oauth2/token Header: Content-Type: application/x-www-form-urlencoded Body: grant_type=client_credentials&client_id={ClientId}&client_secret={ClientSecret}&scope=token | [Parse Token] - extract access_token | [HTTP Get Alerts] GET {ApiHost}/common/v1/alerts Headers: Authorization: Bearer {access_token} X-Tenant-ID: {TenantId} Accept: application/json | [Return value(s) to PVA: AlertsResponse = body('HTTP_Get_Alerts')] Auth is OAuth client credentials. You request a token, then use it as a bearer token on the alerts call. The tenant ID goes in an X-Tenant-ID header, not the URL. Where the credentials live This is the part people will have opinions about, so let me be upfront. The Sophos client ID, secret, and tenant ID are stored as flow-scoped variables wit

At least three coal plants have been repeatedly cited for violating environmental regulations.

Fusion startups have raised $7.1 billion to date, with the majority of it going to a handful of companies.

With an initial capacity of 24 megawatts, the innovative data center uses seawater as a natural cooling system.

Fusion power startup Avalanche Energy said its reactor prototype heated a plasma to over 10 million degrees C.

Five peer-reviewed papers update the design and model its expected output.

How SCPN Phase Orchestrator v0.8.0 turns Kuramoto dynamics into a domain-agnostic control compiler, why we verify math across five languages, and the honest truth about building a Boeing 747 when most people need a bicycle. The $5.2 Billion Blackout That Started This On August 14, 2003, a cascading failure in the US Northeast power grid left 55 million people without electricity. The final report cited something deceptively simple: synchrony loss . A generation unit in Ohio drifted out of phase. The protective relays, designed to prevent damage, tripped in sequence. One desynchronized oscillator triggered a cascade that propagated across 265 power plants in nine minutes. The grid had controllers. It had models. What it lacked was a shared, reviewable language for coherence — a way to ask, in real time: "Is this synchrony valuable or dangerous? And if I touch this knob, can I prove what will happen before the electrons move?" That question is why I built SCPN Phase Orchestrator . It is not a Kuramoto simulator. It is a coherence control compiler — a system that takes any cyclic process (power waves, cloud retries, neural spikes, traffic signals) and compiles it into a unified phase space where synchrony can be observed, classified, and modified with bounded, auditable, replayable actions. Version 0.8.0 just shipped. It includes something I have not seen in any other open-source oscillator library: cross-language mathematical parity verification and Lean proof obligations for safety-critical control chains. This post is the honest story of why we built it, how it works, and where we might have gone too far. The Fragmentation Problem If you work on synchrony in 2026, you live in silos. Power engineers use PSS/E or PowerFactory with swing-equation models. Cloud operators use Airflow, Kestra, or Temporal for workflow orchestration — none of which understand phase dynamics. Neuroscientists use FieldTrip or MNE-Python for EEG phase analysis, but the tools stop at visualiza

Whenever I heard about harmonics, I thought they were only related to large substations, transmission systems, and industrial facilities. I assumed harmonics were something utility engineers dealt with and not something connected to everyday devices. Phone chargers can create harmonics. Laptop chargers can create harmonics. LED lights can create harmonics. Even a UPS sitting under a desk can create harmonics. Today, modern power systems use many power electronic devices such as EV chargers, solar inverters, battery energy storage systems (BESS), UPS systems, data centers, and Variable Frequency Drives (VFDs). While these technologies bring many benefits, they can also introduce harmonic distortion. The more power electronic devices we connect to the grid, the more important harmonic analysis becomes. In this article, I will explain what harmonics are, what causes them, how they affect power quality, how they can be analyzed using PSCAD, and why they are becoming more important in modern power systems. Before we talk about harmonics, let's first understand electrical loads, because this is where harmonics usually begin. What Is an Electrical Load? An electrical load is any device that uses electrical energy to perform useful work. For example, think about a typical evening at home. You turn on a ceiling fan, LED light, laptop, air conditioner, and phone charger. All of these devices use electricity, so they are called electrical loads. Examples of electrical loads include motors, heaters, fans, computers, air conditioners, lighting systems, and EV chargers. However, not all electrical loads use electricity in the same way. Some draw current smoothly, while others draw current in short pulses. This small difference is actually where the story of harmonics begins. Linear vs Non-Linear Loads To understand harmonics, we first need to understand the difference between linear and non-linear loads. Although both types of loads consume electricity, they draw current from the