機械学習でエネルギー需要を予測し分配を最適化するInBarance Research

今回は「機械学習でエネルギー需要を予測し分配を最適化するInBarance Research」についてご紹介します。

関連ワード （InBarance Research、Y Combinator、電力網等） についても参考にしながら、ぜひ本記事について議論していってくださいね。

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マサチューセッツ州のケンブリッジと、英国のケンブリッジにまたがり拠点を構えるinBalance Research（インバランス・リサーチ）は、Y Combinator（ワイコンビネーター）に参加し、現在行っている独立系電力供給業者、電力会社、証券会社に「お告げ」を与える事業を加速させる狙いだ。

Delphi（デルファイ）と呼ばれるサービスを販売するこの極めてアーリーステージのスタートアップは、電力供給業者や電力会社に、エネルギー市場の需要予測に関する分析情報を提供したいと考えている。

この10年間で「100年に1度」の嵐に2度も襲われ、電力網に壊滅的な被害を受けたテキサス州の事例もあり、電力会社にとっては、米国全域にわたる電力網の負荷の総合的な調整が差し迫った問題になっている。

関連記事：悪天候や停電が示す米国の電力網最大の問題は再生可能エネルギーではなくインフラそのものにある

「長期的なソリューションを求めるならば、それは2部構造のソリューションとなります」と、inBalanceの共同創設者にして最高責任者のThomas Marge（トーマス・マージ）氏はいう。「それはハードウェアとソフトウェアの組み合わせです。オンライン上の適切なアセットと適切なソフトウェアがあって初めて、極端なショックに襲われたときにも市場を確実に機能させることができます」。

電気の価格は15分ごとに変化し、ときには激しい変動を見せる。テキサスの電力網を破壊し、いくつもの企業を廃業に追い込んだような気象災害がなかったとしても、ほんの1時間で価格が倍になることもあると、inBalanceは話している。

だからこそ、予測ツールが重要になるのだと同社はいう。価格が高騰するにつれ、アセットの調達が柔軟に行えない水力発電や蓄電業者のアセット管理者は、市場に供給する価値をいつ増やすべきかの判断を迫られる。電力供給が早すぎたり遅すぎたりすれば、そのクリーンな発電による収益は下がり、消費者に高いピーク時価格を強いることになる。

同社によれば、蓄電によるものや断続的な再生可能電力が同時に供給されると、状況はさらに難しくなるという。それが、蓄電電力と再生可能電力の両方の価格を押し下げる圧力となり、それと引き換えに、いずれこれらのクリーンな電力の供給量が落ちたとき、化石燃料による発電量が増加する恐れが生じる。

そうした圧力の予測を行うソフトウェアの提供を行うのがinBalanceだと、同社は主張する。マージ氏とその共同創設者であるRajan Troll（ラジャン・トロル）氏とEdwin Fennell（エドウィン・フェンネル）氏は、以前からビッグデータとエネルギーに関連する問題に関心を寄せていた。

マージ氏の場合、 マサチューセッツ州レキシントンで風力発電の最適化プロジェクトに携わっていたころにその関心が芽生えた。

「基本的に、私たちはデータサイエンスソリューションなのです」とマージ氏。「北米における個々のあらゆる市場の、個々のあらゆるアセットに影響を及ぼす要素を認識し統合することです。それらのアセットがどのように働き出すか、その兆候を1日から1時間前に把握できます」。

現在のところ、北米で同社のソフトウェアを利用しているある電力会社は、二酸化炭素排出量を0.2％削減することに成功した。再生可能エネルギーを重視するinBalanceは、この市場で他のサービスに予測ツールを利用している3000の業者でも、大幅な排出量削減ができると期待している。inBalanceが進めている、同ソフトウェアのもう1つの応用先に、尖頭負荷発電所がある。再生可能電力の間欠性を補完するのが目的だ。

ニューイングランド地区では、2020年12月に同地域の電力会社との協力を開始したばかりであるにも関わらず、二酸化炭素排出量の削減に目覚ましい結果が出ている。予測ツールのお陰で、同社は、その時々で最も価値が高いアセットを示すことができる。そうしたアセットには、天然ガス尖頭負荷発電所、水力発電所、揚水型水力発電所（基本的にこれは蓄電技術）、バッテリーまたはフライホイール・バッテリー計画、さらに価格表示によって企業や消費者が電力消費を抑えるように促すデマンドレスポンス技術などが考えられると、マージ氏は話す。

すでに、6社の企業がDelphiソフトウェアを見に来て、初期ユーザーになっている。マージ氏によれば、そこには国際的な再生可能アセット管理会社や米国でトップ10に入る電力会社などが含まれているという。

「私たちは、数テラバイトに上る公共および独自のデータを用いて、機械学習により電力価格を正確に予測しています。日々の電力システムの安定のために求められるソリューションは、ハードウェア（蓄電や電気自動車の充電など）と、それを最適に利用するためのソフトウェアで成り立ちます。inBalanceの存在意義は、そのソフトウェアソリューションにあります」と同社は声明の中で述べている。

画像クレジット：Stuart Kinlough

【原文】

From distributed homes in Cambridge, Mass. and Cambridge, England, inBalance Research is joining Y Combinator as it looks to accelerate its business as the oracle for independent energy providers, utilities and market makers.

Selling a service it calls Delphi, the very early-stage startup is hoping to provide analysis for power producers and utilities on the demand forecasts of energy markets.

The orchestration of energy load across the grid has become a more pressing issue for utilities around the country after witnessing the disastrous collapse of Texas’ power grid in response to its second “once-in-a-century” storm in the last decade.

“If we want to address the solution long term, it’s a two-part solution,” said inBalance co-founder and chief executive, Thomas Marge. “It’s a combination of hardware and software. You need the right assets online and you need the right software that can ensure that markets operate when there are extreme market shocks.”

Prices for electricity change every 15 minutes, and sometimes those pries can fluctuate wildly. In some places, even without the weather conditions that demolished the Texas grid and drove some companies out of business, prices can double in a matter of hours, according to inBalance.

That’s what makes forecasting tools important, the company said. As prices spike, asset managers of finite responsive resources such as hydro and storage need to decide if they will offer more value to the market now or later. Coming online too early or too late will decrease the revenue for their clean generation and increase peak prices for consumers.

The situation is even worse, according to the company, if storage and intermittent renewables come online at the same time. That can create downward price pressure for both the storage and renewable assets, which, in turn, can lead to increased fossil fuel generation later the same day, once cleaner sources are depleted.

The software to predict those pressures is what inBalance claims to provide. Marge and his fellow co-founders, Rajan Troll and Edwin Fennell have always been interested in the problems associated with big data and energy.

For Marge, that began when he worked on a project to optimize operations for wind farms during a stint in Lexington, Mass.

“Fundamentally we’re a data-science solution,” said Marge. “It’s a combination of knowing what factors influence every single asset on every single market in North America. We have a glimpse into how those assets are going to be working one day before to one hour before in order to do price forecasting.” 

So far, one utility using the company’s software in the Northeast has managed to curb its emissions by 0.2%. With a focus on renewables, inBalance is hoping to roll out larger reductions to the 3,000 market participants that are also using its forecasting tools for other services. Another application is in the work inBalance is conducting with a gas peaker plant to help offset the intermittency of renewable generation sources.

The reduction in emissions in New England is particularly impressive given that the company only began working with the utility there in December. Given its forecasting tools, the company is able to provide a window into which assets might be most valuable at what time — including, potentially, natural gas peaking plants, hydropower, pumped hydropower (basically an energy storage technology), battery or flywheel energy storage projects and demand response technologies that encourage businesses and consumers to reduce consumption in response to price signals, Marge said.

Already, six companies have taken a trip to see the Delphi software and come away as early users. They include a global renewable asset manager and one of the top 10 largest utilities in the U.S., according to Marge.

“We use machine learning to accurately forecast electricity prices from terabytes of public and proprietary data. The solution required for daily power system stability is both hardware — like storage and electric vehicle charging — and the software required to optimally use it. inBalance exists to be that software solution,” the company said in a statement. 

（文：Jonathan Shieber、翻訳：金井哲夫）

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