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Quantum computing is emerging as one of the fastest-growing technology areas, thanks to phenomena occurring at the fundamental scale that only quantum mechanics can describe and explain, such as superposition, entanglement and interference. The processing power of quantum computers is phenomenal with respect to classical digital computers enabling execution of complicated calculations much more efficiently. Digital computers look unsuitable in addressing certain complex problems in mathematics, chemistry, weather forecasting, encryption, cybersecurity, grid management and transportation logistics.
What is a quantum algorithm?
A classical, non-quantum algorithm consists of a systematic approach to solving a given problem in the form of a limited sequence of instructions, with each instruction being executed by the hardware of a conventional computer. Similarly, a quantum algorithm is still a step-by-step procedure, but the steps are performed on a quantum computer. Even if classical algorithms can be performed on a quantum computer replicating quantum mechanics fundamentals and error correction and detection, quantum algorithms use some inherent features of quantum computation, such as superposition or entanglement.
Quantum algorithms for electrical grid management
Some researchers have already explored the potential of quantum computers in boosting power grid performance. The main problem arises from the fact that running and maintaining an existing grid is extremely expensive and time-consuming. The grid management issue is also compounded by the deployment of renewables, which are set to put extra stress on the distribution power lines. In fact, the world’s electricity demand is set to surge, driven by economic growth, technological advancements and the imperative to transition to non-fossil energy sources. To put this into perspective, the expected global electricity demand could reach a value close to 35,300 terawatt-hours (TWh), from 22,000 TWh in 2017.
Power companies, many of which rely on narrow margins, often cannot afford to replace aged equipment, so they keep patching it up, making the grid more prone to power outages.
In response to the Paris Climate Agreement, countries worldwide have embarked upon implementing green energy policies aiming for 100% renewable-based power generation with net-zero emissions by 2050. Distributed energy resources, including photovoltaic and windmills—uncertain sources by definition—will therefore be integrated into power grids, and this may pose substantial challenges for system operators in terms of coordination and management. Power grids are already large distribution systems and will grow even further, so decisions become more complex, too. Events like cyberattacks, made possible by extensive data exchanged between stakeholders and entities, must also be considered. And ironically, attacks inspired by quantum algorithms may crack most of the cryptography algorithms in power system data communication based on various mathematical problems. In the end, operating such complex systems will require novel modeling strategies and trailblazing computational techniques for various functions, such as control, optimization and forecasting.
Today’s computers are ineffective in managing these big issues. Renowned companies including IBM, Google, D-Wave, Intel, Microsoft and various startups, namely IonQ and Rigetti, are competing to build the largest quantum computer.
Current use of quantum computing by electric utilities
Electric utility companies are steadily moving toward employing quantum computing in various fields. Enel, an Italian multinational energy company and a major integrated player in the global energy, gas and renewable energy markets, partnered with Data Reply, an enterprise that offers advanced data analytics powered by AI, to solve combinatorial optimization problems based on the quadratic unconstrained binary optimization (QUBO) model. QUBO creates an optimal plan for assigning a large number of interventions with a finite number of crews. Optimizing the planning of maintenance work conducted by the teams operating in the area, from a computational point of view, means immediate availability and greater efficiency in the use of resources to achieve a significant reduction in costs.
U.K.-based E.ON has been working with IBM Quantum to implement quantum solutions for its critical workflow. According to E.ON, energy will no longer be transported unilaterally from the generating company to the user, but a future could include smaller companies and households that will feed energy into the grid—for example, via their own photovoltaic systems or electric cars. Quantum computing could be used to control these processes more efficiently and effectively in the future. At the same time, the increasing number of electric cars is leading to more complex charging processes, which quantum computing could help address.
The Phasecraft case
In the race to make electrical grids more efficient, Phasecraft, a leading U.K. quantum algorithm startup, has won a U.K. government contract worth £1.2 million to optimize energy grids using quantum technology, as part of the Quantum Catalyst Fund, one of only six projects taken to the next stage of the competition. Following the successful completion of Phase 1, Phase 2 of this project will see Phasecraft work with the Department for Energy Security and Net Zero to prioritize and attempt to address such optimization problems with quantum solutions, with a special focus on operation costs. Building and maintaining grid connections is extremely expensive, costing up to £1.5 million per kilometer of line. The new contract comes after a successful year for the startup, which raised £13 million in Series A funding in August to reach practical quantum advantage—when quantum computers outperform classical computers for useful real-world applications.
What is remarkable is that the Quantum Catalyst Fund aims to accelerate the adoption of quantum technologies to transform public services. As Andrew Griffith, Minister of State for Science, Research and Innovation, remarked, “This further £45 million in funding underscores our commitment to support bright U.K. innovators who are pushing boundaries and seizing the potential of this technology to transform our public services.”
Phasecraft, founded in 2019 by quantum scientists, designs novel quantum algorithms to solve real-world problems on the imperfect quantum computers of today, aiming to accelerate the widespread adoption of quantum computing from decades to years away. Its algorithms are based on novel insights from theoretical physics and computer science, and Phasecraft’s early focus is on applying these algorithmic improvements to modeling and simulation problems, such as the design and use of complex energy grids. Today, Phasecraft works in partnership with leading quantum hardware companies, including Google, IBM and Rigetti, as well as academic and industry leaders.
Practical problems quantum algorithms can address
Optimization and load balancing
Quantum algorithms can efficiently solve complex optimization problems. In an optimization problem, we seek the best of many possible combinations. An example: “What is the most efficient route a traveling salesperson should follow to visit different cities?” Physics can help solve these sorts of problems because it boils down to an energy minimization problem. A fundamental rule of physics, including quantum physics, is that everything tends to reach a minimum-energy state (any object slides down slopes). Quantum annealing simply uses quantum physics to find low-energy states of a problem and therefore the optimal or near-optimal combination of elements. For smart grids, this means better load balancing, minimizing energy losses and optimizing power distribution.
Energy forecasting
Quantum algorithms, by enhancing the process of forecasting energy demand and supply, can help to achieve grid stability and efficient resource allocation. Quantum machine-learning models can process large datasets and improve accuracy in predicting energy consumption patterns.
Grid resilience and security
Quantum cryptography offers accrued security protocols. Quantum-resistant algorithms are essential to protect smart-grid infrastructure against attacks from future quantum computers.
Grid simulation and modeling
Quantum simulators can produce an accurate model of power flow, fault analysis and stability assessments. These simulations enable grid operators to test scenarios, optimize grid parameters and strengthen overall reliability.
Power grid optimization
Quantum algorithms can work on large-scale combinatorial problems related to grid topology optimization, capacitor placement for stabilization purposes and fault detection with tremendous cost savings.
Energy market optimization
Quantum computing can make market-clearing algorithms more powerful, ensuring efficient energy trading and pricing. Real-time optimization of energy markets becomes feasible with quantum algorithms.
Unresolved problems of quantum computers
Even though certain advantages have already been obtained with quantum computers, there are still some issues to be addressed before reaching quantum supremacy over classical computers. Quantum random-access memory is still not capable of effectively encoding information in a quantum state and ensuring the right execution speed of quantum algorithms. Many smart-grid applications rely on a large set of qubits to run quantum algorithms, and controlling those qubits may be a very tough job, as they are extremely sensitive to the surrounding environment, such as temperature and noise; therefore, special ad hoc infrastructure must be provided. Furthermore, maintaining a large number of qubits entangled could prove a critical feat because of decoherence occurrence.
The current quantum computers are not error-free as classical computers are, which may create extra challenges in sensitive power system applications. Therefore, it is incumbent on designers to develop a universal fault-tolerant and error-correcting quantum computer for implementing arbitrary quantum algorithms with minimal effort.
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The post Quantum Algorithms Will Optimize Power Grid Efficiency appeared first on Power Electronics News.
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