Research Achievements

June 12, 2019 

Rewarding or penalizing consumers of electricity to balance its supply and demand - how cost effective is it, and what's the best way to do it?

Viewing electricity distribution and consumption as a large complex system with a lot of uncertainty, a group of researchers from institutions including Nagoya University, Hokkaido University and Tokyo University of Science have used a control theory viewpoint to develop a technology for both analysing and controlling consumer electricity demand that maximizes cost effectiveness. Based on predicting power generation cost and demand, their technology was successfully tested using real-world data, and provides guidelines for the design of both demand response and aggregators such as retailers.


The economic value of demand response that adjusts the power consumption has not been clarified. A control method for maximizing cost-effectiveness of demand response is developed. Using this method, the optimal power consumption can be calculated based on the prediction of the power generation cost and the demand.


Since the output of renewable energy such as photovoltaic generation tends to fluctuate, the power system can be viewed as a large-scale complex system with uncertainty. To stabilize the balance of supply and demand of electricity, we need an energy management system to control this. In recent years, energy management systems have been actively researched against the background of the liberalization of power and the spread of smart meters that visualize the power consumption. Koichi Kobayashi, associate professor at Hokkaido University, Shun-ichi Azuma, professor at Nagoya University, and Nobuyuki Yamaguchi, associate professor at Tokyo University of Science and others developed demand response analysis and control technologies focusing on time-varying power generation costs.


Demand response is one of the methods in energy management systems. Demand response is defined as "when the supply-demand balance is tight, consumers conserve the power consumption and change the power consumption pattern according to the setting of the electricity price or the payment of incentives (rewards)." The cost-effectiveness of this has not previously been clarified.


The introduction of "aggregators" that control the power consumption of consumers has attracted much attention. In this framework, aggregators trade between electric power companies and consumers, instead of direct trade between consumers and electric companies. Aggregators manage hundreds of consumers and control their power consumption in response to requests from electric companies. By the introduction of aggregators, control of the whole power system becomes easier.


During a typical day, the cost-effectiveness of demand response fluctuates depending on the demand and supply of electricity. It is expected that these fluctuations will become larger with the spread of renewable energy. Demand response is aimed at maintaining the balance between supply and demand. In the future, it will become important to evaluate the economic value of demand response, focusing on the power generation cost and the adjustment cost (the cost required to adjust power consumption). Furthermore, it is necessary to develop control strategies that maximize the economic value of demand response.


In order for demand response to produce economic value, the unit price of power generation cost needs to fluctuate greatly during the day. If the difference between the highest and lowest generation cost is large compared to the adjustment cost, then demand response produces economic value. In this research, more specifically, we derived the condition that "demand response produces economic value if the difference between the highest price and lowest price is more than twice the adjustment cost". Since it is a simple condition, it can also be used as a guide to calculate rewards to consumers.


Next, in order to maximize the economic value, a control method for demand response is developed based on model predictive control in which the optimal control strategy is found by prediction using a mathematical model. To show that the proposed method can work, a simulation was successfully carried out using real data from the Japan Electric Power Exchange to forecast the power generation cost and the power consumption.


The paper

Kodai Miyazaki, Koichi Kobayashi, Shun-Ichi Azuma, Nobuyuki Yamaguchi and Yuh Yamashita. "Design and Value Evaluation of Demand Response Based on Model Predictive Control",
IEEE Transactions on Industrial Informatics. Published online June 3, 2019, DOI: 10.1109/TII.2019.2920373



John Wojdylo,


About Nagoya University

Nagoya University has a history of about 150 years, with its roots in a temporary medical school and hospital established in 1871, and was formally instituted as the last Imperial University of Japan in 1939. Although modest in size compared to the largest universities in Japan, Nagoya University has been pursuing excellence since its founding. Six of the 13 Japanese Nobel Prize-winners since 2000 did all or part of their Nobel Prize-winning work at Nagoya University:  four in physics - Maskawa and Kobayashi in 2008, and Akasaki and Amano in 2014  - and two in Chemistry - Noyori in 2001 and Shimomura in 2008. In mathematics, Mori did his Fields Medal-winning work at Nagoya University. A number of other important discoveries have been made at Nagoya University, including the Okazaki DNA Fragments by Reiji and Tsuneko Okazaki in the 1960s; and depletion forces by Asakura and Oosawa in 1954.

In addition, Nagoya University currently engages in research and educational programs aimed at helping developing countries in Africa and Asia improve food security, nutrition and environmental conservation. For example, Nagoya University researchers have potentially solved the striga (witchweed) problem, which causes $13 billion damage annually in Africa to food crops like maize and sorghum. Field tests are now underway in Kenya. In Asia, local farmers are being trained by Nagoya University researchers in growing food crops more sustainably. And new rice varieties have been developed at Nagoya University that can feed more people and thereby reduce food scarcity in developing countries. Many other such programs are currently being undertaken by Nagoya University researchers.


About Nagoya

Nagoya is Japan's fourth-largest city with 2.2 million residents and third-largest metropolitan area after the Tokyo and Osaka urban areas. Nagoya's surrounding Aichi Prefecture has led Japan in industrial output since 1977. Greater Nagoya produces 51.7% of Japan's total automobile output and 45% of the country's auto parts. This represents 8.2% of global automobile production. The Greater Nagoya Area produces 27% of Japan's manufacturing output (versus 11% in Greater Tokyo and 10.2% in Greater Osaka) and 24% of Japan's exports. The Greater Nagoya area  is the hub of Japanese manufacturing industries, producing over 40% of major manufacturing categories such as automobiles, automobile parts, machine tools and aircraft parts. Nagoya Port is Japan's largest in terms of import and export tonnage and in terms of export value. The Greater Nagoya GDP is $US461 billion: as a country it would be 22nd in the world, below Poland and above Belgium (Japanese Cabinet figures, 2015).

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