DOE Pushes Simulations to Safeguard Consumers During Malampaya Scheduled Maintenance

Wazzup Pilipinas!

Energy Secretary Alfonso G. Cusi pushes to firm up measures by each concerned agencies and power stakeholders during the course of the Malampaya maintenance repair from 28 January to 16 February 2017 to ensure readiness of all stakeholders and by way of ensuring consumers are protected from any market abuses.

The Department of Energy (DOE) will closely coordinate with all Malampaya stakeholders including the Malampaya Consortium, the National Grid Corp. of the Philippines (NGCP), Manila Electric Company (MERALCO), Power Sector Assets and Liabilities Management (PSALM) Corp., Philippine Electricity Market Corp. (PEMC) and power generation companies and other distribution utilities to ensure sufficiency of power supply during the shutdown period.

Initially, Sec. Cusi instructed that “Materials, equipment and other assets necessary for the maintenance of Malampaya should all be delivered by January 15 and these should be ready for deployment to make sure that the repair activities should remain on schedule.”

The DOE noted that during the maintenance activities, some power plants are on scheduled maintenance as well. Based on initial study, the lowest projected power supply capacity during the period stood at 8,747 MW on 18 February, while highest demand is projected to reach 8,610 MW on 9 February.

To ensure sufficient power supply, the DOE requires the affected natgas power plants to run on alternative or replacement fuel but it is more expensive than natural gas. Natural Gas as fuel only costs around P4/kilowatt-hour and replacement fuel, such as diesel which costs around P6-P8/kWh.

Sec. Cusi then emphasized that “the Department is exploring all possible options and remedies to maximize protection for consumers.”

Moreover, to augment power supply, the DOE readies the Interruptible Load Program (ILP) in which around 900MW are enrolled.

Further, the DOE also encourages consumers to practice effective “demand-side management.”

The Secretary of Energy also enjoined that “The public should also be proactive in computing the effect of price adjustments to be provided in the simulations given by the agencies concerned to for consumers to practice efficiency measures to avoid price shocks.”

NEC Automates Large-Scale Data Prediction for Business Systems

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NEC Corporation announced the development of a “Predictive Analytics Automation Technology” that completely automates the process for large-scale data predictive analytics performed by relational databases that are widely used for business systems.

Currently, when analyzing relational databases composed of multiple databases, a great deal of work is required for processes that include the discovery and association of complex relationships between databases by skilled scientists, as well as the adjustment of prediction models by machine learning. Moreover, there is a shortage of well-trained data scientists capable of handling the rapidly growing need for advanced data analysis. As a result, there is heavy demand for highly accurate analysis methods that quickly perform large-scale data analysis and are user friendly for non-experts.

NEC’s Predictive Analytics Automation Technology, developed as part of its cutting-edge portfolio of artificial intelligence (AI) technologies, NEC the WISE (*1), automates the series of processes for predictive analysis, from the extraction and design of a data item (feature that is effective for analysis, to the creation of the most suitable predictive model. As a result, even if an individual lacks advanced data analysis skill, it is possible to perform predictive analysis in a short time that is equal to or better than the accuracy of a well-trained data scientist.

Joint trials carried out by Sumitomo Mitsui Banking Corporation and NEC (*2) confirmed that this technology successfully maintained accuracy and reduced predictive analysis to just one day, in comparison to conventional methods that require 2-3 months of work by a professional analyst.

“This new technology can contribute to the acceleration of business decisions, including strategic planning, hypothesis verification and policy implementation, based on the discovery of new potential needs,” said Akio Yamada, general manager, Data Science Research Laboratories, NEC Corporation. “We aim to provide this technology as a service within the 2017 fiscal year for companies seeking to independently perform effective big data analysis.”


Key features of this technology include the following:

1) Strengthens NEC’s “Automatic Feature Design Technology” and automatically discovers feature quantities for relational data bases

This technology strengthens the “Automatic Feature Design Technology” that NEC announced in 2015 and automatically designs the feature for the relational databases that are widely used for business systems.

Based on the relationship of multiple databases, AI searches for and discovers hypotheses at high speed for combinations of data items (feature quantities) that are effective for prediction. Moreover, the system automatically creates the large number of queries to generate features from the databases.

As a result, the time and labor for analysis is significantly shortened since neither large amounts of work are necessary for feature hypothesis planning, which is dependent on analysis experience and knowledge about data, nor are database operations required for creating feature quantities. Furthermore, in comparison to manual analysis, a great deal more hypothesis searching can be executed in a short time, more accurate analysis results can be achieved, and new findings that may not have been noticed by manual processes may be discovered.


2) The “Automatic Prediction Model Design Technology” enables the automatic design of the most suitable model for the data.

Based on feature data, a wide range of prediction models are created using various machine learning methods, such as NEC’s “Heterogeneous Mixed Learning,” logistic regression and decision trees. The prediction model that provides the most suitable analysis results for a user’s goals is selected. Reasons for the predicted value calculated by the prediction model are also provided.

Since users are able to understand the basis of the prediction, they are also able to make the most suitable judgement and implement the most appropriate plan in response to a situation.

NEC also developed a Graphic User Interface (GUI) for intuitive operation, where a display provides users with easy to understand instructions to search for feature quantities and create predictive models.

Power Restored to More Than 1 Million Households in Typhoon Nina-Affected Areas

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With its 24/7 power restoration efforts, the energy family, spearheaded by the Department of Energy (DOE) together with its private institution partners, has resumed electricity supply to 1,003,519 households or about 57% re-energization of Typhoon Nina-affected areas as of 4 January 2017.

Energy Secretary Alfonso G. Cusi said, “After restoring power in town centers and nearby communities, our ground personnel are working round the clock, even double time to bring back the power supply to all affected households in Southern Luzon and Bicol regions.”

Specifically, Cusi relayed, “We, through the National Electrification Administration (NEA), already deployed 982 personnel from 52 participating energy companies and distribution utilities through Task Force Kapatid to help restore power supply in the affected 99 municipalities and 7 cities.”

On transmission facilities, the National Grid Corporation of the Philippines reported that it deployed close to 600 personnel working 24/7 to attain 100% restoration of transmission lines by today. NGCP is focusing on the last three transmission service connected to NGCP customers that are still undergoing rehabilitation as of yesterday (3 January), which include Tabaco 20 Megavolt Ampere (MVA) Load-End Substation (LES) serving Albay Power & Energy Corp. (APEC); Malinao 5 MVA LES serving APEC; and Albay Agro-Industrial Development Corp. (ALINDECO) LES serving AboitizPower Renewable Incorporated’s Tiwi Geothermal Plant.

The following is the status of restoration in the affected provinces as of 4 January 2017:

A) On-Grid Areas:

For Sorsogon, the NEA reported that 46,366 households have been restored under the franchise area of Sorsogon II Electric Cooperative (SORECO II), while SORECO I is currently undergoing clearing and restoration of their distribution facilities.

Albay province, through the report of Albay Power and Energy Corporation (APEC), has restored 31% of all affected areas or a total of 68,668 households.

In Camarines Norte, all power facilities are up and running supplying electricity to its locals, while in Camarines Sur, there are still 296,219 households to be energized spread over the franchise areas of four (4) electric cooperatives in the province.

As reported by NEA, Quezon Province has reached 50% restoration status for all typhoon-affected areas, especially under the Quezon I Electric Cooperative.

For Batangas, NEA reported that Batangas II Electric Cooperative (BATELEC II) has attained 100% restoration, while BATELEC I stood at 90% or around 16,000 remaining households to be energized.


B) Off-Grid Areas:

In the hard-hit province of Catanduanes, the National Electrification Administration (NEA) reported that the First Catanduanes Electric Cooperative, Inc. (FICELCO) has counted 48,000 affected households undergoing restoration. Moreover, the National Power Corporation (NPC) reported that all affected government-owned power plants in the province are already in operation with a dependable capacity of 7.8 megawatts (MW), while among the privately-owned generation facilities totaling to 8.5 MW, only the 2.8 MW Sun West Corporation Hydroelectric Power is still non-operational due to flood water.

For Mindoro Island, NEA reported that 99% of households in Occidental Mindoro have been restored, while Oriental Mindoro stood at 68% re-energization or 120,682 households have experienced resumption of power supply.

While Marinduque’s generation and transmission facilities have been restored by NPC, there are still 43,200 affected households that are yet to be restored by Marinduque Electric Cooperative (MARELCO) as NEA reported.

All other off-grid areas (Masbate, Batangas, Camarines Sur and Marinduque Mini-Grids) under the supervision of NPC are back in operation awaiting restoration of distribution facilities.

“We’ve already added personnel and augmented assets through private institutions and we are continuously monitoring the progress of power restoration,” said Cusi.

Cusi concluded "We are exhausting all possible remedies to bring back the power in the affected areas the soonest possible. We cannot leave our kababayans until we have lighted each and every household affected by Typhoon Nina.”