A review of electricity load profile classification methods

With the electricity market liberalisation in Indonesia, the electricity companies will have the right to develop tariff rates independently. Thus, precise knowledge of load profile classifications of customers will become essential for designing a variety of tariff options, in which the tariff rates are in line with efficient revenue generation and will encourage optimum take up of the available electricity supplies, by various types of customers. Since the early days of the liberalisation of the Electricity Supply Industries (ESI) considerable efforts have been made to investigate methodologies to form optimal tariffs based on customer classes, derived from various clustering and classification techniques. Clustering techniques are analytical processes which are used to develop groups (classes) of customers based on their behaviour and to derive representative sets of load profiles and help build models for daily load shapes. Whereas classification techniques are processes that start by analysing load demand data (LDD) from various customers and then identify the groups that these customers' LDD fall into. In this paper we will review some of the popular clustering algorithms, explain the difference between each method

Electricity load profile classification using Fuzzy C-Means method

This paper presents the Fuzzy C-Means (FCM) clustering method. The FCM technique assigns a degree of membership for each data set to several clusters, thus offering the opportunity to deal with load profiles that could belong to more than one group at the same time. The FCM algorithm is based on minimising a c-means objective function to determine an optimal classification. The simulation of FCM was carried out using actual sample data from Indonesia and the results are presented. Some validity index measurements was carried out to estimate the compactness of the resulting clusters or to find the optimal number of clusters for a data set

Techno-economic feasibility study of solar photovoltaic power plant using RETScreen to achieve Indonesia energy transition.

Indonesia, a key player in the global energy transition, faces surging electricity demand and ambitious renewable energy goals. In response, the government introduced a new regulation about renewable energy tariffs, including tariffs for photovoltaic (PV). However, there remains a gap in the academic literature regarding PV power plant feasibility studies under these tariffs. To address this gap, this study investigates the feasibility of a utility-scale solar photovoltaic (PV) power plant in Indonesia, focusing on the newly implemented renewable energy tariffs based on Independent Power Producers (IPPs) and Indonesia's state-owned electricity company (PLN) perspectives. Five scenarios were developed based on the proposed 26 MW solar power plant on Nias Island utilizing RETScreen software. The results showed that based on the IPP perspective, the newly implemented renewable energy tariff was inadequate to make the project feasible, however, an introduction of a 10 USD/t CO2 emission incentive would make the project financially viable for IPPs. Therefore, it is recommended to introduce emission incentives as a strategic approach to attract investors and stimulate investment in Indonesia's PV power plants market, to accelerate Indonesia's energy transition. Conversely, the results also showed that the project is very profitable for PLN due to the significant cost-savings from the de-dieselization, leading to a reduction in the average generation cost for Nias

The Challenges and Opportunities of Renewable Energy Source (RES) Penetration in Indonesia: Case Study of Java-Bali Power System

Nowadays, the integration of renewable energy sources, especially grid-connected photovoltaic, into electrical power systems, is increasing dramatically. There are several stimulants especially in the Java-Bali power system, including huge solar potential, a national renewable energy (RE) target, regulation support for prosumers, photovoltaic technology development, and multi-year power system planning. However, significant annual photovoltaic penetration can lead to critical issues, including a drop of netload during the day, ramping capability, and minimal load operation for thermal power plants. This study analyses the duck curve phenomenon in the Java-Bali power system that considers high shares of the baseload power plant and specific scenarios in photovoltaic (PV) penetration and electricity demand growth. This study also analyses future netload, need for fast ramping rate capability, and oversupply issues in the Java-Bali power system. The results showed that the duck curve phenomenon appears with a significant netload drop in the middle of the day because of high power generation from grid-connected PV. Furthermore, the need for fast ramp rate capability is critical for a higher peak load combined with the lowest netload valley. Moreover, the significant load growth with high grid-connected PV penetration level caused unit commitment issues for thermal power plants as baseload operators