ASEAN grid flexibility: Preparedness for grid integration of renewable energy

In 2015, ASEAN established a goal of increasing its renewable energy share in its energy portfolio from approximately 13–23% by 2025. Renewable electricity, especially intermittent and variable sources, presents challenges for grid operators due to the uncertain timing and quantity of electricity supply. Grid flexibility, the electric grid's ability to respond to changing demands and supply, now stands a key resource in responding to these uncertainties while maximizing the cost-effective role of clean energy. We develop and apply a grid flexibility assessment tool to assess ASEAN's current grid flexibility using six quantitative indicators: grid reliability, electricity market access; load profile ramp capacity; quality of forecasting tools; proportion of electricity generation from natural gas; and renewable energy diversity. We find that ASEAN nations cluster into three groups: better; moderately; and the least prepared nations. We develop an analytical ramp rate calculator to quantify expected load ramps for ASEAN in an integrated ASEAN Power Grid scenario. The lack of forecasting systems and limited electricity market access represent key weaknesses and areas where dramatic improvements can become cost-effective means to increase regional grid flexibility. As ASEAN pursues renewable energy targets, regional cooperation remains essential to address identified challenges. Member nations need to increase grid flexibility capacity to adequately prepare for higher penetrations of renewable electricity and lower overall system costs

Geospatial multi-criteria analysis for identifying high priority clean energy investment opportunities: A case study on land-use conflict in Bangladesh

Bangladesh is a globally important emerging economy with rapidly increasing energy demand. The Bangladeshi government's primary capacity expansion plan is to install 13.3 GW of new coal by 2021, including the 1.3 GW Rampal coal power plant to be developed in the Sundarbans. Inadequate geospatial and economic information on clean energy investment opportunities are often a significant barrier for policy makers. Our study helps fill this gap by applying a new method to assess energy investment opportunities, with focus on understanding land-use conflicts, particularly important in this context as Bangladesh is constrained on land for agriculture, human settlements, and ecological preservation. By extending a geospatial multi-criteria analysis model (MapRE) we analyze the cost of various renewable energy generation technologies based on resource availability and key siting criteria such as proximity to transmission and exclusion from steep slopes, dense settlements or ecologically sensitive areas. We find there is more utility-scale solar potential than previously estimated, which can be developed at lower costs than coal power and with minimal cropland tradeoff. We also find significant potential for decentralized roof-top solar in commercial and residential areas. Even with a conservative land use program that reserves maximum land for agriculture and human settlement, there is more renewable energy capacity than needed to support Bangladeshi growth. This study provides critical and timely information for capacity expansion planning in South Asia and demonstrates the use of geospatial models to support decision-making in data-limited contexts

ECONOMIC Potential of Renewable Energy in Vietnam's Power Sector

A bottom-up Integrated Resource Planning model is used to examine the economic potential of renewable energy in Vietnam’s power sector. In a baseline scenario without renewables, coal provides 44% of electricity generated from 2010 to 2030. The use of renewables could reduce that figure to 39%, as well as decrease the sector’s cumulative emission of CO2 by 8%, SO2 by 3%, and NOx by 4%. In addition,renewables could avoid installing 4.4GW in fossil fuel generating capacity, conserve domestic coal,decrease coal and gases imports, improving energy independence and security. Wind could become cost-competitive assuming high but plausible on fossil fuel prices, if the cost of the technology falls to 900 US$/kW

A general equilibrium analysis of demand side management programs under the clean development mechanism of the kyoto protocol

This paper analyzes the economic and environmental consequences of a potential demand side management program in Thailand using a general equilibrium model. The program considers replacement of less efficient electrical appliances in the household sector with more efficient counterparts. The study further examines changes in the economic and environmental effects of the program if it is implemented under the clean development mechanism of the Kyoto Protocol, which provides carbon subsidies to the program. The study finds that the demand side management program would increase economic welfare if the ratio of unit costof electricity savings to price of electricity is 0.4 or lower even in the absence of the clean development mechanism. If the program's ratio of unit cost of electricity savings to price of electricity is greater than 0.4, registration of the program under the clean development mechanism would be needed to achieve positive welfare impacts. The level of welfare impacts would, however, depend on the price of carbon credits the program generates. For a given level of welfare impacts, the registration of the demand side management program under the clean development mechanism would increase the volume of emission reductions.Energy Production and Transportation,Environmental Economics&Policies,Economic Theory&Research,Environment and Energy Efficiency,Energy and Environment

A Review of Electricity Demand Forecasting in Low and Middle Income Countries: The Demand Determinants and Horizons

With the globally increasing electricity demand, its related uncertainties are on the rise as well. Therefore, a deeper insight of load forecasting techniques for projecting future electricity demands becomes imperative for business entities and policy makers. The electricity demand is governed by a set of different variables or “electricity demand determinants”. These demand determinants depend on forecasting horizons (long term, medium term, and short term), the load aggregation level, climate, and socio-economic activities. In this paper, a review of different electricity demand forecasting methodologies is provided in the context of a group of low and middle income countries. The article presents a comprehensive literature review by tabulating the different demand determinants used in different countries and forecasting the trends and techniques used in these countries. A comparative review of these forecasting methodologies over different time horizons reveals that the time series modeling approach has been extensively used while forecasting for long and medium terms. For short term forecasts, artificial intelligence-based techniques remain prevalent in the literature. Furthermore, a comparative analysis of the demand determinants in these countries indicates a frequent use of determinants like the population, GDP, weather, and load data over different time horizons. Following the analysis, potential research gaps are identified, and recommendations are provided, accordingly

Opportunities and Challenges of Integrating Renewable Energy in Smart Grid System

AbstractSmart grid technology is the key for an efficient use of distributed energy resources. Noting the climate change becomes an important issue the whole world is currently facing, the ever increasing price of petroleum products and the reduction in cost of renewable energy power systems, opportunities for renewable energy systems to address electricity generation seems to be increasing. However, to achieve commercialization and widespread use, an efficient energy management strategy of system needs to be addressed. Recently, the concept of smart grid has been successfully applied to the electric power systems. This paper presents the study of integrating renewable energy in smart grid system. The introductory sections provide the role of renewable energy and distributed generation in smart grid system. Subsequent sections cover the concept of smart grid as well as benefits and barrier of smart grid renewable energy system. Pricing is a significant variable in success of renewable energy promotion. Thus, it is important to gain insight to renewable energy pricing by considering unique characteristics associated with renewable energy alternatives. A review of work done in renewable smart grid systems in recent years indicates the promising potential of such research characteristics in the future. This would be useful to developers and practitioners of renewable energy systems and to policy makers

A Co-optimization Model of Natural Gas Supply and Electric Power Systems

In Thailand, natural gas has been the primary source of fuel for power generation for the past few decades due to availability of indigenous resources. With continuous load growth and near depletion of domestic natural gas supply, renewable energy will play an increasing role in power industry in a close future. To achieve that, energy storage would become the key enabler. Therefore, this paper proposes a co-optimization steady-state model of a -coupled system of gas supply network and electric power system with integration of an energy storage device namely power-to-gas. The IEEE-14 bus power system coupled with the 20-node and 24 pipeline natural gas system is used to verify effectiveness of the proposed method through computer simulation. The results show the capability in maintaining the system variables within the statutory security limits and reducing power losses. Moreover, the proposed method has another feature that can optimally curtail loads of the two systems when experiencing stressful conditions

The Impact of Temperature Change on Energy Demand a Dynamic Panel Analysis

This paper presents an empirical study of energy demand, in which demand for a series of energy goods (Gas, Oil Products, Coal, Electricity) is expressed as a function of various factors, including temperature. Parameter values are estimated econometrically, using a dynamic panel data approach. Unlike previous studies in this field, the data sample has a global coverage, and special emphasis is given to the dynamic nature of demand, as well as to interactions between income levels and sensitivity to temperature variations. These features make the model results especially valuable in the analysis of climate change impacts. Results are interpreted in terms of derived demand for heating and cooling. Non-linearities and discontinuities emerge, making necessary to distinguish between different countries, seasons, and energy sources. Short- and long-run temperature elasticities of demand are estimated.Advertising, Media Industries, Broadcasting, Price Discrimination, Television, Radio, Differentiation..