Space and time: Wind in an investment planning model

Investment planning models inform investment decisions and government policies. Current models do not capture the intermittent nature of renewable energy sources, restricting the applicability of the models for high penetrations of renewables. We provide a methodology to capture spatial variation in wind output in combination with transmission constraints. The representation of wind distributions using stochastic approaches or using extensive historic data sets exceeds computational constraints for real world application. Hence we restrict the amount of input data, and use bootstrapping to illustrate the robustness of the results. For the UK power system we model wind deployment and the value of transmission capacity.     

Internalizing externalities into capacity expansion planning: The case of electricity in Vietnam

This paper examines the impacts of including external costs such as environmental and health damages from power production on power generation expansion planning in Vietnam. Using the MARKAL model and covering a 20-year period to 2025, the study shows that there are substantial changes in the generation structure in favor of renewable energy technologies and other low emitting technologies. These changes lead to a reduction in fossil fuel requirements, and consequently, a reduction of CO₂, NO_x, SO₂, and PM emissions which could be expected to also reduce the associated environmental and human health impacts. The avoided external costs would be equivalent to 4.4 US cent/kWh. However, these gains are not free as the additional electricity production cost would be around 2.6 US cent/kWh higher if the switch to more expensive, but lower emitting technologies were made. The net benefit of internalizing these externalities is thus around 1.8 US cent/kWh.     

Analysis of the impact of electricity grid interconnection between Korea and Japan—Feasibility study for energy network in Northeast Asia

This study analyzes the impact of an electricity grid interconnection between Korea and Japan on their energy systems. Both countries seriously consider energy security as the most important policy issue because of a lack of domestic energy resources. In addition, public concern for the environment is recently rising up in response to the global warming. Electricity grid interconnection has strong potential to cope with such complicated problems cost-effectively. We have developed the interconnection model, which includes the electricity grid interconnection between the electricity sectors of Korea and Japan, considering both technological and economic efficiency. The result of the study reveals the significant cost-effectiveness of the interconnection, in particular, under stringent condition such as nuclear phase-out in Japan and CO₂ emission target in Korea and Japan. In the case that Japan's nuclear power plants will be phased out, the interconnection attains further cost reduction of constructing substitutive thermal power plants. On the other hand, when Korea and Japan set a joint CO₂ emission target, it achieves the emission target more efficiently than they reduce the emission individually.     

Successful renewable energy development in a competitive electricity market: A Texas case study

The development of renewable energy in markets with competition at wholesale and retail levels poses challenges not present in areas served by vertically-integrated utilities. The intermittent nature of some renewable energy resources impact reliability, operations, and market prices, in turn affecting all market participants. Meeting renewable energy goals may require coordination among many market players.     

The impact of ICT investment and energy price on industrial electricity demand: Dynamic growth model approach

The authors investigate the effects of information and communications technology (ICT) investment, electricity price, and oil price on the consumption of electricity in South Korea's industries using a logistic growth model. The concept electricity intensity is used to explain electricity consumption patterns. An empirical analysis implies that ICT investment in manufacturing industries that normally consume relatively large amounts of electricity promotes input factor substitution away from the labor intensive to the electricity intensive. Moreover, results also suggest that ICT investment in some specific manufacturing sectors is conducive to the reduction of electricity consumption, whereas ICT investment in the service sector and most manufacturing sectors increases electricity consumption. It is concluded that electricity prices critically affect electricity consumption in half of South Korea's industrial sectors, but not in the other half, a finding that differs somewhat from previous research results. Reasons are suggested to explain why the South Korean case is so different. Policymakers may find this study useful, as it answers the question of whether ICT investment can ultimately reduce energy consumption and may aid in planning the capacity of South Korea's national electric power.     

Development of a scalable infrastructure model for planning electricity generation and CO2 mitigation strategies under mandated reduction of GHG emission

In a power-generation system, power plants as major CO₂ sources may be widely separated, so they must be connected into a comprehensive network to manage both electricity and CO₂ simultaneously and efficiently. In this study, a scalable infrastructure model is developed for planning electricity generation and CO₂ mitigation (EGCM) strategies under the mandated reduction of GHG emission. The EGCM infrastructure model is applied to case studies of Korean energy and CO₂ scenarios in 2020; these cases consider combinations of prices of carbon credit and total electricity demand fulfilled by combustion power plants. The results highlight the importance of systematic planning for a scalable infrastructure by examining the sensitivity of the EGCM infrastructure. The results will be useful both to help decision makers establish a power-generation plan, and to identify appropriate strategies to respond to climate change.     

Implications of private sector participation in power generation—a case study from India

India suffers from widespread shortages of electricity supply. These shortages, among others, are detrimental to the economic growth. The prospects for the next decade do not seem to be much brighter. Efforts in expanding generation capacity by the state-owned electric utilities are hampered by severe resource constraints. Against this backdrop, to mobilize additional resources to help bridge the gap in demand and supply, the Government of India formulated a policy in 1991 with the objective to encourage greater investment by private enterprises in the electricity sector. To study the implications of such an initiative on various stakeholders, viz., public utilities, consumers and private sector, the present paper tries to analyse issues like planned rationing, guarantees to private sector, backing down of existing capacity. Using the state of Karnataka (in Southern India) as a case study, the paper develops multiple scenarios using an integrated mixed integer-programming model. The results show the advantage of marginal non-supply (rationing) of electricity in terms of achieving overall effective supply demand matching as well as providing economic benefits to the state that could be generated through cost savings. The results also show the negative impacts of high guarantees offered to the private sector in terms of the opportunity costs of reduced utilization of both the existing and the new public capacity. The estimated generation losses and the associated economic impacts of backing down of existing and new public capacity on account of guarantees are found to be significantly high. For 2011–12, depending on the type of scenarios, the estimated generation and economic losses are likely to be in the range of 3200–10,000 GWh and Rs. 4200–13,600 million respectively. The impact of these losses on the consumers could be in terms of significant increase in energy bills (in the range of 19–40% for different scenarios) due to rise in tariffs.     

Electricity market auction settings in a future Danish electricity system with a high penetration of renewable energy sources - A comparison of marginal pricing and pay-as-bid

The long-term goal for Danish energy policy is to be free of fossil fuels through the increasing use of renewable energy sources (RES) including fluctuating renewable electricity (FRE).The Danish electricity market is part of the Nordic power exchange, which uses a Marginal Price auction system (MPS) for the day-ahead auctions. The market price is thus equal to the bidding price of the most expensive auction winning unit. In the MPS, the FRE bid at prices of or close to zero resulting in reduced market prices during hours of FRE production. In turn, this reduces the FRE sources’ income from market sales. As more FRE is implemented, this effect will only become greater, thereby reducing the income for FRE producers.Other auction settings could potentially help to reduce this problem. One candidate is the pay-as-bid auction setting (PAB), where winning units are paid their own bidding price.This article investigates the two auction settings, to find whether a change of auction setting would provide a more suitable frame for large shares of FRE. This has been done with two energy system scenarios with different shares of FRE.From the analysis, it is found that MPS is generally better for the FRE sources. The result is, however, very sensitive to the base assumptions used for the calculations.     

Impact on power planning due to demand-side management (DSM) in commercial and government sectors with rebound effect—A case study of central grid of Oman

This paper presents the results of a study that estimated the DSM energy saving and load management potential in commercial and government/institutional sectors in Oman (central grid area) and evaluated its impact on generation capacity and energy savings. The end-use (lighting and air-conditioning) energy consumption data have been collected in two major segments of the commercial sector for simplicity and to save time and money. Another unique aspect of the study is the inclusion of the energy savings, in transmission and distribution (T&D) losses that are estimated by using generation expansion planning approach. The study has found that DSM is financially beneficial from customers’ point of view as the discounted payback period of investment in efficient lighting and air-conditioning is between 4 and 12 years of the surveyed sample. From the utility point of view the capacity saving at the horizon year is between 372 and 596 MW and the overall energy saving for the whole planning horizon is about 29–44 TWh. The total avoided cost in generation and capacity saving is somewhere between 416 and 597 million dollars.     

The causal relationship between electricity consumption and economic growth in a Gaming and Tourism Center: The case of Macao SAR, the People’s Republic of China

A number of Asian cities decided to establish gaming and resort facilities in order to capitalize on the growing number of gamblers and their family members in Asia. In doing so, they expect to sustain economic growth but, on the other hand, will consume a considerable amount of energy. Nevertheless, the causal relationship between economic growth and electricity consumption in this type of service-oriented territories has never been investigated. Using the historical data obtained from the Government of Macao SAR, we found that electricity consumption and economic growth in terms of gross domestic product are co-integrated for the period of 1999 Quarter 1-2008 Quarter 4. Moreover, vector error correction (VEC) models indicated a lack of short-run relationships but showed that there was a long-run equilibrium relationship between electricity consumption and gross domestic product. The accuracy of VEC models was assessed by using the mean squared error and the mean absolute error. The error analysis shows that VEC models reproduced time series of gross domestic product and electricity consumption in difference form accurately.     

Research and deployment priorities for renewable technologies: Quantifying the importance of various renewable technologies for low cost,high renewable electricity systems in an Australian case study

This study aims to identify research priorities to enable low cost, high renewable power systems. An evolutionary program optimises the mix of technologies in 100% renewable energy portfolios (RE) in the Australian National Electricity Market. Various technologies are reduced in availability to determine their relative importance for achieving low costs. The single most important factor is found to be the integration of large quantities of wind; therefore wind integration is identified as a research priority. In contrast, photovoltaics are found to “saturate” the system at less than 10% of total energy (in the absence of storage or demand management, installation of further photovoltaics does not contribute significant further value). This indicates that policies to promote utility-scale photovoltaics should be considered in partnership with complementary measures (such as demand side participation and storage). Biofuelled gas turbines are found to be important; a complete absence of bioenergy increases costs by AU$20–30/MWh, and even having only 0.1 TWh per year of bioenergy available reduces average costs by AU$3–4/MWh. Limits on the non-synchronous penetration (NSP) are found to be relatively expensive, suggesting a significant research priority around finding alternative approaches to providing synchronous services, such as inertia. Geothermal and concentrating solar thermal technologies do not appear essential as long as sufficient wind and peaking bioenergy is available.     

Decarbonization synergies from joint planning of electricity and hydrogen production: A Texas case study

Hydrogen (H₂) shows promise as an energy carrier in contributing to emissions reductions from sectors which have been difficult to decarbonize, like industry and transportation. At the same time, flexible H₂ production via electrolysis can also support cost-effective integration of high shares of variable renewable energy (VRE) in the power system. In this work, we develop a least-cost investment planning model to co-optimize investments in electricity and H₂ infrastructure to serve electricity and H₂ demands under various low-carbon scenarios. Applying the model to a case study of Texas in 2050, we find that H₂ is produced in approximately equal amounts from electricity and natural gas under the least-cost expansion plan with a CO₂ price of $30–60/tonne. An increasing CO₂ price favors electrolysis, while increasing H₂ demand favors H₂ production from Steam Methane Reforming (SMR) of natural gas. H₂ production is found to be a cost effective solution to reduce emissions in the electric power system as it provides flexibility otherwise provided by natural gas power plants and enables high shares of VRE with less battery storage. Additionally, the availability of flexible electricity demand via electrolysis makes carbon capture and storage (CCS) deployment for SMR cost-effective at lower CO₂ prices ($90/tonne CO₂) than for power generation ($180/tonne CO₂). The total emissions attributable to H₂ production is found to be dependent on the H₂ demand. The marginal emissions from H₂ production increase with the H₂ demand for CO₂ prices less than $90/tonne CO₂, due to shift in supply from electrolysis to SMR. For a CO₂ price of $60/tonne we estimate the production weighted-average H₂ price to be between $1.30–1.66/kg across three H₂ demand scenarios. These findings indicate the importance of joint planning of electricity and H₂ infrastructure for cost-effective energy system decarbonization.     

Model‐based approach for planning renewable energy transition in a resource‐constrained electricity system—A case study from India

Globally, electricity systems are going through transitions. The contributions from renewable energy‐based power generation, both in installed capacity and electricity generation, are moving from marginal to the mainstream. India is not an exception; it is aggressively pursuing this transition by fixing steep targets for renewable capacity additions. While the cost of renewable energy sources is expected to fast reach grid parity, the policy interventions play a critical role in ramping up the efforts to support the proposed investments in renewable capacity and renewable electricity generation. In this respect, this research attempts to analyze the effectiveness of renewable energy policies such as Renewable Purchase Obligation (RPO) and Renewable Energy Certificate mechanisms in tapping the renewable energy potential in India. We propose a mixed‐integer linear programming model‐based approach to evaluate the effectiveness of the above interventions in the Indian context. The model is developed and validated as a low carbon electricity planning tool to optimally meet the dynamic electricity demand and RPO targets as well as to manage the unmet total electricity demand and RPO targets. The Karnataka state electricity system (a state in south India) is chosen as a case study. The results suggest that Karnataka Electricity System is moving toward a sustainable renewable energy future even without any support from nonsolar Renewable Energy Certificate policy. However, policy interventions are critical for optimally utilizing the solar generation capacity.     

An hourly solar radiation model under actual weather and terrain conditions: A case study in Heihe river basin

This paper describes an hourly incident solar radiation model, which could be used to estimate long-term global radiation, direct radiation and diffuse radiation with high spatial and temporal resolution under its de facto weather and terrain in large regions. The model is based on parameterized radiation transfer theory, and has referred to some data from the NCEP/NCAR (National Centers Environmental Prediction/National Center for Atmospheric Research) and some information about topography. The model was successfully used to calculate hourly instantaneous solar irradiance by a spatial resolution of 1 km×1 km in Alberts projection, in the Heihe river basin with a drainage area of 130,000 km² in 2002. Now that only observed global radiation data at three automatic stations is available in Heihe river basin, global radiation at the three stations is used to validate the model. The three automatic stations are deployed in the mountain (Xishui), in the oasis (Linze), and in the desert area (Erjinaqi), respectively. The measured hourly instantaneous global radiation data do not comply with the calculated series at Xishui, with a determination coefficient R²=0.71$R^2=0.71$. While at Linze and Erjinaqi stations, the determination coefficients are 0.90 and 0.91, respectively. The main reason why large errors are observed at Xishui station is that total cloud percent data from the NCEP/NCAR do not have a high spatial and temporal resolution. Also the spatial resolution of the observed data is not consistent with the calculated values. According to the model numerical test, topography is an important factor affecting model results on uneven land surfaces. Besides, in arid desert regions with even land surfaces, the 6 hourly model results agree with NCEP/NCAR global radiation data and measured data well.     

Reinforcement learning for electricity dispatch in grids with high intermittent generation and energy storage systems: A case study for the Brazilian grid

Intermittent energy sources such as wind and solar have recently been growing a lot faster than dispatchable energy sources in Brazil, which made investments in energy storage systems become an attractive possibility in the country. Current operational policies for energy dispatch do not consider storage systems and need adjustments to fit this technology. With this motivation, we use reinforcement learning techniques to develop policies for managing storage systems in a grid that can handle time-varying inputs and loads, with rolling forecasts. We use a deterministic lookahead (DLA) policy which has been parametrically modified to perform well in the presence of uncertain forecasts. For realistic simulations, the base model considers important characteristics in a grid that influence the interaction between scheduling and real-time operation such as power and ramping capacities, notification times, and stochastic forecasts. The parametric modification with tunable parameters allows an optimal balance between two conflicting services provided by the storage system: time-shifting and spinning reserves. Optimal reserves ranged from 35% to 100%, depending on the tested dataset, which shows the importance of tuning. Differently from stochastic lookahead policies, which are computationally expensive, parameterized DLA policies can be applied to real-time operation after being optimized in a stochastic base model.     

Market power in a coal-based power generation sector: The case of Poland

The paper presents an analysis of market power in the Polish power sector. The study is carried out for the structure that was established by the last consolidation undertaken by the government in 2007, using a game theoretic model of the power generation market (the PolMark model). The model is run under five scenarios and eight cases. The scenarios distinguish between assumptions on strategic behaviour, whereas the cases distinguish assumptions on coal prices. The following measures are discussed in this study: electricity prices, production volumes, consumer and producer surpluses, dead weight welfare loss, CO₂, SO₂, NO_x emissions and fuel supplies to power producers. The results confirm that the potential to exert market power in the Polish power generation sector may influence significantly electricity prices and production volumes. The analysis indicates that under the competitive scenario the average wholesale electricity price would be approximately 14.7% lower and the production would be 6.7% higher when compared to the reference scenario. Furthermore, apart from surplus transfer between producers and consumers, the dead weight loss was estimated at the level of 123.6 M€. This value reflects the net social loss resulting from uncompetitive market equilibrium.     

An energy-based evaluation of the matching possibilities of very large photovoltaic plants to the electricity grid: Israel as a case study

We present the results of a number of PV-grid matching simulations performed using hourly generation data from the Israel Electric Corporation (IEC) for the year 2006, together with corresponding meteorological data from Sede Boqer in the Negev Desert. The principal results of this investigation are: (1) the effective flexibility factor (ff) of the IEC grid was close to ff=0.65, but with a different plant operating strategy, ff could have been considerably higher; (2) for ff=0.65, the largest no-dump PV system could have provided only 2.7% of the annual demand, but for higher flexibilities – up to ff=1 – the percentage penetration could be as high as 17.4%; (3) considerable improvement in penetration can result by relaxing the “no-dump” criterion initially imposed on the PV system; (4) using the IEC's existing plant types, additional penetration can be expected by re-scheduling part of the base-load generating capacity to anticipate expected solar input; (5) for a radically decreased grid flexibility – that might result from IEC decisions about future generator purchases – the required employment of massive amounts of storage would render the potential contribution of PV to be insignificant.     

Logistics cost analysis of rice straw pellets for feasible production capacity and spatial scale in heat utilization systems: A case study in Nanporo town,Hokkaido, Japan

Rice straw is a promising renewable energy source because it is abundantly available in Asia. This study conducted a case study of logistics cost analysis for rice straw pellets by considering all stages in the supply chain to define the main factors affecting the selling price of rice straw pellets: collection (job-commission or employment of part-time workers), transportation, storage (vinyl greenhouses or storage buildings with larger capacity), pelletizing, and delivery to users with biomass boilers. The selling price was found to be strongly dependent on the production capacity because the investment cost for the pellet production facility had a significant effect of economies of scale. A production capacity of larger than 1500 t y⁻¹ is required for rice straw pellets to compete with wood pellets and fossil fuels in the studied Japanese context if the subsidy rate for the investment is 50%, part-time workers conduct the collection, and rice straw is stored in the storage buildings. Our sensitivity analysis also showed an economically feasible spatial scale: for example, rice straw should be collected within a 20 km radius and the users should be within a 38 km radius when the production capacity is 1500 t y⁻¹. In addition, other critical factors related to the collection of rice straw from the paddy fields and transportation of rice straw rolls to storage were identified as planning factors to further reduce the total logistics cost of rice straw pellets.     

Compound microgrid installation operation planning of a PEFC and photovoltaics with prediction of electricity production using GA and numerical weather information

A fuel cell microgrid with photovoltaics effectively reduces greenhouse gas emission. A system operation optimization technique with photovoltaics and unstable power is important. In this paper, the optimal operation algorithm of this compound microgrid is developed using numerical weather information (NWI) that is freely available. A GA (genetic algorithm) was developed to minimize system fuel consumption. Furthermore, the relation between the NWI error characteristics and the operation results of the system was clarified. As a result, the optimized operation algorithm using NWI reduced the energy cost of the system.     

Techno-economic modelling of water electrolysers in the range of several MW to provide grid services while generating hydrogen for different applications: A case study in Spain applied to mobility with FCEVs

The use of hydrogen as energy carrier is a promising option to decarbonize both energy and transport sectors. This paper presents an advanced techno-economic model for calculation of optimal dispatch of large-scale multi MW electrolysis plants in order to obtain a more accurate evaluation of the feasibility of business cases related to the supply of this fuel for different end uses combined with grid services' provision. The model is applied to the Spanish case using different scenarios to determine the minimum demand required from the FCEV market so that electrolysis facilities featuring several MW result in profitable business cases. The results show that grid services contribute to the profitability of hydrogen production for mobility, given a minimum but considerable demand from FCEV fleets.