Investment In New Generation Capacity Research Articles

Into a cooler future with electricity generated from solar photovoltaic

SummaryThe fast-growing global cooling demand due to income growth in tropical countries necessitates substantial investments in new generation capacity. Despite the synergy between the temporal behavior of cooling demand and solar PV production, it is not clear whether the increased cooling demand will make solar PV more cost-effective or less so. We use a capacity expansion model to investigate the cost-effectiveness of investing in solar PV to meet the electricity demand linked to cooling for seven different regions under various CO2 emission targets. Solar PV plays a dominant role in meeting the additional electricity demand for cooling, and the share of solar PV in the additional generation capacity ranges from 64% to 135%. Additionally, powering electric cooling with mainly solar PV is cheaper than powering the rest of the demand. These results suggest that solar PV may comprise the backbone of electricity supply for cooling in the future electricity system.

The potential of industrial electricity savings to reduce air pollution from coal-fired power generation in China

Coal-intensive power supply systems, along with a fast-growing electricity demand driven by industry has caused serious air pollution and health concerns. These concerns are particularly prominent in countries where electricity use is likewise dominated by industry and heavily dependent on coal-based electricity. A more efficient industry and coal-free electricity systems are the core components of the United Nations 2030 Agenda for Sustainable Development. Previous studies rarely reflect on the impacts of the electricity savings of industrial consumers on the electricity supply sector with respect to future air emission changes, and also neglect the potential benefits of reducing investments in new generation capacity. Here, a comprehensive modeling framework is newly developed to quantify the connections of electricity savings, coal-based electricity systems, air pollutant emissions, and control investments in China, a country exposed to poor air quality. The modeling framework includes 175 energy efficiency technologies (covering multiple industrial sectors) and detailed information of power generation units (thermal efficiency, environmental performance, and lifespan), and allows for unit-by-unit assessment. We find that industrial efficiency improvements can significantly decrease the dependence on coal-fired power generation, particularly the most polluting power fleet. Efficient use of electricity in industry can drive all small high-polluting coal generation units (i.e. units below 300 MW, in total 753 units) to be phased out and effectively curb less efficient coal-fired plants to come online in China. Meanwhile, the air pollutant emissions can be significantly avoided because of the closed coal-fired power units. Developed cost portfolios demonstrate that improving industrial energy efficiency is more cost-effective than installing flue gas controls in coal-fired plants. We further reveal that a sustainable industry could contribute to climate change mitigation even if less remarkable than air quality improvement, while enabling the expansion of intermittent renewable power supply.

Coordination of risk-based generation investments in conventional and renewable capacities in oligopolistic electricity markets: A robust regulatory tool

Investment in new generation capacity is considerably affected by issues such as regulatory-determined incentives, techno-economic uncertainties and financial risks. In addition, increased penetration of renewables such as wind capacities resulting in decreased market prices, leads to the augmented risk of investing in conventional generations such as thermal technologies, which may hamper generation adequacy. Thus, to meet regulatory goals for adequacy and environmental considerations, regulators should determine investment incentives considering targets for techno-environmental issues and generation investors’ risks. So, this paper presents a bi-level robust regulatory model, in which regulator in the first level designs incentives considering generation companies’ (GENCOs’) investment response to regulatory decisions. In the second level, a robust game-theoretic model is considered to capture interactions between risk-averse GENCOs, facing uncertainties such as rivals’ behavior and nondispatchable generations. The effectiveness of proposed model is demonstrated by IEEE-RTS and ERCOT test systems and the results are compared with those obtained in the deterministic cases. As the results show, capacity payments and feed-in premiums should be coordinately designed to meet regulatory targets for techno-environmental conditions. Besides, more levels of uncertainties lead to designing more levels of investment incentives with respect to the deterministic case. Moreover, the more is the level of GENCOs’ risk-aversion, the more is the cost of designed incentives for promising regulatory targets considering GENCOs’ risk-hedging.

The marginal-cost pricing for a competitive wholesale district heating market: A case study in the Netherlands

District heating represents a viable way to reduce carbon dioxide emissions in the built environment. This paper aims to assess the extent to which the market revenues of multiple heat production technologies can cover their fixed costs in a competitive wholesale district heating market. Marginal-cost pricing is applied in a case study of the Netherlands. A linear programming model incorporating heat supply and demand is developed to obtain hourly dispatch and heat market prices. It is concluded that low carbon heat generation technologies tend to have low short-run marginal costs. All examined heat producers have an under-recovery of fixed costs in a range between 60% and 90% except the waste incineration combined heat and power plant. It has an overall return on investment of 44% and 12% within the reference and heat pump scenario respectively. Although marginal-cost pricing may ensure cost-efficient dispatch, the market revenues are far from enough to recoup the investment costs for the majority of the heat producer, let alone the network costs. Significant additional remuneration is required to sustain a competitive heat market and ensure sufficient investment in new generation capacity in the long run.

Energy-Saving Effects of Progressive Pricing and Free CFL Bulb Distribution Program: Evidence from Ethiopia

Abstract In Africa, about 70 percent of the total population still lives without electricity. Significant resources are needed to meet the gap. Demand-side management is crucial to curb the increasing demand even in developing countries. A traditional approach is to raise prices, but promoting energy-efficient products such as compact fluorescent lamp (CFL) bulbs is also a win-win proposition. While end-users can reduce their spending, power utilities can avoid costly investments in new generation capacity. This paper estimates the effects of progressive pricing as well as CFL distribution program in Ethiopia. It is found that the increasing block tariff structure reduced the demand: the price elasticity is estimated at 0.29. This is particularly useful to influence large-volume users, who are presumably the rich. The CFL program is also found effective to contain the electricity demand. The estimated impact is about 45 kWh per customer. This is significant energy savings particularly for low-volume users.

Business and policy models to incentivise utilities to engage with demand-side management

Business and policy models to incentivise utilities to engage with demand-side management (DSM) have received more attention in the grey literature than the academic literature. This review paper contributes to filling this gap by reviewing theoretical frameworks for four key categories of business models and how they relate to policy models that enable their implementation. The paper proposes a theoretical lens through which to visualise the different frameworks. The review discusses the key benefits and challenges for utilities to engage with DSM, and finds that deferred investment in new generation capacity, new business opportunities and services, and dealing with variable power production are the primary benefits, and limited incentives to invest in markets based on the quantity of energy sold and cost recovery issues (such as DSM programme costs) are the main challenges. The paper reviews four primary business and policy models: decoupling, demand-side participation in capacity markets, utility obligations and Energy Service Companies (ESCOs), and finds that despite the limitations of the evidence base on the applicability of decoupling in fully liberalised markets, demand-side participation in capacity markets, utility obligations and ESCOs appear to be applicable across contexts.

Measuring market power and the efficiency of Alberta's restructured electricity market: An energy‐only market design

AbstractWe measure the degree of market power execution and inefficiencies in Alberta's restructured electricity market. Using hourly wholesale market data from 2008 to 2014, we find that firms exercise substantial market power in the highest demand hours with limited excess production capacity. The degree of market power execution in all other hours is low. Market inefficiencies are larger in the high demand hours and elevate production costs by 6.7%–19% above the competitive benchmark, with an average of 13%. This reflects 2.1% of the average market price across all hours. A recent regulatory policy clarifies that certain types of unilateral market power execution is permitted in Alberta. We find evidence that suggests that strategic behaviour changed after this announcement. Market power execution increased. We illustrate that the observed earnings are often sufficient to promote investment in natural gas based technologies. The rents from market power execution can exceed the estimated capacity costs for certain generation technologies. However, we demonstrate that the energy market profits in the presence of no market power execution are generally insufficient to promote investment in new generation capacity. This stresses the importance of considering both short‐run and long‐run electricity market performance measures.

Are we Following the Right Path? Assessment of the Portuguese Electricity Generation on Atmospheric Emissions

1. Introduction In the last 20 years considerable changes have been occurring on the energy markets. The traditional public management has been gradually replaced by private management and the traditional utility monopolies have given place to free and competitive markets. In the European Union (EU), in particular, important steps have been taken to meet liberalisation objectives in the energy market (Ferreira et al., 2005). The idea is to improve economic efficiency and service quality, to guarantee provision and energy availability in better economic conditions, to provide consumers free access to alternative supply sources and to provide a better environmental protection. All these objectives were set on the 96/92/EC and 2003/54/EC Directives and latter on the III Energy Package approved in 2009. Simultaneously, the evolution of the EU-27 energy system has been characterised by a decoupling between energy demand and GHG emissions growth. Between 1997 and 2007 total GHG emissions decreased by 1.2% while final energy consumption grew by 5%. In the same period, final electricity consumption per capita also rose by 17%, continuing the trend observed in preceding years (Eurostat, 2009). This electricity demand is expected to grow about twice faster than the average energy demand (Perez-Arriaga et al., 2005). Thus, further investments in new generation capacity will be needed during the next years. Indeed, between 1997 and 2007 both total installed capacity of electricity generation and power generation increased by 18%. In 2007, thermal power plants provided the majority of capacity--with a share of 58% -, followed by hydro (18%) and nuclear plants (17%). Despite the strongly increase, the renewable energy sources (RES) still contribute to only 7% of total installed capacity of electricity generation. The most important change was registered by wind capacity, although hydro power still remains the largest contributor, with a 62% share of RES, in 2007, followed by wind energy (25%). The power generation showed a similar trend, with thermal power plants contributing for the majority of generation (56%) and RES for only 6%, in 2007. Although electricity generated from RES had verified a 41% increase, between 1997 and 2007, its contribution to total electricity consumption has only increased by 19% over this period, reaching 15.6% in 2007. Furthermore, total energy dependency rate has increased by 8.1 percentage points. The EU-27 is highly dependent on oil (82.6%), natural gas (60.3%) and hard coal and derivatives (58.6%) and the forecasts show the same trend for the next decades (Eurostat, 2009). Additionally, there is an accelerating decline of fossil fuel domestic resources. Consequently, most of the energy consumption growth will need to be met by increasing imports from outside the EU. Conversely, most environmental pressures show an improving trend. From 1990 to 2007 GHG emissions decreased by 9.3% slowing down (0.2%) between 2000 and 2007 (Eurostat, 2009). The changes operated in the fuel mix during that period, together with the restructuring of the Eastern European economies, were the key drivers for this improvement. This environmental enhancement has though an important exception. Total carbon emissions are expected to rise at a short-term rate of 0.3% per year, accelerating from 2015 onwards to a long-term rate of 0.5% per year (Perez-Arriaga et al., 2005). Because the anthropogenic sources of carbon dioxide to the atmosphere are dominated by fossil fuel use, energy and electricity are the main components for the mitigation of those emissions (Edmonds et al., 2006). In Portugal, energy-related activities are the major sources of Greenhouse Gases (GHG) emissions, accounting in 2008, for 70.8% of total emissions, presenting an increase of 37.4% over the 1990-2008 period. By far the most important gas emitted by this sector is C[O.sub.2], with 97.2% of sector emissions (APA, 2010). …

Identification of Generation Expansion Plans in Competitive Markets

Generation expansion planning plays a key role in the development of a power system. This paper contributes by developing a heuristic based on the results of a simulation model of the Central Interconnected System (SIC), which iteratively optimizes the number of expansion units necessary to accomplish certain assumptions and restrictions that a competitive market must meet in the long term. The first approach is from the theoretical perspective, through a review of the available literature on the subject, and the analysis of the historical development that the generation segment has at SIC, from the private and regulator perspectives. Additionally, a discussion of concepts related to the structure and assumptions that must be met in a competitive market is achieved, allowing the definition of the rules that must be followed by the heuristic. The heuristic uses a model developed by Endesa Chile, called MHT, which simulates the economic dispatch of a hidro-thermal system. The disadvantage of MHT is the massive use of computer resources, employing extensive time to run. Therefore, a number of simplifications on the input data are proposed, to reduce the simulation time; however, they produce significant distortion on the results. The heuristic is applied to a significant number of cases with different initial conditions, demonstrating a satisfactory performance under all the scenarios, which is verified by the fact that investment in new generation capacity reaches the expected levels.

Modeling hourly electricity dynamics for policy making in long-term scenarios

Energy policies are often related to the global effort in reducing greenhouse gas emissions through increased use of renewable energies in electricity production. The impact of these policies is usually calculated by energy planning tools. However, the modeling methodologies most currently used are not adequate to simulate long-term scenarios while considering the hourly dynamics of supply and demand.This paper presents an extension of the TIMES energy planning tool for investment decisions in electricity production that considers seasonal, daily and hourly supply and demand dynamics. The inclusion of these dynamics enables the model to produce more accurate results in what concerns the impact of introducing energy efficiency policies and the increased use of renewable energies.The model was validated in São Miguel (Azores, Portugal) for the years 2006–2009, where a comparison with real data showed that the model can simulate the supply and demand dynamics. Further, the long-term analysis shows that the inclusion of these dynamics contributes to a better assessment of the renewable energy potential, suggests the postponement of investments in new generation capacity, and demonstrates that using fine time resolution modeling is very valuable for the design of effective policy measures under high renewable penetration energy systems.

Making a case for white light-emitting diodes in the Western Cape

Within the context of the energy crisis in the Western Cape, the Provincial Government and Eskom (the South African power utility) embarked on a retrofit campaign to install 5 million compact fluorescent lamps (CFLs) in a desperate attempt to decrease the generation deficit. There is also increased pressure for investments in new generation capacity, with all options including the Pebble Bed Modular reactor (PBMR), the Open Cycle Gas Turbines (OCGT) as well as renewable resource technologies being pro-posed. Despite all these concerted efforts it is wide-ly regarded that demand-side technologies, with education programs, subsidies and research fund-ing, have greater scope for achieving success as they tackle the root cause rather than the symptom.The light emitting diode (LED) is a new energy efficient option in the lighting sector that has in recent times been deployed extensively by the City of Cape Town’s Transport Network Operations Department. The technology promises superior attributes that include a longer lifespan and higher energy conversion efficiencies, when compared to the traditional incandescents and fluorescents. This paper details the achievements of the LED in its brief history in the local traffic and signals industry as well as its projected impact on the city traffic light department’s future energy and mainte-nance budget. It is then proposed that these mono-chromatic signal LEDs, which is fast evolving into a white LED, holds the best promise in Cape Town as well as the Western Cape’s energy future if adopted for general lighting in the domestic, commercial and industrial market.

A stochastic dynamic model for optimal timing of investments in new generation capacity in restructured power systems

In this paper we formulate the power generation investment problem for a decentralised and profit-maximising investor operating in a restructured and competitive power system. In particular, we look at how uncertainty influences the optimal timing of investments in new power generation capacity. A real options approach is used to take long-term uncertainty in load growth, and its influence on future electricity prices, into account in the investment optimisation. In order to value the operational flexibility of a new power plant we use an electricity price model, where the spot price is a function of load level and installed generation capacity, in addition to short-term uncertainties and temporal fluctuations in the market. The investor’s income from a capacity payment, which also can depend on the system’s total capacity balance, can also be represented. Hence, with the optimisation model we can analyse power plant profitability and optimal timing of new investments under different market designs. In a case study from the Nordic electricity market we analyse the effect of uncertainty on optimal investment timing. We also examine how a fixed or variable capacity payment would influence the investment decision, and discuss the system consequences of the resulting investment strategies.

New Ananlytical Approach For Long-Term Generation Expansion Planning Based on Maximum Principle And Gaussian distribution Function

This paper presents a new approach for the optimal long-range generation planning. A completely new analytical approach for the production costing model and reliability measure is developed under the assumption of Gaussian probabilistic distribution of random load fluctuations and plant outages. The long-range generation investment problem is formulated as an optimal control problem to determine optimally the annual investment in new generation capacity. The Hamiltonian minimization is performed by using a version of the gradient projection method.

Optimization Technique For Long-Term Generation Expansion Planning

This paper presents a new approach for the optimal long-range generation planning. A completely new analytical approach for the production costing model and reliability measure is developed under the assumption of Gaussian probabilistic distribution of random load fluctuations and plant outages. The long-range generation investment problem is formulated as an optimal control problem to determine optimally the annual investment in new generation capacity. The Hamiltonian minimization is performed by using a version of the gradient projection method.

Optimization technique for long-term generation expansion planning using the maximum principle and the Gaussian distribution function

Abstract This paper presents a new approach to optimal long-range generation planning. A completely new analytical approach to the production costing model and reliability measure is developed under the assumption of a Gaussian probability distribution for the random load fluctuations and plant outages. The long-range generation investment problem is formulated as an optimal control problem to determine optimally the annual investment in new generation capacity. The Hamiltonian minimization is performed by using a version of the gradient projection method.