Optimisation of electricity energy markets and assessment of CO2 trading on their structure : a stochastic analysis of the greek power sector

Power production was traditionally dominated by monopolies. After a long period of research and organisational advances in international level, electricity markets have been deregulated allowing customers to choose their provider and new producers to compete the former Public Power Companies. Vast changes have been made in the European legal framework but still, the experience gathered is not sufficient to derive safe conclusions regarding the efficiency and reliability of deregulation. Furthermore, emissions' trading progressively becomes a reality in many respects, compliance with Kyoto protocol's targets is a necessity, and stability of the national grid's operation is a constraint of vital importance. Consequently, the production of electricity should not rely solely in conventional energy sources neither in renewable ones but on a mixed structure. Finding this optimal mix is the primary objective of the study. A computational tool has been created, that simulates and optimises the future electricity generation structure based on existing as well as on emerging technologies. The results focus on the Greek Power Sector and indicate a gradual decreasing of anticipated CO2 emissions while the socioeconomic constraints and reliability requirements of the system are met. Policy interventions are pointed out based on the numerical results of the model. (C) 2010 Elsevier Ltd. All rights reserved

Decarbonizing the EU power sector: policy approaches in the light of current trends and long-term trajectories

ASSESSMENT European climate policy is gradually shifting towards a long-term perspec- tive. The electricity sector has a crucial role to play in the long-term decar- bonization of the EU economy. It makes up a significant share of EU emis- sions and can contribute to the reduction of emissions in other sectors, particularly buildings and transport. The EU 2008 Climate and Energy Package (CEP) took a significant step towards a low-carbon future, initi- ating a very ambitious program of renewables expansion and strengthen- ing the ETS. However, the omissions and internal inconsistencies of the CEP are becoming more and more evident. This relates in particular to the absence of long-term, comprehensive signals for decarbonization and the imbalance between the ETS, energy efficiency and renewables objectives. This risks delaying and distorting investment in low-carbon infrastructure and ideas, raising the ultimate cost of climate policy. In view of the inertias within the electricity sector, it is imperative for the EU to set a long-term signal for the decarbonization of the sector by set- ting 2030 objectives for the ETS and complementary policies. The EU’s decarbonization strategy needs to be robust against future uncertainties; strengthening a technology neutral instrument like the ETS can provide a key part of a comprehensive signal to develop the full range of decarbon- ization options. The instrument imbalance also needs to be addressed. Demand side policies should be the point of departure for supply side interventions: ETS caps should be set so as to achieve carbon scarcity after energy efficiency and RES objectives have been taken into account. A short-term adjustment of scarcity in the ETS may create some incen- tives for low-carbon investment. However, it would not address the funda- mental concern, namely the lack of policy information regarding the post 2020 environment in which these investment will amortize.European climate policy; 2050 decarbonization; European emissions trading scheme; renewables policy

Competitive Benchmarking: An IS Research Approach to Address Wicked Problems with Big Data and Analytics

Wicked problems like sustainable energy and financial market stability are societal challenges that arise from complex socio-technical systems in which numerous social, economic, political, and technical factors interact. Understanding and mitigating them requires research methods that scale beyond the traditional areas of inquiry of Information Systems (IS) “individuals, organizations, and markets” and that deliver solutions in addition to insights. We describe an approach to address these challenges through Competitive Benchmarking (CB), a novel research method that helps interdisciplinary research communities to tackle complex challenges of societal scale by using different types of data from a variety of sources such as usage data from customers, production patterns from producers, public policy and regulatory constraints, etc. for a given instantiation. Further, the CB platform generates data that can be used to improve operational strategies and judge the effectiveness of regulatory regimes and policies. We describe our experience applying CB to the sustainable energy challenge in the Power Trading Agent Competition (Power TAC) in which more than a dozen research groups from around the world jointly devise, benchmark, and improve IS-based solutions

What does the future hold for utility electricity efficiency programs?

This study develops projections of future spending and savings from electricity efficiency programs funded by electric utility customers in the United States through 2030 based on three scenarios. Our analysis relies on detailed bottom-up modeling of current state energy efficiency policies, demand-side management and integrated resource plans, and regulatory decisions. The three scenarios represent a range of potential outcomes given the policy environment at the time of the study and uncertainties in the broader economic and state policy environment in each state. We project spending to increase to $8.6 billion in 2030 in the medium scenario, about a 45 percent increase relative to 2016 spending. In the high case, annual spending increases to$11.1 billion in 2030 and remains relatively flat in the low case ($6.8 billion in 2030). Our analysis suggests that electricity efficiency programs funded by utility customers will continue to impact load growth significantly at least through 2030, as savings as a percent of retail sales are forecast at 0.7 percent in the medium scenario and 0.98 percent in the high scenario

Models in evolutionary economics and environmental policy: Towards an evolutionary environmental economics

In this paper we review evolutionary economic modelling in relation to environmental policy. We discuss three areas in which evolutionary economic models have a particularly high added value for environmental policy-making: the double externality problem, technological transitions and consumer demand. We explore the possibilities to apply evolutionary economic models in environmental policy assessment, including the opportunities for making policy-making endogenous to environmental innovation. We end with a critical discussion of the challenges that remain.

Corporate political activity and location-based advantage: MNE responses to institutional transformation in Uganda’s electricity industry

We examine how multinational enterprises (MNEs) employ political strategies in response to location-based, institutional transformations in new frontier African markets. Specifically, we explore the heterogeneous corporate political activities of advanced and emerging market MNEs in Uganda’s electricity industry, as they respond to and influence locational advantage using diverse political capabilities. We argue that, in institutionally fragile, new frontier markets, Dunning’s OLI paradigm is more theoretically robust and managerially relevant when combined with a political perspective. Effective MNE political strategies in these markets rely on nonmarket capabilities in political stakeholder engagement, community embeddedness, regional understanding, and responsiveness to stages of institutionalization

Systematic analysis of the evolution of electricity and carbon markets under deep decarbonization

The decarbonization of electricity generation presents policy makers in many countries with the delicate task of balancing initiatives for technological change with a commitment to market liberalization. Despite the theoretical attractions, it has become doubtful whether carbon markets by themselves can offer the desired solution. We address this question through an integrated modeling framework, stylized for the Great Britain (GB) power market within the EU ETS, which includes three distinct components: (a) long-term least-cost capacity planning, similar in functionality to many used in policy analysis, but innovative in providing the endogenous calculation of carbon prices; (b) short-term price risk analysis producing hourly dispatch and pricing outputs, which are used to test the annual financial performance metrics implied by the longer-term investments; and (c) agent-based computational learning to derive pricing behavior in imperfect markets. The results indicate that the risk/return profile of electricity markets may deteriorate substantially as a result of decarbonization, reducing the propensity of companies to invest in the absence of increased government support and/or more beneficial market circumstances. If allowed, markets may adjust by deferring investment until conditions improve, consolidating to increase market power, or operating in a tighter market with reduced spare capacity. To the extent that each of these “market-led” solutions may be politically unpalatable, policy design will need to sustain a delicate regulatory regime, moderating the possible increased market power of companies while maintaining low-carbon subsidies for longer than expected. This paper considers some of the modeling implications for this compromise

Energy and emissions : local and global effects of the rise of China and India

Part 1 of the paper reviews recent trends in fossil fuel use and associated externalities. It also argues that the recent run-up in international oil prices reflects growing concerns about supply constraints associated with declining spare capacity in OPEC, refining bottlenecks, and geopolitical uncertainties rather than growing incremental use of oil by China and India. Part 2 compares two business as usual scenarios with a set of alternate scenarios based on policy interventions on the demand for or supply of energy and different assumptions about rigidities in domestic and international energy markets. The results suggest that energy externalities are likely to worsen significantly if there is no shift in China's and India's energy strategies. High energy demand from China and India could constrain some developing countries'growth through higher prices on international energy markets, but for others the"growth retarding"effects of higher energy prices are partially or fully offset by the"growth stimulating"effects of the larger markets in China and India. Given that there are many inefficiencies in the energy system in both China and India, there is an opportunity to reduce energy growth without adversely affecting GDPgrowth. The cost of a decarbonizing energy strategy will be higher for China and India than a fossil fuel-based strategy, but the net present value of delaying the shift will be higher than acting now. The less fossil fuel dependent alternative strategies provide additional dividends in terms of energy security.Energy Production and Transportation,Environment and Energy Efficiency,Energy and Environment,Energy Demand,Transport Economics Policy&Planning

Are agent-based simulations robust? The wholesale electricity trading case

Agent-based computational economics is becoming widely used in practice. This paper explores the consistency of some of its standard techniques. We focus in particular on prevailing wholesale electricity trading simulation methods. We include different supply and demand representations and propose the Experience-Weighted Attractions method to include several behavioural algorithms. We compare the results across assumptions and to economic theory predictions. The match is good under best-response and reinforcement learning but not under fictitious play. The simulations perform well under flat and upward-slopping supply bidding, and also for plausible demand elasticity assumptions. Learning is influenced by the number of bids per plant and the initial conditions. The overall conclusion is that agent-based simulation assumptions are far from innocuous. We link their performance to underlying features, and identify those that are better suited to model wholesale electricity markets.Agent-based computational economics, electricity, market design, experience-weighted attraction (EWA), learning, supply functions, demand aggregation, initial beliefs.