Explaining high transport costs within Malawi - bad roads or lack of trucking competition ?

What are the main determinants of transport costs: network access or competition among transport providers? The focus in the transport sector has often been on improving the coverage of"hard"infrastructure, whereas in reality the cost of transporting goods is quite sensitive to the extent of competition among transport providers and scale economies in the freight transport industry, creating monopolistic behavior and circular causation between lower transport costs and greater trade and traffic. This paper contributes to the discussion on transport costs in Malawi, providing fresh empirical evidence based on a specially commissioned survey of transport providers and spatial analysis of the country’s infrastructure network. The main finding is that both infrastructure quality and market structure of the trucking industry are important contributors to regional differences in transport costs. The quality of the trunk road network is not a major constraint but differences in the quality of feeder roads connecting villages to the main road network have significant bearing on transport costs. And costs due to poor feeder roads are exacerbated by low volumes of trade between rural locations and market centers. With empty backhauls and journeys covering small distances, only a few transport service providers enter the market, charging disproportionately high prices to cover fixed costs and maximize markups.Transport Economics Policy&Planning,Rural Roads&Transport,Roads&Highways,Banks&Banking Reform,Rural Transport

Enabling Micro-level Demand-Side Grid Flexiblity in Resource Constrained Environments

The increased penetration of uncertain and variable renewable energy presents various resource and operational electric grid challenges. Micro-level (household and small commercial) demand-side grid flexibility could be a cost-effective strategy to integrate high penetrations of wind and solar energy, but literature and field deployments exploring the necessary information and communication technologies (ICTs) are scant. This paper presents an exploratory framework for enabling information driven grid flexibility through the Internet of Things (IoT), and a proof-of-concept wireless sensor gateway (FlexBox) to collect the necessary parameters for adequately monitoring and actuating the micro-level demand-side. In the summer of 2015, thirty sensor gateways were deployed in the city of Managua (Nicaragua) to develop a baseline for a near future small-scale demand response pilot implementation. FlexBox field data has begun shedding light on relationships between ambient temperature and load energy consumption, load and building envelope energy efficiency challenges, latency communication network challenges, and opportunities to engage existing demand-side user behavioral patterns. Information driven grid flexibility strategies present great opportunity to develop new technologies, system architectures, and implementation approaches that can easily scale across regions, incomes, and levels of development

A Review of the Monitoring of Market Power The Possible Roles of TSOs in Monitoring for Market Power Issues in Congested Transmission Systems

The paper surveys the literature and publicly available information on market power monitoring in electricity wholesale markets. After briefly reviewing definitions, strategies and methods of mitigating market power we examine the various methods of detecting market power that have been employed by academics and market monitors/regulators. These techniques include structural and behavioural indices and analysis as well as various simulation approaches. The applications of these tools range from spot market mitigation and congestion management through to long-term market design assessment and merger decisions. Various market-power monitoring units already track market behaviour and produce indices. Our survey shows that these units collect a large amount of data from various market participants and we identify the crucial role of the transmission system operators with their access to dispatch and system information. Easily accessible and comprehensive data supports effective market power monitoring and facilitates market design evaluation. The discretion required for effective market monitoring is facilitated by institutional independence.Electricity, liberalisation, market power, regulation

Energy-Aware Algorithms for Greening Internet-Scale Distributed Systems Using Renewables

Internet-scale Distributed Systems (IDSs) are large distributed systems that are comprised of hundreds of thousands of servers located in hundreds of data centers around the world. A canonical example of an IDS is a content delivery network (CDN) that delivers content to users from a large global deployment of servers around the world. IDSs consume large amounts of energy and their energy requirements are projected to increase significantly in the future. With carbon emissions from data centers increasing every year, use of renewables to power data centers is critical for the sustainability of data centers and for the environment. In this thesis we design energy-aware algorithms that leverage renewable sources of energy and study their potential to reduce brown energy consumption in IDSs. Firstly, we study the use of renewable solar energy to power IDS data centers. A net-zero IDS produces as much energy from renewables (green energy) as it needs to entirely off-set its energy consumption. We develop effective algorithms to help minimize the number of solar panels provisioned for net-zero IDSs. We empirically evaluate our algorithms using load traces from Akamai\u27s global CDN and solar data from PVWatts. Our results show that for net-zero year, net-zero month, and net-zero week, our optimal algorithm can reduce the number of panels by 36%, 68%, and 82% respectively, thereby making sustainability of IDSs significantly more achievable. IDSs consume a significant amount of energy for cooling their infrastructure. Therefore, next, we study the potential benefits of using open air cooling (OAC) to reduce the energy usage as well as the capital costs incurred by an IDS for cooling. We develop an algorithm to incorporate OAC into the IDS architecture and empirically evaluate its efficacy using extensive work load traces from Akamai\u27s global CDN and global weather data from NOAA. Our results show that by using OAC, a global IDS can extract a 51% cooling energy reduction during summers and a 92% reduction in the winter. Finally, we study the greening potential of combining two contrasting sources of renewable energy, namely solar energy and open air cooling (OAC). OAC involves the use of outside air to cool data centers if the weather outside is sufficiently cold and dry. Therefore OAC is likely to be abundant in colder weather and at night-time. In contrast, solar energy generation is correlated with sunny weather and day-time. Given their contrasting natures, we study whether synthesizing these two renewable sources of energy can yield complementary benefits. Given the intermittent nature of renewable energy, we use energy storage and load shifting to facilitate the use of green energy and study trade-offs in brown energy reduction based on key parameters like battery size, number of solar panels, and radius of load movement. We do a detailed cost analysis, including amortized cost savings as well as a break-even analysis for different energy prices. Our results show that we can significantly reduce brown energy consumption by about 55% to 59% just by combining the two technologies. We can increase our savings further to between 60% to 65% by adding load movement within a radius of 5000kms, and to between 73% to 89% by adding energy storage

Lifetime-aware cloud data centers: models and performance evaluation

We present a model to evaluate the server lifetime in cloud data centers (DCs). In particular, when the server power level is decreased, the failure rate tends to be reduced as a consequence of the limited number of components powered on. However, the variation between the different power states triggers a failure rate increase. We therefore consider these two effects in a server lifetime model, subject to an energy-aware management policy. We then evaluate our model in a realistic case study. Our results show that the impact on the server lifetime is far from negligible. As a consequence, we argue that a lifetime-aware approach should be pursued to decide how and when to apply a power state change to a server