Decentralised Energy Systems and Associated Policy Mechanisms—A Review of Africa

Decentralised energy (DE), also known as distributed energy, refers to power generation and energy storage systems located at or near the point of use;and may also be connected to a local distribution network system or to a high voltage transmission system either directly or through a local distribution network system. It is generated or stored by a variety of small devices commonly referred to as distributed energy resources (DER);the definition also extends to include stand-alone systems completely isolated from the public networks. The contribution made by independent power producers (IPP’s) through deployment of DER in the African energy market is critical to fast-tracking the deployment of renewables, diversification of the energy mix and enhancing access to modern and clean energy. There is need to develop policy mechanisms aimed at enhancing the current positive drive in the energy market;and this has been observed to be a driving factor in countries which have developed appropriate policy strategies. This paper presents the concept of DE in detail and how it could complement efforts to addressing the current energy crises in Southern Africa;it also looks at policy developments in Africa and presents the scenarios in the two southern African countries of South Africa and Botswana. The research is based on an extensive review of literature on the subject matter, consultations with stakeholders as well as feedback from the Learning Network for Sustainable Energy Systems (LeNSes) workshops.

Dispersed Wind Power Planning Method Considering Network Loss Correction with Cold Weather

In order to play a positive role of decentralised wind power on-grid for voltage stability improvement and loss reduction of distribution network,a multi-objective two-stage decentralised wind power planning method is proposed in the paper,which takes into account the network loss correction for the extreme cold region.Firstly,an electro-thermal model is introduced to reflect the effect of temperature on conductor resistance and to correct the results of active network loss calculation;secondly,a two-stage multi-objective two-stage decentralised wind power siting and capacity allocation and reactive voltage optimisation control model is constructed to take account of the network loss correction,and the multi-objective multi-planning model is established in the first stage to consider the whole-life cycle investment cost of WTGs,the system operating cost and the voltage quality of power supply,and the multi-objective planning model is established in the second stage.planning model,and the second stage further develops the reactive voltage control strategy of WTGs on this basis,and obtains the distribution network loss reduction method based on WTG siting and capacity allocation and reactive power control strategy.Finally,the optimal configuration scheme is solved by the manta ray foraging optimisation(MRFO)algorithm,and the loss of each branch line and bus loss of the distribution network before and after the adoption of this loss reduction method is calculated by taking the IEEE33 distribution system as an example,which verifies the practicability and validity of the proposed method,and provides a reference introduction for decision-making for the distributed energy planning of the distribution network.

The Bisq decentralised exchange: on the privacy cost of participation

The Bisq Trade Protocol and the Bisq DAO(decentralised autonomous organisation)are core components of Bisq,a decentralised cryptocurrency exchange.The Bisq Trade Protocol systematises the peer-to-peer trading of Bitcoin for other currencies and the Bisq DAO decentralises the governance and finance functions of the entire exchange.However,by following the Bisq Trade Protocol and interacting with the Bisq DAO,participants necessarily publish data to the Bitcoin blockchain and broadcast additional data to the Bisq peer-to-peer network.We examine the privacy cost to participants in sharing this data.Specifically,we use novel address clustering heuristics to construct the one-to-many mappings from participants to addresses on the Bitcoin blockchain and augment the address clusters with data stored within the Bisq peer-to-peer network.We describe address clustering heuristics for both the Bisq Trade Protocol and the Bisq DAO.We show that the heuristics aggregate activity performed by each participant:trading,voting,transfers,etc.We identify instances where participants are operating under multiple aliases,some of which are real-world names.We identify the dominant transactors and their role in a two-sided market.We conclude with suggestions to better protect the privacy of participants in the future.

Decentralised dynamic high-gain scaling-based output-feedback control of large-scale non-linear interconnected systems with delays

A general class of non-linear large-scale interconnected systems is considered,wherein each subsystem is comprised of a nominal part in a general strict-feedback-like structure and a set of appended dynamics.Parametric and functional uncertainties and time delays are allowed throughout the overall system structure including the nominal strictfeedback-like parts and appended dynamics of each subsystem as well as the non-linear subsystem interconnections.The controller design is based on the dual dynamic highgain scaling technique and provides a robust adaptive delay-independent globally stabilising decentralised output-feedback controller.The disturbance attenuation properties of the proposed output-feedback decentralised controller to an exogenous disturbance input are also analysed and specific conditions under which properties such as Input-toOutput-practical-Stability and asymptotic stabilisation are attained are also discussed.

Decentralised energy and its performance assessment models

Energy development concerns not only the development of renewable energies but also the shift from centralised to clean,decentralised power generation.The development of decentralised energy(DE)is a core part of the energy and economic strategies being adopted around the world that drives the progress toward a highly sustainable future.This paper reviews the concepts,development status,trends,benefits and challenges of DE systems and analyses the existing models and methods for assessing the performance of these systems.A hierarchical decision model for evaluating the performance of DE systems is also constructed based on the framework of multiple criteria decision analysis,which considers the identification,definition and assessment grade of decision criteria.The evidential reasoning approach is applied to aggregate assessment information in a case study of the implementation of an intelligent decision system.Sensitivity and trade-off analyses are also conducted to show how the proposed model can be used to support decision making in DE systems.

Blockchain for decentralised rural development and governance

Rural areas are steadily being marginalised in a global economy where‘core/periphery’models of development are dominant.To overcome this,rural areas have experimented with decentralised governance.However,this process is fraught with political,fiscal,and institutional difficulties.These often revolve around transparency and accountability issues and low participation rates.Blockchain technology could act as a social innovation to overcome issues in decentralised governance,and rural areas could even prove to be a fertile environment for future innovation.In this conceptual paper,the potential of blockchain technology is theoretically positioned in regional development discourses.After exploring how blockchain could be applied to rural governance and the barriers it needs to overcome to reach mass adoption,a new distributed model of governance is suggested.

Electricity demand forecasting for decentralised energy management

The world is experiencing a fourth industrial revolution.Rapid development of technologies is advancing smart infrastructure opportunities.Experts observe decarbonisation,digitalisation and decentralisation as the main drivers for change.In electrical power systems a downturn of centralised conventional fossil fuel fired power plants and increased proportion of distributed power generation adds to the already troublesome outlook for op-erators of low-inertia energy systems.In the absence of reliable real-time demand forecasting measures,effective decentralised demand-side energy planning is often problematic.In this work we formulate a simple yet highly effective lumped model for forecasting the rate at which electricity is consumed.The methodology presented focuses on the potential adoption by a regional electricity network operator with inadequate real-time energy data who requires knowledge of the wider aggregated future rate of energy consumption.Thus,contributing to a reduction in the demand of state-owned generation power plants.The forecasting session is constructed initially through analysis of a chronological sequence of discrete observations.Historical demand data shows behaviour that allows the use of dimensionality reduction techniques.Combined with piecewise interpolation an electricity demand forecasting methodology is formulated.Solutions of short-term forecasting problems provide credible predictions for energy demand.Calculations for medium-term forecasts that extend beyond 6-months are also very promising.The forecasting method provides a way to advance a novel decentralised informatics,optimisa-tion and control framework for small island power systems or distributed grid-edge systems as part of an evolving demand response service.

Direct and Indirect Gradient Control for Static Optimisation

Static “self-optimising” control is an important concept, which provides a link between static optimisation and control. According to the concept, a dynamic control system could be configured in such a way that when a set of certain variables are maintained at their setpoints, the overall process operation is automatically optimal or near optimal at steady-state in the presence of disturbances. A novel approach using constrained gradient control to achieve “self-optimisation” has been proposed by Cao. However, for most process plants, the information required to get the gradient measure may not be available in real-time. In such cases, controlled variable selection has to be carried out based on measurable candidates. In this work, the idea of direct gradient control has been extended to controlled variable selection based on gradient sensitivity analysis (indirect gradient control). New criteria, which indicate the sensitivity of the gradient function to disturbances and implementation errors, have been derived for selection. The particular case study shows that the controlled variables selected by gradient sensitivity measures are able to achieve near optimal performance.

复杂软件系统的分散式构造:一个电子商务案例研究(英文)

Software development skills are only partially trained with traditional programming languages and software engineering courses. To achieve practical skills needed in software industry, complex examples are necessary which have to be generated in a project-like setting. This includes common solution finding, intensive communication and structured programming tasks. Here, a case study from the domain of eCommerce is presented, showing the complexity needed for these learning processes.

Investigating Energy Prosumer Behaviour in Crowd Energy Using an Interactive Model/Diorama

Smart living labs such as the one located in Fribourg(Switzerland) focus on improving wellbeing and furthering knowledge related to building the district of the future on a technical and social level. Therefore, smart living labs represent an experimental platform/space where sustainable production and consumption strategies can be tested in a protected environment. A significant change in the socioeconomic production and consumption sphere can be expected by the rise of the so-called energy prosumer. Accordingly, this article presents an interactive model for the experimental investigation of energy prosumer behavior. In this context, two potential experiments on investment and trade decisions are briefly outlined. Since(behavioral and economic) experiments are usually conducted under controlled conditions in experimental labs involving mainly undergraduate students, the presented interactive model is flexible and mobile, providing the advantage to conduct experiments nearly everywhere involving everyday citizens.

DecPDEVS: New Simulation Algorithms to Improve Message Handling in PDEVS

This work proposes a new simulation algorithm to improve message handling in discrete event formalism. We present an approach to minimize simulation execution time. To do this, we propose to reduce the number of exchanged messages between Parallel DEVS (PDEVS) components (simulators and coordinators). We propose three changes from PDEVS: direct coupling, flat structure and local schedule. The goal is the decentralisation of a number of tasks to make the simulators more autonomous and simplify the coordinators to achieve a greater speedup. We propose to compare the simulation results of several models to demonstrate the benefits of our approach.

Multiperspective Analysis of Microscale Trigeneration Systems and Their Role in the Crowd Energy Concept

The energy system of the future will transform from the current centralised fossil based to a decentralised, clean, highly efficient, and intelligent network. This transformation will require innovative technologies and ideas like trigeneration and the crowd energy concept to pave the way ahead. Even though trigeneration systems are extremely energy efficient and can play a vital role in the energy system, turning around their deployment is hindered by various barriers. These barriers are theoretically analysed in a multiperspective approach and the role decentralised trigeneration systems can play in the crowd energy concept is highlighted. It is derived from an initial literature research that a multiperspective （technological, energy-economic, and user） analysis is necessary for realising the potential of trigeneration systems in a decentralised grid. And to experimentally quantify these issues we are setting up a microseale trigeneration lab at our institute and the motivation for this lab is also briefly introduced.

Bureaucratic Factors Impeding the Delivery of Infrastructure at the Metropolitan Municipal and District Assemblies (MMDAs) in Ghana

Decentralisation of infrastructure delivery to sub-national governments has become commonplace in governments worldwide especially in developing countries such as Ghana. This is due to the benefits of decentralisation in improving public service delivery. However, decentralised infrastructure delivery is marred with numerous challenges that render most local governments incapable of providing infrastructure within their localities. This paper explored the bureaucratic factors that impede infrastructure delivery at the MMDAs in Ghana. A questionnaire survey with 121 construction professionals in the Departments of Works (DoWs) of the MMDAs within the Ashanti and Greater Accra Regions of Ghana was conducted. The results indicated six (6) major components of the bureaucratic factors that impede the delivery of infrastructure at the MMDAs: Central government bureaucracy;Minimal control of MMDAs;Political influence;MMDA project funding;Lack of capacity of MMDAs;and Political interference. This paper calls for a more committed central government to the establishment of adequate decentralised structures and implementation of major reforms that would remove the bureaucratic obstacles in the delivery of infrastructure at the MMDAs, to ensure effective infrastructure delivery at the MMDAs.

Measuring node decentralisation in blockchain peer to peer networks

New blockchain platforms are launching at a high cadence,each fighting for attention,adoption,and infrastructure resources.Several studies have measured the peer-to-peer(P2P)network decentralisation of Bitcoin and Ethereum(i.e.,two of the largest used platforms).However,with the increasing demand for blockchain infrastructure,it is important to study node decentralisation across multiple blockchain networks,especially those containing a small number of nodes.In this paper,we propose NodeMaps,a data processing framework to capture,analyse,and visualise data from several popular P2P blockchain platforms,such as Cosmos,Stellar,Bitcoin,and Lightning Network.We compare and contrast the geographic distribution,the hosting provider diversity,and the software client variance in each of these platforms.Through our comparative analysis of node data,we found that Bitcoin and its Lightning Network Layer 2 protocol are widely decentralised P2P blockchain platforms,with the largest geographical reach and a high proportion of nodes operating on The Onion Router(TOR)privacy-focused network.Cosmos and Stellar blockchains have reduced node participation,with nodes predominantly operating in large cloud providers or well-known data centres.

Residential electrical vehicle charging strategies:the good,the bad and the ugly

In recent years,a wide variety of centralised and decentralised algorithms have been proposed for residential charging of electric vehicles(EVs).In this paper,we present a mathematical framework which casts the EV charging scenarios addressed by these algorithms as optimisation problems having either temporal or instantaneous optimisation objectives with respect to the different actors in the power system.Using this framework and a realistic distribution network simulation testbed,we provide a comparative evaluation of a range of different residential EV charging strategies,highlighting in each case positive and negative characteristics.

PID Controller Tuning for a Multivariable Glass Furnace Process by Genetic Algorithm

Standard genetic algorithms （SGAs） are investigated to optimise discrete-time proportional-integral-derivative （PID） con- troller parameters, by three tuning approaches, for a multivariable glass furnace process with loop interaction. Initially, standard genetic algorithms （SGAs） are used to identify control oriented models of the plant which are subsequently used for controller optimisa- tion. An individual tuning approach without loop interaction is considered first to categorise the genetic operators, cost functions and improve searching boundaries to attain the desired performance criteria. The second tuning approach considers controller parameters optimisation with loop interaction and individual cost functions. While, the third tuning approach utilises a modified cost function which includes the total effect of both controlled variables, glass temperature and excess oxygen. This modified cost function is shown to exhibit improved control robustness and disturbance rejection under loop interaction.

Distributed governance of Solar Radiation Management geoengineering:A possible solution to SRM’s“free-driver”problem?

Geoengineering(deliberate climate modification)is a possible way to limit Anthropogenic Global Warming(AGW)(Shepherd,2009;National Research Council,2015).Solar Radiation Management geoengineering(SRM)offers relatively inexpensive,rapid temperature control.However,this low cost leads to a risk of controversial unilateral intervention—the“free-driver”problem(Weitzman,2015).Consequently,this creates a risk of counter-geoengineering(deliberate warming)(Parker et al.,2018),resulting in governance challenges(Svoboda,2017)akin to an arms race.Free-driver deployment scenarios previously considered include the rogue state,Greenfinger(Bodansky,2013),or power blocs(Ricke et al.,2013),implying disagreement and conflict.We propose a novel distributed governance model of consensually-constrained unilateralism:Countries’authority is limited to each state’s fraction of the maximum realistic intervention(e.g.,pre-industrial temperature).We suggest a division of authority based on historical emissions(Rocha et al.,2015)—noting alternatives(e.g.,population).To aid understanding,we offer an analogue:An over-heated train carriage,with passenger-controlled windows.We subsequently discuss the likely complexities,notably Coasian side-payments.Finally,we suggest further research:Algebraic,bot and human modeling;and observational studies.