Pierluigi Mancarella

From cogeneration to trigeneration: profitable alternatives in a competitive market

Trigeneration refers to the combined production of electricity, heat, and cooling. In a competitive energy market framework, the adoption of Combined Heat, Cooling, and Power (CHCP) plants may become profitable with respect to traditional systems, where electricity, heat, and cooling are produced or purchased separately. This paper illustrates and evaluates the possible benefits of adopting different trigeneration alternatives in the design of a new energy system, with the specific focus on comparing different cooling production solutions. For the cooling side of CHCP systems, most of the literature refers to absorption groups fed by cogenerated thermal energy. Here, the trigeneration concept is extended to also include conventional electric chillers, heat pumps, or direct-fired absorption chillers. Comparative analysis of the trigeneration solutions is carried out for a hospital site, by performing time-domain simulations to characterize the out-of-design operation and different regulation strategies of the equipment. Poor effectiveness of using classical energy efficiency indices is discussed. A more effective economic analysis, where buying/selling electricity in a competitive market is specifically considered, is then performed. Finally, a multiscenario analysis is carried out for assessing the impact of electricity and gas price variations on the choice of the most convenient trigeneration solution.

Decentralized Participation of Flexible Demand in Electricity Markets—Part II: Application With Electric Vehicles and Heat Pump Systems

Realizing the significant demand flexibility potential in deregulated power systems requires its suitable integration in electricity markets. Part I of this work has presented the theoretical, algorithmic and implementation aspects of a novel pool market mechanism achieving this goal by combining the advantages of centralized mechanisms and dynamic pricing schemes, based on Lagrangian relaxation (LR) principles. Part II demonstrates the applicability of the mechanism, considering two reschedulable demand technologies with significant potential, namely electric vehicles with flexible charging capability and electric heat pump systems accompanied by heat storage for space heating. The price response sub-problems of these technologies are formulated, including detailed models of their operational properties. Suitable case studies on a model of the U.K. system are examined in order to validate the properties of the proposed mechanism and illustrate and analyze the benefits associated with the market participation of the considered technologies.

Automated Demand Response From Home Energy Management System Under Dynamic Pricing and Power and Comfort Constraints

This paper presents a comprehensive and general optimization-based home energy management controller, incorporating several classes of domestic appliances including deferrable, curtailable, thermal, and critical ones. The operations of the appliances are controlled in response to dynamic price signals to reduce the consumers electricity bill whilst minimizing the daily volume of curtailed energy, and therefore considering the users comfort level. To avoid shifting a large portion of consumer demand toward the least price intervals, which could create network issues due to loss of diversity, higher prices are applied when the consumers demand goes beyond a prescribed power threshold. The arising mixed integer nonlinear optimization problem is solved in an iterative manner rolling throughout the day to follow the changes in the anticipated price signals and the variations in the controller inputs while information is updated. The results from different realistic case studies show the effectiveness of the proposed controller in minimizing the households daily electricity bill while preserving comfort level, as well as preventing creation of new least-price peaks.

The Grid: Stronger, Bigger, Smarter?: Presenting a Conceptual Framework of Power System Resilience

Increasing the resilience of critical power infrastructures to high-impact, low-probability events, such as extreme weather phenomena driven by climate change, is of key importance for keeping the lights on. However, what does resilience really mean? Should we build a stronger and bigger grid or a smarter one? This article discusses a conceptual framework of power system resilience, its key features, and potential enhancement measures.

Integrated Modeling and Assessment of the Operational Impact of Power-to-Gas (P2G) on Electrical and Gas Transmission Networks

Power-to-gas (P2G) is the process whereby electricity is used to produce hydrogen or synthetic natural gas. The electricity for the P2G process could, for instance, come from renewable energy which would otherwise be curtailed due to system or line constraints. The existing natural gas network could then potentially be used as a means to store, transport, and reutilize this energy, thus preventing its waste. While there are several ongoing discussions on P2G in different countries, these are generally not backed by quantitative studies on its potential network implications and benefits. To bridge this gap, this paper introduces an original methodology to analyze different P2G processes and assess their operational impacts on both electricity and gas transmission networks. This is carried out by using a novel integrated model specifically developed for the simulation of operational interdependences between the two networks considering P2G. To demonstrate the several innovative features of the proposed model, technical, environmental, and economic operational aspects of P2G and its potential benefits are analyzed on the case of the Great Britains system, also providing insights into relief of gas and electrical transmission network constraints.

Modeling and Evaluating the Resilience of Critical Electrical Power Infrastructure to Extreme Weather Events

Electrical power systems have been traditionally designed to be reliable during normal conditions and abnormal but foreseeable contingencies. However, withstanding unexpected and less frequent severe situations still remains a significant challenge. As a critical infrastructure and in the face of climate change, power systems are more and more expected to be resilient to high-impact low-probability events determined by extreme weather phenomena. However, resilience is an emerging concept, and, as such, it has not yet been adequately explored in spite of its growing interest. On these bases, this paper provides a conceptual framework for gaining insights into the resilience of power systems, with focus on the impact of severe weather events. As quantifying the effect of weather requires a stochastic approach for capturing its random nature and impact on the different system components, a novel sequential Monte-Carlo-based time-series simulation model is introduced to assess power system resilience. The concept of fragility curves is used for applying weather- and time-dependent failure probabilities to systems components. The resilience of the critical power infrastructure is modeled and assessed within a context of system-of-systems that also include human response as a key dimension. This is illustrated using the IEEE 6-bus test system.

Integrated Electrical and Gas Network Flexibility Assessment in Low-Carbon Multi-Energy Systems

Summary form only given. In power systems with increasing variable renewable sources, gas generation is playing an increasingly prominent role in providing flexibility to meet net-load requirements. The flexibility provided by the gas turbines in turn relies on the flexibility of the gas network. While there are several discussions on the gas networks ability in providing this operational flexibility, this has not been clearly modelled or quantified. In addition, the gas network may also be responsible for supplying heating technologies, and low-carbon scenarios see tighter interactions between the electricity, heating and gas sectors, calling for a holistic multi-energy system assessment. On these premises, this paper presents a methodology to quantify the flexibility the gas network can provide to the power system, as well as the constraints it may impose on it, with also consideration of different heating scenarios. This is achieved by a multi-stage integrated gas and electrical transmission network model, using electrical DC OPFs and both steady-state and transient gas analyses. A novel metric making use of the concept of zonal linepack is introduced to assess the integrated gas and electrical flexibility, which is then used to impose gas-related internetwork inter-temporal constraints on the electrical OPF. Case studies performed for the Great Britain transmission system demonstrate the proposed integrated flexibility assessment, provide insights into the effects of changes to the heating sector on the multi-energy systems combined flexibility requirements and capability, and assess how the electrical network can experience local generation and reserve constraints related to the gas networks lack of flexibility.

Flexible Distributed Multienergy Generation System Expansion Planning Under Uncertainty

Summary form only given. A key feature of smart grids is the use of demand side resources to provide flexibility to the energy system and thus increase its efficiency. Multienergy systems where different energy vectors such as gas, electricity, and heat are optimized simultaneously prove to be a valuable source of demand side flexibility. However, planning of such systems may be extremely challenging, particularly in the presence of long-term price uncertainty in the underlying energy vectors. In this light, this paper proposes a unified operation and planning optimization methodology for distributed multienergy generation (DMG) systems with the aim of assessing flexibility embedded in both operation and investment stages subject to long-term uncertainties. The proposed approach reflects real options thinking borrowed from finance, and is cast as a stochastic mixed integer linear program. The methodology is illustrated through a realistic U.K.-based DMG case study for district energy systems, with combined heat and power plant, electric heat pumps, and thermal energy storage. The results show that the proposed approach allows reduction in both expected cost and risk relative to other less flexible planning methods, thus potentially enhancing the business case of flexible DMG systems.

Evaluation of the impact of electric heat pumps and distributed CHP on LV networks

This paper introduces and discusses a methodology to model and assess the impact of distributed electro-thermal technologies such as Distributed Combined Heat and Power (DCHP) and Electric Heat Pump (EHP) on LV distribution networks. Modelling of load and generation for both electricity and heat is carried out as the starting point of the analysis. In this way, it is possible to capture the relevant interactions between the two energy vectors. A fractal algorithm is then used to generate generic large-scale networks with different topologies and characteristics that can resemble real networks. Different metrics are used to quantify the impact of the considered technologies, with emphasis on thermal and voltage limits. Case studies carried out for typical urban and rural areas in the UK and for different scenarios exemplify the developed methodology and illustrate the main drivers for impact and trends in the different cases.

Distributed Software Infrastructure for General Purpose Services in Smart Grid

In this paper, the design of an event-driven middleware for general purpose services in smart grid (SG) is presented. The main purpose is to provide a peer-to-peer distributed software infrastructure to allow the access of new multiple and authorized actors to SGs information in order to provide new services. To achieve this, the proposed middleware has been designed to be: 1) event-based; 2) reliable; 3) secure from malicious information and communication technology attacks; and 4) to enable hardware independent interoperability between heterogeneous technologies. To demonstrate practical deployment, a numerical case study applied to the whole U.K. distribution network is presented, and the capabilities of the proposed infrastructure are discussed.