Unserved Energy Research Articles

Economic Impact of Electricity Interruptions: A Case Study Based on Sri Lanka

A power system responsible to supply reasonable level of reliable, qualitative electricity supply to its consumers in an acceptable price. Reasonable level is defined as one balancing the need for power supply and the cost involved. This includes increasing adequacy and security of the system. If the frequency and duration of outages can be reduced, the benefit can be given to consumers. Cost of Unserved Energy is considered as a basic parameter of economic evaluation in the process of increasing the power system reliability. Initial research was conducted before two decades ago and now it is needed to conduct a study of up-to-date on the scope. Thus, research to assess the cost of Unserved Energy for Sri Lanka was conducted and the outcome of the research is presented in this research paper. Consumer survey is chosen as the methodology of the research and it is conducted into three separate electricity consumer categories of domestic, industrial and Commercial. Each category is sub-grouped according to different classifications and separate results have shown for momentary planned and unplanned and non-momentary planned and unplanned interruptions. Finally, the results of each category are averaged into two final values one each for each classification considered.

Optimal Energy Reserve Scheduling in Integrated Electricity and Gas Systems Considering Reliability Requirements

With the growing interdependence between the electricity system and the natural gas system, the operation uncertainties in either subsystem, such as wind fluctuations or component failures, could have a magnified impact on the reliability of the whole system due to energy interactions. A joint reserve scheduling model considering the cross-sectorial impacts of operation uncertainties is essential but still insufficient to guarantee the reliable operation of the integrated electricity and natural gas system (IEGS). Therefore, this paper proposes a day-ahead security-constrained unit commitment (SCUC) model for the IEGS to schedule the operation and reserve si-multaneously considering reliability requirements. Firstly, the multi-state models for generating units and gas wells are established. Based on the multi-state models, the expected unserved energy cost (EUEC) and the expected wind curtailment cost (EWC) criteria are proposed based on probabilistic methods considering wind fluctuation and random failures of components in IEGS. Furthermore, the EUEC and EWC criteria are incorporated into the day-ahead SCUC model, which is noncon-vex and mathematically reformulated into a solvable mixed-integer second-order cone programming (MISOCP) problem. The proposed model is validated using an IEEE 30-bus system and Belgium 20-node natural gas system. Numerical results demonstrate that the proposed model can effectively schedule the energy reserve to guarantee the reliable operation of the IEGS considering the multiple uncertainties in different subsystems and the cross-sectorial failure propagation.

Crediting Variable Renewable Energy and Energy Storage in Capacity Markets: Effects of Unit Commitment and Storage Operation

As more variable renewable energy (VRE) and energy storage (ES) facilities are installed, accurate quantification of their contributions to system adequacy becomes crucial. We propose a definition of capacity credit (CC) for valuing adequacy contributions of these resources based on their marginal capability to reduce expected unserved energy. We show that such marginal credits can incentivize system-optimal investments in markets with installed capacity requirements and energy price caps. We simulated such markets using a LP-based capacity expansion planning model with convexified unit commitment (UC) constraints and ES. The impacts of UC and ES on capacity credits are investigated. Furthermore, we analyze technology and system cost distortions resulting from implementing inaccurate CCs in the capacity market. The results show that ignoring UC constraints can overestimate the CCs for VRE and ES. Building ES increases the CCs of VRE resources with higher capacity factors and a negative correlation with load. Assigning the wrong credit to VRE can significantly distort resource mixes and system cost. Implementing the proposed CCs can, in theory, eliminate those distortions and achieve the same overall optimum as a theoretical market without energy price caps.

Enhancing distribution system resilience against extreme weather events: Concept review, algorithm summary, and future vision

Distribution system infrastructures are vulnerable to extreme weather events, such as hurricane, ice coating, flood, and wildfires. Resilience is a measure of the system's ability to prevent the damage during extreme events and to recover the system function after such events. With the economic development, it becomes increasingly important for power utilities to maintain critical loads always in service and to reduce the unserved energy of all loads. If many distribution system equipments are damaged, the utility companies dispatch static or mobile distributed energy resources, reconfigure the network topology in order to restore the islanded sections of the distribution system. In recent years, a large number of studies have been done on operation and planning strategies to enhance the distribution system resilience. This review paper introduces the background of resilient distribution system. Then, it makes a comprehensive summary of the resources for resilience enhancement, the mathematical model of operation and planning algorithms. In particular, the objective function, mathematical formulation, decision variables, and solution algorithm of each study are compared. Finally, the roadmap of resilient distribution system is extracted and the future research direction on this topic is proposed.

A Methodology to Calculate the Non-Supplied Energy Level in Distribution Grids With Radial Structure

The distribution agents of electrical energy have a commitment with the end customers to comply with certain reliability indices in order to guarantee the quality of the service they provide, among these, one of the most important is to maintain continuity in the electrical supply. This article presents a methodology with a possible application to real electrical distribution systems for calculating the level of unserved energy through the use of the concepts of operational zones and unavailability, through the analysis of failures in each of the different lines. and subsequent outages that occur in the test system. Different scenarios and configurations are evaluated by varying the position of reclosers and fuses in order to present the results and the corresponding conclusions.

Improving reliability of the power distribution system in Goma (DRC) using solar distributed generation

The existing power distribution system of the city of Goma in the Democratic Republic of the Congo has many problems, including the scarcity of electric energy, power unreliability, the low access rate of electrification, poor flexibility in the network topology, and lack of demand response, which lead to shedding of load, unbalancing and overloading the system. The reliability of the Goma power distribution system is very poor by international standards. The major cause of this is the lack of adequate energy supply to meet demand. To mitigate the power reliability problem, a solar-based distributed generation (DG) is modelled and evaluated in this study. Each feeder has been considered separately with an appropriately designed DG. The work has evaluated initial investment cost and life cycle cost of the investment to assess the feasibility of the proposed solution. Based on the unserved energy and electricity tariff, an economic analysis was conducted. The reliability indices are computed and the modelled solution is designed for each feeder in PV syst software and simulated using ETAP, whose simulation results show that the reliability can be improved by up to 76%.

Enabling demand response for optimal deployment of multi‐carrier microgrids incorporating incentives

This paper inspects customer multi-carrier microgrid deployments' techno-economic viability and assists investors in deciding whether or not to invest in multi-carrier microgrid installations equipped with smart demand-side technologies. The solution of the proposed model determines the optimal mix and size of distributed energy resources, and identifies the ideal participation rate of potential responsive customers within the multi-carrier microgrid. The objective of the proposed model is to minimize the overall deployment cost comprising the investment and replacement of distributed energy resources, demand-side smart measurement and informing appliances, loan payoff, operation, maintenance, peak demand charge, energy demand shifting reward or penalty, emission, and unserved energy while ensuring the desired levels of reliability and online reserve. The model also considers incentive policies to encourage customers to install demand-side smart technologies to participate in demand response programs actively. The planning problem is formulated by mixed-integer programming. The proposed model is applied to an industrial zone as an aggregate load. Numerical simulations exhibit the model's efficacy and scrutinize in-depth, the effect of a variety of factors on multi-carrier microgrid planning results, including the extents of the capital investment fund and loan in addition to demand response enabling technology cost.

Technical and financial analysis of large-scale solar-PV in eThekwini Municipality: Residential, business and bulk customers

Regulatory changes, economic challenges, environmental concerns, and changing public perception have contributed to the profound changes observed globally in the electricity industry. Since 2008, South Africa has been experiencing electric power deficits and outages. This has been due in part to generation capacity constraints, belated investment in new electricity infrastructure, deferred maintenance of existing power assets, load growth in areas which were not adequately planned for, high population and economic growth over the last two decades. This has resulted in peak electricity demand outstripping available power generation capacity, leading to electricity shortages and load shedding, which is now impeding economic growth. In South Africa, forced under frequency load shedding, rising electricity tariffs, energy efficiency, declining cost of solar PV systems, the introduction of Carbon taxes, high cost of unserved energy has led consumers to explore embedded generation options to assist with reducing their energy bills, hence investments in solar PV has become an option to municipal customers. The simple payback period of solar PV systems is an important indicator for customers to ascertain whether to invest in these systems or not. Revenue loss remains a significant concern for municipalities who have historically designed single and two-rate bundled tariffs, which rely on municipalities selling electricity to ensure its business’s sustainability. Municipalities have now proposed new tariff structures designed to minimize the adverse impact of reducing electricity sales from solar PV by creating net billing tariffs with a built in network access charge component based on the customer’s inverter size. Case studies were carried out to better understand the impact on the feasibility of solar PV systems with and without the implementation of these new tariffs and its impact on the customer’s payback periods. A calculation of the levelised cost of electricity and customers rate of return for the different customer classes were also calculated to provide a better picture on the financial feasibility of rooftop solar PV. Results obtained from these case studies indicate lucrative payback periods for customers installing solar PV systems with improved revenue recovery for the municipality.

A MILP optimization model for siting isolation devices in distribution systems with DERs to enhance reliability

The deployment of distributed energy resources (DER) theoretically improves the reliability of a radial distribution system by taking advantage of the ability to island DERs and customers. However, an isolation device has to be placed in order to create this “island.” On the other hand, a radial distribution system typically lacks isolation devices that are able to detect and isolate a fault, especially on the main distribution feeder, which is nowadays often protected by the substation breaker. This paper proposes a methodology to identify the optimal locations to install isolation devices in a radial distribution network with DER integrations, aiming at reliability improvements of distribution networks. We exploit utility historical load and fault data for generating multiple fault scenarios and develop a stochastic programming-based optimization model for unserved energy minimization. Two case studies on an IEEE 4-bus and 123-bus systems are performed, including some sensitivity analysis.

Global 100% energy transition by 2050: A fiction in developing economies?

Global 100% energy transition by 2050: A fiction in developing economies?

Scheduling of energy storage.

The increasing reliance on renewable energy generation means that storage may well play a much greater role in the balancing of future electricity systems. We show how heterogeneous stores, differing in capacity and rate constraints, may be optimally, or nearly optimally, scheduled to assist in such balancing, with the aim of minimizing the total imbalance (unserved energy) over any given period of time. It further turns out that in many cases the optimal policies are such that the optimal decision at each point in time is independent of the future evolution of the supply-demand balance in the system, so that these policies remain optimal in a stochastic environment. This article is part of the theme issue 'The mathematics of energy systems'.

Reliability-cost trade-offs for electricity industry planning with high variable renewable energy penetrations in emerging economies: A case study of Indonesia’s Java-Bali grid

Electricity industries in emerging economies face particular challenges in delivering affordable, environmentally sustainable, and secure power given growing demand and limited financial resources. While supply reliability is often poor and emission reductions given lower priority, solar and wind are now amongst our cheapest supply options but highly variable. Our study seeks to demonstrate the potential value of trading-off reliability standards against higher renewables and lower industry costs in future generation planning. We use an open-source, evolutionary programming-based, capacity expansion planning tool, NEMO, to solve least cost generation mixes for Indonesia’s Java-Bali grid in 2030. We explicitly test the cost and emission impacts of reliability targets of 0.005%–5% unserved energy (USE), modelled as both a hard optimization constraint and a penalty price on USE in the cost function. Our results highlight that lower reliability targets can increase solar and wind penetrations, reducing CO2 emissions while reducing industry costs. Both methods of incorporating reliability delivered similar outcomes but pricing USE had some advantages for optimization over hard constraint setting. While the impacts of lower reliability on consumers requires careful consideration, our study highlights the potential cost and emission implications of arguably unrealistic reliability targets in generation planning for emerging economies.

Probabilistic evaluations on marginal price and capacity adequacy of power systems with price-elastic demand

An increasing deployment of smart grid technologies and demand response programs has enabled demands to be more elastic in response to electricity prices, actively contributing to power system operation. However, demand-price elasticity could potentially impact accuracy of electricity price forecasting and generation capacity adequacy evaluation, which have not been thoroughly explored in literature. To this end, a probabilistic model is developed to evaluate marginal electricity price and capacity adequacy of power systems with elastic demand, while considering uncertainties of both demand and supply sides (e.g., random outages of generating units with multi-bidding-segments as well as variability of renewable energy outputs). Specifically, based on the concept of marginal bidding segment, the probability of a bidding segment being marginal is computed via the probabilistic production simulation approach. Accordingly, the discrete probability distribution of marginal electricity price can be obtained, which is further used to calculate mean and variance of marginal electricity price with elastic demand. Moreover, considering the interaction between elastic demands and uncertain electricity prices, the loss-of-load probability and the expected unserved energy are further estimated. Numerical studies are presented to validate effectiveness of the proposed method.

A FLISR approach for distribution networks integrated distributed generators

The penetration of distributed generators (DG ) into the distribution etworks (DN) greatly improves the reliability of electricity supply and reduces power loss. However, the operation of these DGs can also make the protection of distribution etwork more complex. This paper will examine the effects of two DG types on the protection of DN by analyzing the solution called Fault Location, Isolation and Service Restoration (FLISR). The FLISR approach considers DGs as auxiliary sources for the post-fault restoration plans in order to minimize the number of interrupted customers and unserved energy. Moreover, the combination of setting value of the overcurrent relay and the statuses of switching device and the loss voltage warning signal are used to detect and identify types of incidents in the distribution etwork with DGs. A two-constrained objective function will be solved to find possible plans for fault isolation and service restoration. There are six performance indices (PIs) selected for post-fault service restoration processing. The simulation results for the 22kV distribution network with integrated DG were performed by using E-terra software to validate this FLISR approach. To be concluded, the FLISR approach well adapt to the integration of DG into the DN and also helps to identify risks from false protection-coordination. On the other hand, it also helps to quickly detect and identify types of incidents as well as evaluate service restoration plans after incidents of distribution etwork with DG less than two minutes.

Improving Energy Transition Analysis Tool through Hydropower Statistical Modelling

Reservoir and pumped hydro storage facilities represent one of the best options for providing flexibility at low marginal cost and very low life cycle carbon emissions. However, hydropower generation is subject to physical, environmental and regulatory constraints, which introduce complexity in the modelling of hydropower in the context of transition energy analysis. In this article, a probabilistic model for hydropower generation is developed in order to improve an hourly-resolved tool for transition path analysis presented in previous research. The model is based on time series analysis, which exploits the fact that the different constraints affecting hydropower generation were met in the past. The upgraded version of the transition path analysis tool shows a decrease in the hydropower flexibility as compared with previous published results, providing a better picture of the benefits and drawbacks associated with a specific transition path under analysis, for example in terms of assessing the probability of unserved energy. The upgraded version of the tool was employed to analyse the Spanish National Energy and Climate Plan (NECP), finding consistence between proposals associated with the power system and related CO2 reduction and share of renewable electricity targets.

An Evaluation of the Economic and Resilience Benefits of a Microgrid in Northampton, Massachusetts

Recent developments and advances in distributed energy resource (DER) technologies make them valuable assets in microgrids. This paper presents an innovative evaluation framework for microgrid assets to capture economic benefits from various grid and behind-the-meter services in grid-connecting mode and resilience benefits in islanding mode. In particular, a linear programming formulation is used to model different services and DER operational constraints to determine the optimal DER dispatch to maximize economic benefits. For the resiliency analysis, a stochastic evaluation procedure is proposed to explicitly quantify the microgrid survivability against a random outage, considering uncertainties associated with photovoltaic (PV) generation, system load, and distributed generator failures. Optimal coordination strategies are developed to minimize unserved energy and improve system survivability, considering different levels of system connectedness. The proposed framework has been applied to evaluate a proposed microgrid in Northampton, Massachusetts that would link the Northampton Department of Public Works, Cooley Dickenson Hospital, and Smith Vocational Area High School. The findings of this analysis indicate that over a 20-year economic life, a 441 kW/441 kWh battery energy storage system, and 386 kW PV solar array can generate $2.5 million in present value benefits, yielding a 1.16 return on investment ratio. Results of this study also show that forming a microgrid generally improves system survivability, but the resilience performance of individual facilities varies depending on power-sharing strategies.

Correction to “Minimizing Unserved Energy Using Heterogeneous Storage Units” [Sep 19 3647-3656

Correction to “Minimizing Unserved Energy Using Heterogeneous Storage Units” [Sep 19 3647-3656

Assessing the potential of battery storage as a peaking capacity resource in the United States

In 2018, the United States Federal Energy Regulatory Commission established an order requiring all energy market operators in their jurisdiction to allow storage resources to participate as capacity resources. In response to the order, each market operator specified a minimum duration for storage resources to meet or exceed to qualify as peaking capacity. In this work, we assess the impacts of minimum storage duration requirements on energy storage buildout and system operation through 2050 in the United States electricity grid. We also investigate the role that future capital cost reductions play in energy storage deployment in the United States. We use a national-scale capacity expansion model and allow the model to choose from a suite of competing technologies, including battery storage devices of various durations as it builds out a least-cost system. We consider scenarios different minimum storage durations and storage cost projections. We find there is substantial economic potential – greater than 100 GW in some cases – for storage with durations of ten hours or less to provide peaking capacity in the United States. We also find that storage deployment is sensitive to minimum storage duration requirements. Longer requirements reduce the amount of storage deployed. Shorter requirements lead to more deployment, but if they are not adjusted to account for the declining capacity credit of storage, there is greater risk for instances of unserved energy. Our results indicate that the design and implementation of duration requirements can have substantial impacts on storage deployment and broader system reliability.

Multiobjective generation and transmission expansion planning of renewable dominated power systems using stochastic normalized normal constraint

This paper proposes a comprehensive framework for generation and transmission planning of renewable dominated power systems, which is formulated as a stochastic multiobjective problem. In this regard, a Normalized Normal Constraint (NNC) solution approach is proposed to solve the introduced stochastic multiobjective generation and transmission planning (GTP) problem. The NNC is utilized in this paper as a relation between different objective functions with different dimensions to find the optimal weighting factors of these objectives. The NNC is applied for solving the GTP problem with objective functions including the investment and operation costs along with the transmission losses, while considering the cost of unserved energy, as well as the uncertainty of load and Renewable Energy Resources (RERs). A fuzzy-based decision making framework is utilized to select the best solution among the optimal non-dominated solution points. A scenario-based approach is used to model the uncertainties. The Garver 6-bus and IEEE 118-bus test systems are utilized to perform the numerical analysis. The simulation results validate the performance and importance of the proposed model, as well as the effectiveness of the NNC to find the evenly distributed Pareto solutions of the multiobjective problems.

Probability-Interval-Based Optimal Planning of Integrated Energy System With Uncertain Wind Power

Owing to a higher energy supply efficiency and operational flexibility, integrated energy system (IES), including the power, heating, and gas systems, will be the primary form of energy supply in the future. However, with the increase of large-scale stochastic wind power integration, the IES planning will face a significant challenge as the traditional power system. Therefore, a probability-interval-based IES planning considering wind power integration is proposed in this article. First, a conditional value-at-risk (CVaR) based probability-interval method is developed to describe the uncertain wind power. Second, beside traditional facilities, electricity storage system is introduced to improve the flexibility of IES. Then, an expansion planning model for IES is established to minimize the total cost including investment, operation, CVaR cost, and unserved energy cost. Moreover, the piecewise linearization method is used to deal with the nonlinear integral terms of the proposed model to improve the solution efficiency. Finally, IEEE14-NGS14 and IEEE118-NGS40 systems are constructed and the planning model is solved by GAMS/CPLEX. The numerical results illustrate the correctness and effectiveness of the proposed method.