[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-85844-en":3,"doc-seo-85844-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},85844,8796095461610,"Oliver","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Comparing Socially-Equitable Renewable Energy Budget Allocation MDP Policies in Mature and Emerging Economies","Equitable renewable-energy planning is modeled as a sequential decision problem whose available levers differ between mature and emerging economies. This work formulates socially-equitable renewable-energy budget allocation as a Markov Decision Process (MDP) and evaluates the same policies across U.S. cities and West Java, Indonesia using a single solver interface. Results show a receding-horizon value-iteration policy dominates, improving renewable penetration while reducing low-income harm. A market-chasing heuristic can become catastrophically inequitable in Indonesia.","Comparing Socially-Equitable Renewable Energy Budget Allocation MDP Policies in Mature and Emerging Economies  \nRiya Kinnarkar  \nManagement & Technology University of Pennsylvania Philadelphia, PA, USA  \nYan Pratama Akhra  \nIndustrial and Systems Engineering Institute Technology of Sepuluh Nopember (ITS) Surabaya, Indonesia  \nMansur M. Arief  \nIndustrial and Systems Engineering King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia  \nDino Arla  \nPT PLN Persero Indramayu, Indonesia  \narXiv :2607 . 10201v1 [ ee ss . SY] 11 Jul 2026  \nAbstract—Equitable renewable-energy planning is a sequential decision problem, but the decision variables available toa public planner differ sharply between mature and emerging economies. In the former the government largely builds generation, while in the latter it steers private investment through incentives and quotas. We formulate socially-equitable renewable-energy budget allocation as a Markov Decision Process (MDP) and, using a single problem-agnostic solver interface, compare the same policies across the two settings: eight U.S. cities (a mature economy) and West Java, Indonesia (an emerging economy). The results show that across both settings, a receding-horizon value-iteration policy dominates. In the U.S., it reaches 66% renewable penetration while cutting the underserved low-income population by 96% versus a random baseline. In West Java it closes the low-access gap while crowding in the most private capital. More interestingly, a naive market-chasing heuristic, which is mildly sub-optimal in the U.S., could yield catastrophic outcomes in Indonesia, by underserving every low-access region, because chasing attractive markets and serving the underserved goals diverge once the planner acts through private developers.  \nIndex Terms—Renewable energy, social equity, Markov Decision Process, grid optimization, energy justice  \nI. INTRODUCTION  \nThe transition to renewable energy is not only a technical challenge but also a societal one. Grids designed for dispatchable fossil generation struggle to absorb variable wind and solar, and while renewable investment has surged, grid infrastructure funding has lagged, leaving thousands of gigawatts of projects awaiting connection [1] . At the sametime, the burdens of an unreliable grid fall disproportionatelyon low-income and socially vulnerable communities: U.S. households in poverty spend more than twice the average share of income on energy [2], and after major storms, communities lower on the CDC social vulnerability index wait significantly longer for power to return [3] . Yet most renewable-energy planning tools optimize cost and reliability while treating equity as an add-on. Embedding social  \nequity directly into the planner’s objective is therefore both a modeling and a policy need.  \nThe crux of this paper is that the public levers for driving an equitable renewable transition differ fundamentally between mature and emerging economies. In a mature economy such as the U.S., a public planner can directly finance and build generation under a capital budget. Inan emerging economy such as Indonesia, most renewable capacity is built by private companies and independent power producers selling to the state utility; the government’s lever is not construction but incentives and quotas that steer where private capital flows. A planning model—and the policy insights drawn from it—may not survive this shift. We therefore formulate socially-equitable budget allocation as a Markov Decision Process (MDP) and evaluate the same set of policies on two settings: eight U.S. cities (the planner builds) and West Java, Indonesia (the planner incentivizes) . We compare exact value iteration [4], Monte Carlo Tree Search (MCTS) [5], and equity- and marketoriented heuristics, and cross-deploy each policy’s inductive bias from one setting to the other.  \nOur contribution is as follows. First, we build a MDP model of socially-equitable renewable-energy bu","cbCaieTF4vFjtXEz","https://ap.wps.com/l/cbCaieTF4vFjtXEz","pdf",252801,3,1,5,"English","en",105,"# Introduction\n# Related Work","[{\"question\":\"How does the paper define socially-equitable renewable-energy budget allocation across different economies?\",\"answer\":\"It defines the planning problem as a Markov Decision Process that captures socially-equitable budget allocation while reflecting that public levers differ across mature and emerging economies.\"},{\"question\":\"What policy approach performs best in both the U.S. and West Java?\",\"answer\":\"A receding-horizon value-iteration policy dominates across both settings.\"},{\"question\":\"Why can a market-chasing heuristic succeed in the U.S. but fail in Indonesia?\",\"answer\":\"Because in the U.S. the planner primarily builds generation, whereas in Indonesia the planner steers private developers via incentives and quotas, the objectives can diverge and cause severe underserving of low-access regions.\"}]",1784206657,13,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"comparing-socially-equitable-renewable-energy-budget-allocation-mdp-policies-in-mature-and-emerging-economies","",{"@graph":36,"@context":85},[37,53,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,50],{"item":41,"name":42,"@type":43,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":20},"https://docshare.wps.com/document/research-report/",{"item":51,"name":13,"@type":43,"position":52},"https://docshare.wps.com/document/comparing-socially-equitable-renewable-energy-budget-allocation-mdp-policies-in-mature-and-emerging-economies/85844/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":24,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-25","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"How does the paper define socially-equitable renewable-energy budget allocation across different economies?","Question",{"text":75,"@type":76},"It defines the planning problem as a Markov Decision Process that captures socially-equitable budget allocation while reflecting that public levers differ across mature and emerging economies.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What policy approach performs best in both the U.S. and West Java?",{"text":80,"@type":76},"A receding-horizon value-iteration policy dominates across both settings.",{"name":82,"@type":73,"acceptedAnswer":83},"Why can a market-chasing heuristic succeed in the U.S. but fail in Indonesia?",{"text":84,"@type":76},"Because in the U.S. the planner primarily builds generation, whereas in Indonesia the planner steers private developers via incentives and quotas, the objectives can diverge and cause severe underserving of low-access regions.","https://schema.org",{"og:url":51,"og:type":87,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":89,"canonical":51},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":92},[93,97,101,105,109,114,119,122,127,130,134],{"id":21,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":22,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":22,"slug":137},19,"General","general"]